本文参考东北证券研报《基于阶段划分的中美两国股市价格联动关系研究》内容，对沪深300和标普500两个指数的价格联动关系进行了研究。20实际80年代以来，金融自由化和经济一体化使国际资本流动趋势不断加强，金融信息和风险在全球范围内传播的途径和速度都出现不断上升的趋势。随着杭锅加入WTO，印日QFII和QDII制度，进行股权分置改革，汇率改制，经历全球经济危机等一系列事件，中国股市与世界资本市场之间的关系也越来越紧密。
【1】通过长期均衡检验验证中美两国不同杰顿的同步性和影响关系的持续性。
【2】对于短期价格引导关系使用格兰杰因果检验检验美股对A股的短期冲击。
随着海外资金投资A股的渠道服日渐丰富以及投资额度的平稳增加，A股与每股体现出的联动关系逐渐增强。
【1】时间范围：2007.1 ～ 2019.6
【2】研究指数：沪深300、标普500
【3】区间划分：2007.10.9，2014.11.17，2016.12.5，2019.5.30
本文参考东北证券研报《基于阶段划分的中美两国股市价格联动关系研究》内容，对沪深300和标普500两个指数的价格联动关系进行了研究。20实际80年代以来，金融自由化和经济一体化使国际资本流动趋势不断加强，金融信息和风险在全球范围内传播的途径和速度都出现不断上升的趋势。随着杭锅加入WTO，印日QFII和QDII制度，进行股权分置改革，汇率改制，经历全球经济危机等一系列事件，中国股市与世界资本市场之间的关系也越来越紧密。
【1】通过长期均衡检验验证中美两国不同杰顿的同步性和影响关系的持续性。
【2】对于短期价格引导关系使用格兰杰因果检验检验美股对A股的短期冲击。
随着海外资金投资A股的渠道服日渐丰富以及投资额度的平稳增加，A股与每股体现出的联动关系逐渐增强。
【1】时间范围：2007.1 ～ 2019.6
【2】研究指数：沪深300、标普500
【3】区间划分：2007.10.9，2014.11.17，2016.12.5，2019.5.30
from jqdata import *
import numpy as np
import pandas as pd
import statsmodels.api as sm
import warnings
warnings.filterwarnings('ignore')
#获取SP500与HS300指数数据
q = query(finance.GLOBAL_IDX_DAILY).filter(finance.GLOBAL_IDX_DAILY.code=='INX').order_by(finance.GLOBAL_IDX_DAILY.day.desc())
SP500_df = finance.run_query(q)
HS300_df = get_price('000300.XSHG', start_date = datetime.date(2005,7,1), end_date = datetime.date(2019,5,30))
在数据选取上，我们采用了最近15年两国股市代表性指数的开盘价和收盘价作为样本，由于文化差异了两国交易日并不完全匹配，存在不同的休市日期，我们选取的交易日数据为提出不匹配的数据吼得到的交叉日期，共3274组。
#交易日获取函数
def get_trade_day_list(start_date, end_date):
date_df = get_price('000001.XSHG', start_date = start_date, end_date = end_date)
date_list = []
for item in list(date_df.index):
item = str(item)
y = int(item[0:4])
m = int(item[5:7])
d = int(item[8:10])
date_list.append(datetime.date(y,m,d))
return date_list
#定义重合交易日获取函数
def get_common_days(df_1, df_2, start_day, end_day):
trade_day_list = get_trade_day_list(start_day, end_day)
common_date_list = []
for day in trade_day_list:
if day in df_1.index:
if day in list(df_2['day']):
common_date_list.append(day)
return common_date_list
#获取不同时间段重合交易日
total_common_days = get_common_days(HS300_df, SP500_df, datetime.date(2005,7,1), datetime.date(2019,5,30))
common_days_1 = get_common_days(HS300_df, SP500_df, datetime.date(2005,7,1), datetime.date(2007,10,9))
common_days_2 = get_common_days(HS300_df, SP500_df, datetime.date(2007,10,10), datetime.date(2014,11,16))
common_days_3 = get_common_days(HS300_df, SP500_df, datetime.date(2014,11,17), datetime.date(2016,12,4))
common_days_4 = get_common_days(HS300_df, SP500_df, datetime.date(2016,12,5), datetime.date(2019,5,30))
#整理SP500数据格式
def get_sp_price(index_df, time_period):
index_price_df = pd.DataFrame()
day_list = []
open_list = []
close_list = []
high_list = []
low_list = []
volume_list = []
for day in time_period:
day_index = index_df[(index_df.day == day)].index.tolist()[0]
day_list.append(day)
open_list.append(index_df.loc[day_index, 'open'])
close_list.append(index_df.loc[day_index, 'close'])
high_list.append(index_df.loc[day_index, 'high'])
low_list.append(index_df.loc[day_index, 'low'])
volume_list.append(index_df.loc[day_index, 'volume'])
index_price_df['open'] = open_list
index_price_df['close'] = close_list
index_price_df['high'] = high_list
index_price_df['low'] = low_list
index_price_df['volume'] = volume_list
index_price_df = index_price_df.T
index_price_df.columns = day_list
index_price_df = index_price_df.T
return index_price_df
#整理整体量价数据
SP500_df = get_sp_price(SP500_df, total_common_days)
HS300_df = HS300_df.loc[total_common_days]
#整理不同周期内量价数据
SP500_df_1 = SP500_df.loc[common_days_1]
SP500_df_2 = SP500_df.loc[common_days_2]
SP500_df_3 = SP500_df.loc[common_days_3]
SP500_df_4 = SP500_df.loc[common_days_4]
HS300_df_1 = HS300_df.loc[common_days_1]
HS300_df_2 = HS300_df.loc[common_days_2]
HS300_df_3 = HS300_df.loc[common_days_3]
HS300_df_4 = HS300_df.loc[common_days_4]
#SP500与HS300行情图
close_curve_df = pd.DataFrame()
close_curve_df['HS300'] = HS300_df['close']
close_curve_df['SP500'] = SP500_df['close']
close_curve_df.plot(figsize = (20,12))
<matplotlib.axes._subplots.AxesSubplot at 0x7f8179ad0278>
金融市场中许多变量的时间序列数据是非平稳的，传统的数理统计和经济计量方法很难适用，但在有些时候，两个非平稳序列的某种特定线性组合会变为平稳序列，我们就成这个非平稳过程为协整过程。本文采用协会智能检验来确定两指数的日度收盘价时都具有长期的均衡关系，描述性统计见下表：
#获取基础统计量
basic_stats_df = pd.DataFrame()
SP500_basic_stats = []
SP500_basic_stats.append(len(SP500_df['close']))
SP500_basic_stats.append(SP500_df['close'].mean())
SP500_basic_stats.append(SP500_df['close'].std())
SP500_basic_stats.append(SP500_df['close'].min())
SP500_basic_stats.append(np.percentile(SP500_df['close'], 25))
SP500_basic_stats.append(np.percentile(SP500_df['close'], 50))
SP500_basic_stats.append(np.percentile(SP500_df['close'], 75))
SP500_basic_stats.append(SP500_df['close'].max())
basic_stats_df['SP500'] = SP500_basic_stats
HS300_basic_stats = []
HS300_basic_stats.append(len(HS300_df['close']))
HS300_basic_stats.append(HS300_df['close'].mean())
HS300_basic_stats.append(HS300_df['close'].std())
HS300_basic_stats.append(HS300_df['close'].min())
HS300_basic_stats.append(np.percentile(HS300_df['close'], 25))
HS300_basic_stats.append(np.percentile(HS300_df['close'], 50))
HS300_basic_stats.append(np.percentile(HS300_df['close'], 75))
HS300_basic_stats.append(HS300_df['close'].max())
basic_stats_df['HS300'] = HS300_basic_stats
basic_stats_df = basic_stats_df.T
basic_stats_df.columns = ['count', 'avg', 'std', 'min', '25%', '50%', '75%', 'max']
basic_stats_df
| count | avg | std | min | 25% | 50% | 75% | max | |
|---|---|---|---|---|---|---|---|---|
| SP500 | 3274.0 | 1683.929997 | 556.987238 | 676.53 | 1265.4425 | 1466.140 | 2082.3575 | 2945.83 |
| HS300 | 3274.0 | 2953.719517 | 962.279231 | 824.10 | 2363.7525 | 3064.155 | 3513.2200 | 5877.20 |
从描述性统计值观察，整个样本期内沪深300更为剧烈，标普500整体呈现缓慢上涨态势。随后我们计算了不同阶段的相关系数，在第一阶段二者相关系数达到了0.87，我们不任务是二者存在内在联动关系只是由于中美两国股市偶然性均处于上涨行情中，从第二至第四阶段的相关性可知，两国股市关联性并不高，均低于25%。
#统计相关系数
corr_df = pd.DataFrame()
corr_list = []
start_list = []
end_list = []
total_corr = SP500_df['close'].corr(HS300_df['close'])
total_start = str(total_common_days[0])
total_end = str(total_common_days[-1])
corr_list.append(total_corr)
start_list.append(total_start)
end_list.append(total_end)
corr_1 = SP500_df_1['close'].corr(HS300_df_1['close'])
start_1 = str(common_days_1[0])
end_1 = str(common_days_1[-1])
corr_list.append(corr_1)
start_list.append(start_1)
end_list.append(end_1)
corr_2 = SP500_df_2['close'].corr(HS300_df_2['close'])
start_2 = str(common_days_2[0])
end_2 = str(common_days_2[-1])
corr_list.append(corr_2)
start_list.append(start_2)
end_list.append(end_2)
corr_3 = SP500_df_3['close'].corr(HS300_df_3['close'])
start_3 = str(common_days_3[0])
end_3 = str(common_days_3[-1])
corr_list.append(corr_3)
start_list.append(start_3)
end_list.append(end_3)
corr_4 = SP500_df_4['close'].corr(HS300_df_4['close'])
start_4 = str(common_days_4[0])
end_4 = str(common_days_4[-1])
corr_list.append(corr_4)
start_list.append(start_4)
end_list.append(end_4)
corr_df['start'] = start_list
corr_df['end'] = end_list
corr_df['corr'] = corr_list
corr_df = corr_df.T
corr_df.columns = ['all', '1', '2', '3', '4']
corr_df = corr_df.T
corr_df
| start | end | corr | |
|---|---|---|---|
| all | 2005-07-01 | 2019-05-30 | 0.416866 |
| 1 | 2005-07-01 | 2007-10-09 | 0.874911 |
| 2 | 2007-10-10 | 2014-11-14 | -0.152778 |
| 3 | 2014-11-17 | 2016-12-02 | 0.247359 |
| 4 | 2016-12-05 | 2019-05-30 | 0.223405 |
对长期均衡关系进行检验，首先利用单位根检验平稳性。由下表可知两者的原始价格数据均不平稳，一阶差分序列是平稳的时间序列数据，沪深300与标普500价格序列数据属于同阶单整，可以做协整检验，检验方法是Engle-Granger协整检验。
#ADF检验输出结果转换函数
def get_ADF_results(array):
ADF_df = pd.DataFrame()
ADF_results = sm.tsa.stattools.adfuller(array)
ADF_list = []
ADF_list.append(ADF_results[0])
ADF_list.append(ADF_results[1])
ADF_list.append(ADF_results[2])
ADF_list.append(ADF_results[3])
ADF_list.append(ADF_results[4]['1%'])
ADF_list.append(ADF_results[4]['5%'])
ADF_list.append(ADF_results[4]['10%'])
ADF_df['ADF'] = ADF_list
return ADF_df
#平稳性检验
ADF_df = pd.DataFrame()
ADF_df['SP500'] = get_ADF_results(SP500_df['close'])['ADF']
ADF_df['HS300'] = get_ADF_results(HS300_df['close'])['ADF']
ADF_df['SP500_diff'] = get_ADF_results(SP500_df['close'].diff()[1:])['ADF']
ADF_df['HS300_diff'] = get_ADF_results(HS300_df['close'].diff()[1:])['ADF']
ADF_df = ADF_df.T
ADF_df.columns = ['ADF_stat', 'P_value', 'Lag_used', 'Number_of_observations_used', '1%', '5%', '10%']
ADF_df = ADF_df.T
ADF_df
| SP500 | HS300 | SP500_diff | HS300_diff | |
|---|---|---|---|---|
| ADF_stat | 0.346095 | -2.709413 | -1.170604e+01 | -9.792798e+00 |
| P_value | 0.979363 | 0.072423 | 1.528120e-21 | 6.288054e-17 |
| Lag_used | 24.000000 | 27.000000 | 2.300000e+01 | 2.600000e+01 |
| Number_of_observations_used | 3249.000000 | 3246.000000 | 3.249000e+03 | 3.246000e+03 |
| 1% | -3.432364 | -3.432366 | -3.432364e+00 | -3.432366e+00 |
| 5% | -2.862430 | -2.862431 | -2.862430e+00 | -2.862431e+00 |
| 10% | -2.567244 | -2.567244 | -2.567244e+00 | -2.567244e+00 |
接下来进行全部时段样本和分阶段样本协整检验，从下表来看，检验结果与两指数的关系一直，无论是整体区间还是各阶段样本，协整检验均不能通过，两者不存在长期均衡关系。我们认为中美两国股市长期走势相对独立，不存在长期均衡的关联特征。
#Engle-Granger协整检验输出结果转换函数
def get_EG_results(array_1, array_2):
EG_df = pd.DataFrame()
EG_results = sm.tsa.stattools.coint(array_1, array_2)
EG_list = []
EG_list.append(EG_results[0])
EG_list.append(EG_results[1])
EG_list.append(EG_results[2][0])
EG_list.append(EG_results[2][1])
EG_list.append(EG_results[2][2])
EG_df['EG'] = EG_list
return EG_df
#协整检验
EG_df = pd.DataFrame()
EG_df['Total'] = get_EG_results(SP500_df['close'], HS300_df['close'])['EG']
EG_df['Period_1'] = get_EG_results(SP500_df_1['close'], HS300_df_1['close'])['EG']
EG_df['Period_2'] = get_EG_results(SP500_df_2['close'], HS300_df_2['close'])['EG']
EG_df['Period_3'] = get_EG_results(SP500_df_3['close'], HS300_df_3['close'])['EG']
EG_df['Period_4'] = get_EG_results(SP500_df_4['close'], HS300_df_4['close'])['EG']
EG_df = EG_df.T
EG_df.columns = ['stat', 'P_value', '1%', '5%', '10%']
EG_df = EG_df.T
EG_df
| Total | Period_1 | Period_2 | Period_3 | Period_4 | |
|---|---|---|---|---|---|
| stat | -0.173920 | -2.003504 | -0.096613 | -2.035797 | -1.742232 |
| P_value | 0.980931 | 0.526756 | 0.983386 | 0.509927 | 0.657334 |
| 1% | -3.899789 | -3.917106 | -3.903010 | -3.919258 | -3.915292 |
| 5% | -3.337997 | -3.347618 | -3.339791 | -3.348810 | -3.346613 |
| 10% | -3.045746 | -3.052417 | -3.046991 | -3.053243 | -3.051720 |
即使在上一部分分析中没有得到中美两国股票市场长期均衡关系的结论，但多种现象表明美国股票市场价格变化短期异动对于A股有着比较大的冲击，因此本届着重检验美国股票市场价格变化对A股走势的价格引导作用。在这里我们采用对数收益率的计算方式以更好地考察两国股市影响过程。下图即为两指数15年对应收益率变化。
#开盘收益率计算函数
def r_op_cal(stock_df):
index_list = list(stock_df.index)
r_op_list = [0]
for item in index_list[1:]:
loc = index_list.index(item)
last_day = index_list[loc - 1]
op = stock_df.loc[item, 'open']
cl = stock_df.loc[last_day, 'close']
r_op_list.append(log(op) - log(cl))
stock_df['R_OP'] = r_op_list
return stock_df
#收盘收益率计算函数
def r_cl_cal(stock_df):
index_list = list(stock_df.index)
r_cl_list = []
for item in index_list:
op = stock_df.loc[item, 'open']
cl = stock_df.loc[item, 'close']
r_cl_list.append(log(cl) - log(op))
stock_df['R_CL'] = r_cl_list
return stock_df
#整理整体量价数据
SP500_df = r_op_cal(SP500_df)
SP500_df = r_cl_cal(SP500_df)
HS300_df = r_op_cal(HS300_df)
HS300_df = r_cl_cal(HS300_df)
#整理不同周期内量价数据
SP500_df_1 = SP500_df.loc[common_days_1]
SP500_df_2 = SP500_df.loc[common_days_2]
SP500_df_3 = SP500_df.loc[common_days_3]
SP500_df_4 = SP500_df.loc[common_days_4]
HS300_df_1 = HS300_df.loc[common_days_1]
HS300_df_2 = HS300_df.loc[common_days_2]
HS300_df_3 = HS300_df.loc[common_days_3]
HS300_df_4 = HS300_df.loc[common_days_4]
#SP500开盘收益率
SP500_df['R_OP'].plot(figsize = (20,12))
<matplotlib.axes._subplots.AxesSubplot at 0x7f8179e04518>
#SP500收盘收益率
SP500_df['R_CL'].plot(figsize = (20,12))
<matplotlib.axes._subplots.AxesSubplot at 0x7f817a00da20>
#HS300开盘收益率
HS300_df['R_OP'].plot(figsize = (20,12))
<matplotlib.axes._subplots.AxesSubplot at 0x7f8179b78710>
#HS300收盘收益率
HS300_df['R_CL'].plot(figsize = (20,12))
<matplotlib.axes._subplots.AxesSubplot at 0x7f817a4e15f8>
利用格兰杰因果关系检验中美股市领先之后因果关系，充分考虑中美股市交易时间的不同步，为确保结果稳健，吻别研究-5阶之后向检验结果，根据AIC准则确定最佳滞后期，通常为1期，结果如下：
#Granger因果检验F,T
def get_G_results(result_array, cause_array, maxlag):
G_df = pd.DataFrame()
G_df['result'] = result_array
G_df['cause'] = cause_array
F_list = []
P_list = []
G_result = sm.tsa.stattools.grangercausalitytests(G_df, maxlag)
for item in range(1,(maxlag + 1)):
F_list.append(G_result[item][0]['ssr_ftest'][0])
P_list.append(G_result[item][0]['ssr_ftest'][1])
G_result_df = pd.DataFrame()
G_result_df['F'] = F_list
G_result_df['P'] = P_list
return G_result_df
#日频数据——(HSOP,SPCL)
daily_1_df = pd.DataFrame()
daily_1_df['F_1'] = get_G_results(HS300_df_1['R_OP'], SP500_df_1['R_CL'], 5)['F']
daily_1_df['P_1'] = get_G_results(HS300_df_1['R_OP'], SP500_df_1['R_CL'], 5)['P']
daily_1_df['F_2'] = get_G_results(HS300_df_2['R_OP'], SP500_df_2['R_CL'], 5)['F']
daily_1_df['P_2'] = get_G_results(HS300_df_2['R_OP'], SP500_df_2['R_CL'], 5)['P']
daily_1_df['F_3'] = get_G_results(HS300_df_3['R_OP'], SP500_df_3['R_CL'], 5)['F']
daily_1_df['P_3'] = get_G_results(HS300_df_3['R_OP'], SP500_df_3['R_CL'], 5)['P']
daily_1_df['F_4'] = get_G_results(HS300_df_4['R_OP'], SP500_df_4['R_CL'], 5)['F']
daily_1_df['P_4'] = get_G_results(HS300_df_4['R_OP'], SP500_df_4['R_CL'], 5)['P']
daily_1_df
Granger Causality number of lags (no zero) 1 ssr based F test: F=8.4237 , p=0.0039 , df_denom=530, df_num=1 ssr based chi2 test: chi2=8.4714 , p=0.0036 , df=1 likelihood ratio test: chi2=8.4048 , p=0.0037 , df=1 parameter F test: F=8.4237 , p=0.0039 , df_denom=530, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=4.1516 , p=0.0163 , df_denom=527, df_num=2 ssr based chi2 test: chi2=8.3819 , p=0.0151 , df=2 likelihood ratio test: chi2=8.3166 , p=0.0156 , df=2 parameter F test: F=4.1516 , p=0.0163 , df_denom=527, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=3.1324 , p=0.0253 , df_denom=524, df_num=3 ssr based chi2 test: chi2=9.5228 , p=0.0231 , df=3 likelihood ratio test: chi2=9.4385 , p=0.0240 , df=3 parameter F test: F=3.1324 , p=0.0253 , df_denom=524, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=2.5761 , p=0.0368 , df_denom=521, df_num=4 ssr based chi2 test: chi2=10.4823 , p=0.0330 , df=4 likelihood ratio test: chi2=10.3800 , p=0.0345 , df=4 parameter F test: F=2.5761 , p=0.0368 , df_denom=521, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=1.9792 , p=0.0802 , df_denom=518, df_num=5 ssr based chi2 test: chi2=10.1061 , p=0.0723 , df=5 likelihood ratio test: chi2=10.0108 , p=0.0749 , df=5 parameter F test: F=1.9792 , p=0.0802 , df_denom=518, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=8.4237 , p=0.0039 , df_denom=530, df_num=1 ssr based chi2 test: chi2=8.4714 , p=0.0036 , df=1 likelihood ratio test: chi2=8.4048 , p=0.0037 , df=1 parameter F test: F=8.4237 , p=0.0039 , df_denom=530, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=4.1516 , p=0.0163 , df_denom=527, df_num=2 ssr based chi2 test: chi2=8.3819 , p=0.0151 , df=2 likelihood ratio test: chi2=8.3166 , p=0.0156 , df=2 parameter F test: F=4.1516 , p=0.0163 , df_denom=527, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=3.1324 , p=0.0253 , df_denom=524, df_num=3 ssr based chi2 test: chi2=9.5228 , p=0.0231 , df=3 likelihood ratio test: chi2=9.4385 , p=0.0240 , df=3 parameter F test: F=3.1324 , p=0.0253 , df_denom=524, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=2.5761 , p=0.0368 , df_denom=521, df_num=4 ssr based chi2 test: chi2=10.4823 , p=0.0330 , df=4 likelihood ratio test: chi2=10.3800 , p=0.0345 , df=4 parameter F test: F=2.5761 , p=0.0368 , df_denom=521, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=1.9792 , p=0.0802 , df_denom=518, df_num=5 ssr based chi2 test: chi2=10.1061 , p=0.0723 , df=5 likelihood ratio test: chi2=10.0108 , p=0.0749 , df=5 parameter F test: F=1.9792 , p=0.0802 , df_denom=518, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=828.3209, p=0.0000 , df_denom=1667, df_num=1 ssr based chi2 test: chi2=829.8116, p=0.0000 , df=1 likelihood ratio test: chi2=673.6642, p=0.0000 , df=1 parameter F test: F=828.3209, p=0.0000 , df_denom=1667, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=408.0821, p=0.0000 , df_denom=1664, df_num=2 ssr based chi2 test: chi2=818.6167, p=0.0000 , df=2 likelihood ratio test: chi2=666.0987, p=0.0000 , df=2 parameter F test: F=408.0821, p=0.0000 , df_denom=1664, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=274.3675, p=0.0000 , df_denom=1661, df_num=3 ssr based chi2 test: chi2=826.5712, p=0.0000 , df=3 likelihood ratio test: chi2=671.3559, p=0.0000 , df=3 parameter F test: F=274.3675, p=0.0000 , df_denom=1661, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=206.9059, p=0.0000 , df_denom=1658, df_num=4 ssr based chi2 test: chi2=832.1161, p=0.0000 , df=4 likelihood ratio test: chi2=674.9875, p=0.0000 , df=4 parameter F test: F=206.9059, p=0.0000 , df_denom=1658, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=167.0299, p=0.0000 , df_denom=1655, df_num=5 ssr based chi2 test: chi2=840.7004, p=0.0000 , df=5 likelihood ratio test: chi2=680.6306, p=0.0000 , df=5 parameter F test: F=167.0299, p=0.0000 , df_denom=1655, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=828.3209, p=0.0000 , df_denom=1667, df_num=1 ssr based chi2 test: chi2=829.8116, p=0.0000 , df=1 likelihood ratio test: chi2=673.6642, p=0.0000 , df=1 parameter F test: F=828.3209, p=0.0000 , df_denom=1667, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=408.0821, p=0.0000 , df_denom=1664, df_num=2 ssr based chi2 test: chi2=818.6167, p=0.0000 , df=2 likelihood ratio test: chi2=666.0987, p=0.0000 , df=2 parameter F test: F=408.0821, p=0.0000 , df_denom=1664, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=274.3675, p=0.0000 , df_denom=1661, df_num=3 ssr based chi2 test: chi2=826.5712, p=0.0000 , df=3 likelihood ratio test: chi2=671.3559, p=0.0000 , df=3 parameter F test: F=274.3675, p=0.0000 , df_denom=1661, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=206.9059, p=0.0000 , df_denom=1658, df_num=4 ssr based chi2 test: chi2=832.1161, p=0.0000 , df=4 likelihood ratio test: chi2=674.9875, p=0.0000 , df=4 parameter F test: F=206.9059, p=0.0000 , df_denom=1658, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=167.0299, p=0.0000 , df_denom=1655, df_num=5 ssr based chi2 test: chi2=840.7004, p=0.0000 , df=5 likelihood ratio test: chi2=680.6306, p=0.0000 , df=5 parameter F test: F=167.0299, p=0.0000 , df_denom=1655, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=51.1691 , p=0.0000 , df_denom=480, df_num=1 ssr based chi2 test: chi2=51.4890 , p=0.0000 , df=1 likelihood ratio test: chi2=48.9252 , p=0.0000 , df=1 parameter F test: F=51.1691 , p=0.0000 , df_denom=480, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=28.6645 , p=0.0000 , df_denom=477, df_num=2 ssr based chi2 test: chi2=57.9300 , p=0.0000 , df=2 likelihood ratio test: chi2=54.7048 , p=0.0000 , df=2 parameter F test: F=28.6645 , p=0.0000 , df_denom=477, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=19.0754 , p=0.0000 , df_denom=474, df_num=3 ssr based chi2 test: chi2=58.0712 , p=0.0000 , df=3 likelihood ratio test: chi2=54.8246 , p=0.0000 , df=3 parameter F test: F=19.0754 , p=0.0000 , df_denom=474, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=15.6220 , p=0.0000 , df_denom=471, df_num=4 ssr based chi2 test: chi2=63.6821 , p=0.0000 , df=4 likelihood ratio test: chi2=59.7978 , p=0.0000 , df=4 parameter F test: F=15.6220 , p=0.0000 , df_denom=471, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=12.4353 , p=0.0000 , df_denom=468, df_num=5 ssr based chi2 test: chi2=63.6377 , p=0.0000 , df=5 likelihood ratio test: chi2=59.7511 , p=0.0000 , df=5 parameter F test: F=12.4353 , p=0.0000 , df_denom=468, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=51.1691 , p=0.0000 , df_denom=480, df_num=1 ssr based chi2 test: chi2=51.4890 , p=0.0000 , df=1 likelihood ratio test: chi2=48.9252 , p=0.0000 , df=1 parameter F test: F=51.1691 , p=0.0000 , df_denom=480, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=28.6645 , p=0.0000 , df_denom=477, df_num=2 ssr based chi2 test: chi2=57.9300 , p=0.0000 , df=2 likelihood ratio test: chi2=54.7048 , p=0.0000 , df=2 parameter F test: F=28.6645 , p=0.0000 , df_denom=477, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=19.0754 , p=0.0000 , df_denom=474, df_num=3 ssr based chi2 test: chi2=58.0712 , p=0.0000 , df=3 likelihood ratio test: chi2=54.8246 , p=0.0000 , df=3 parameter F test: F=19.0754 , p=0.0000 , df_denom=474, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=15.6220 , p=0.0000 , df_denom=471, df_num=4 ssr based chi2 test: chi2=63.6821 , p=0.0000 , df=4 likelihood ratio test: chi2=59.7978 , p=0.0000 , df=4 parameter F test: F=15.6220 , p=0.0000 , df_denom=471, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=12.4353 , p=0.0000 , df_denom=468, df_num=5 ssr based chi2 test: chi2=63.6377 , p=0.0000 , df=5 likelihood ratio test: chi2=59.7511 , p=0.0000 , df=5 parameter F test: F=12.4353 , p=0.0000 , df_denom=468, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=262.0191, p=0.0000 , df_denom=581, df_num=1 ssr based chi2 test: chi2=263.3721, p=0.0000 , df=1 likelihood ratio test: chi2=217.3875, p=0.0000 , df=1 parameter F test: F=262.0191, p=0.0000 , df_denom=581, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=130.4991, p=0.0000 , df_denom=578, df_num=2 ssr based chi2 test: chi2=263.2560, p=0.0000 , df=2 likelihood ratio test: chi2=217.2461, p=0.0000 , df=2 parameter F test: F=130.4991, p=0.0000 , df_denom=578, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=84.9279 , p=0.0000 , df_denom=575, df_num=3 ssr based chi2 test: chi2=257.8854, p=0.0000 , df=3 likelihood ratio test: chi2=213.4747, p=0.0000 , df=3 parameter F test: F=84.9279 , p=0.0000 , df_denom=575, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=65.5503 , p=0.0000 , df_denom=572, df_num=4 ssr based chi2 test: chi2=266.3267, p=0.0000 , df=4 likelihood ratio test: chi2=219.2320, p=0.0000 , df=4 parameter F test: F=65.5503 , p=0.0000 , df_denom=572, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=52.1501 , p=0.0000 , df_denom=569, df_num=5 ssr based chi2 test: chi2=265.7915, p=0.0000 , df=5 likelihood ratio test: chi2=218.8020, p=0.0000 , df=5 parameter F test: F=52.1501 , p=0.0000 , df_denom=569, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=262.0191, p=0.0000 , df_denom=581, df_num=1 ssr based chi2 test: chi2=263.3721, p=0.0000 , df=1 likelihood ratio test: chi2=217.3875, p=0.0000 , df=1 parameter F test: F=262.0191, p=0.0000 , df_denom=581, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=130.4991, p=0.0000 , df_denom=578, df_num=2 ssr based chi2 test: chi2=263.2560, p=0.0000 , df=2 likelihood ratio test: chi2=217.2461, p=0.0000 , df=2 parameter F test: F=130.4991, p=0.0000 , df_denom=578, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=84.9279 , p=0.0000 , df_denom=575, df_num=3 ssr based chi2 test: chi2=257.8854, p=0.0000 , df=3 likelihood ratio test: chi2=213.4747, p=0.0000 , df=3 parameter F test: F=84.9279 , p=0.0000 , df_denom=575, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=65.5503 , p=0.0000 , df_denom=572, df_num=4 ssr based chi2 test: chi2=266.3267, p=0.0000 , df=4 likelihood ratio test: chi2=219.2320, p=0.0000 , df=4 parameter F test: F=65.5503 , p=0.0000 , df_denom=572, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=52.1501 , p=0.0000 , df_denom=569, df_num=5 ssr based chi2 test: chi2=265.7915, p=0.0000 , df=5 likelihood ratio test: chi2=218.8020, p=0.0000 , df=5 parameter F test: F=52.1501 , p=0.0000 , df_denom=569, df_num=5
| F_1 | P_1 | F_2 | P_2 | F_3 | P_3 | F_4 | P_4 | |
|---|---|---|---|---|---|---|---|---|
| 0 | 8.423710 | 0.003858 | 828.320927 | 3.223366e-148 | 51.169146 | 3.185251e-12 | 262.019144 | 6.444243e-49 |
| 1 | 4.151583 | 0.016257 | 408.082149 | 6.191963e-145 | 28.664530 | 1.754833e-12 | 130.499121 | 1.699032e-47 |
| 2 | 3.132435 | 0.025292 | 274.367466 | 1.263874e-144 | 19.075367 | 1.077186e-11 | 84.927884 | 1.697212e-45 |
| 3 | 2.576068 | 0.036831 | 206.905888 | 4.593938e-144 | 15.622026 | 5.184140e-12 | 65.550297 | 1.231257e-45 |
| 4 | 1.979200 | 0.080169 | 167.029919 | 5.280297e-144 | 12.435266 | 2.406184e-11 | 52.150133 | 1.585163e-44 |
#日频数据——(HSCL,SPCL)
daily_2_df = pd.DataFrame()
daily_2_df['F_1'] = get_G_results(HS300_df_1['R_CL'], SP500_df_1['R_CL'], 5)['F']
daily_2_df['P_1'] = get_G_results(HS300_df_1['R_CL'], SP500_df_1['R_CL'], 5)['P']
daily_2_df['F_2'] = get_G_results(HS300_df_2['R_CL'], SP500_df_2['R_CL'], 5)['F']
daily_2_df['P_2'] = get_G_results(HS300_df_2['R_CL'], SP500_df_2['R_CL'], 5)['P']
daily_2_df['F_3'] = get_G_results(HS300_df_3['R_CL'], SP500_df_3['R_CL'], 5)['F']
daily_2_df['P_3'] = get_G_results(HS300_df_3['R_CL'], SP500_df_3['R_CL'], 5)['P']
daily_2_df['F_4'] = get_G_results(HS300_df_4['R_CL'], SP500_df_4['R_CL'], 5)['F']
daily_2_df['P_4'] = get_G_results(HS300_df_4['R_CL'], SP500_df_4['R_CL'], 5)['P']
daily_2_df
Granger Causality number of lags (no zero) 1 ssr based F test: F=0.2313 , p=0.6308 , df_denom=530, df_num=1 ssr based chi2 test: chi2=0.2326 , p=0.6296 , df=1 likelihood ratio test: chi2=0.2326 , p=0.6296 , df=1 parameter F test: F=0.2313 , p=0.6308 , df_denom=530, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.1565 , p=0.8551 , df_denom=527, df_num=2 ssr based chi2 test: chi2=0.3161 , p=0.8538 , df=2 likelihood ratio test: chi2=0.3160 , p=0.8539 , df=2 parameter F test: F=0.1565 , p=0.8551 , df_denom=527, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.1244 , p=0.9457 , df_denom=524, df_num=3 ssr based chi2 test: chi2=0.3782 , p=0.9447 , df=3 likelihood ratio test: chi2=0.3781 , p=0.9447 , df=3 parameter F test: F=0.1244 , p=0.9457 , df_denom=524, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.1415 , p=0.9667 , df_denom=521, df_num=4 ssr based chi2 test: chi2=0.5759 , p=0.9657 , df=4 likelihood ratio test: chi2=0.5755 , p=0.9657 , df=4 parameter F test: F=0.1415 , p=0.9667 , df_denom=521, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.7799 , p=0.5645 , df_denom=518, df_num=5 ssr based chi2 test: chi2=3.9824 , p=0.5520 , df=5 likelihood ratio test: chi2=3.9675 , p=0.5541 , df=5 parameter F test: F=0.7799 , p=0.5645 , df_denom=518, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.2313 , p=0.6308 , df_denom=530, df_num=1 ssr based chi2 test: chi2=0.2326 , p=0.6296 , df=1 likelihood ratio test: chi2=0.2326 , p=0.6296 , df=1 parameter F test: F=0.2313 , p=0.6308 , df_denom=530, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.1565 , p=0.8551 , df_denom=527, df_num=2 ssr based chi2 test: chi2=0.3161 , p=0.8538 , df=2 likelihood ratio test: chi2=0.3160 , p=0.8539 , df=2 parameter F test: F=0.1565 , p=0.8551 , df_denom=527, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.1244 , p=0.9457 , df_denom=524, df_num=3 ssr based chi2 test: chi2=0.3782 , p=0.9447 , df=3 likelihood ratio test: chi2=0.3781 , p=0.9447 , df=3 parameter F test: F=0.1244 , p=0.9457 , df_denom=524, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.1415 , p=0.9667 , df_denom=521, df_num=4 ssr based chi2 test: chi2=0.5759 , p=0.9657 , df=4 likelihood ratio test: chi2=0.5755 , p=0.9657 , df=4 parameter F test: F=0.1415 , p=0.9667 , df_denom=521, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.7799 , p=0.5645 , df_denom=518, df_num=5 ssr based chi2 test: chi2=3.9824 , p=0.5520 , df=5 likelihood ratio test: chi2=3.9675 , p=0.5541 , df=5 parameter F test: F=0.7799 , p=0.5645 , df_denom=518, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=14.1395 , p=0.0002 , df_denom=1667, df_num=1 ssr based chi2 test: chi2=14.1649 , p=0.0002 , df=1 likelihood ratio test: chi2=14.1052 , p=0.0002 , df=1 parameter F test: F=14.1395 , p=0.0002 , df_denom=1667, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=7.8533 , p=0.0004 , df_denom=1664, df_num=2 ssr based chi2 test: chi2=15.7538 , p=0.0004 , df=2 likelihood ratio test: chi2=15.6799 , p=0.0004 , df=2 parameter F test: F=7.8533 , p=0.0004 , df_denom=1664, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=5.3923 , p=0.0011 , df_denom=1661, df_num=3 ssr based chi2 test: chi2=16.2452 , p=0.0010 , df=3 likelihood ratio test: chi2=16.1666 , p=0.0010 , df=3 parameter F test: F=5.3923 , p=0.0011 , df_denom=1661, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=5.2209 , p=0.0004 , df_denom=1658, df_num=4 ssr based chi2 test: chi2=20.9969 , p=0.0003 , df=4 likelihood ratio test: chi2=20.8658 , p=0.0003 , df=4 parameter F test: F=5.2209 , p=0.0004 , df_denom=1658, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=4.2131 , p=0.0008 , df_denom=1655, df_num=5 ssr based chi2 test: chi2=21.2055 , p=0.0007 , df=5 likelihood ratio test: chi2=21.0717 , p=0.0008 , df=5 parameter F test: F=4.2131 , p=0.0008 , df_denom=1655, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=14.1395 , p=0.0002 , df_denom=1667, df_num=1 ssr based chi2 test: chi2=14.1649 , p=0.0002 , df=1 likelihood ratio test: chi2=14.1052 , p=0.0002 , df=1 parameter F test: F=14.1395 , p=0.0002 , df_denom=1667, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=7.8533 , p=0.0004 , df_denom=1664, df_num=2 ssr based chi2 test: chi2=15.7538 , p=0.0004 , df=2 likelihood ratio test: chi2=15.6799 , p=0.0004 , df=2 parameter F test: F=7.8533 , p=0.0004 , df_denom=1664, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=5.3923 , p=0.0011 , df_denom=1661, df_num=3 ssr based chi2 test: chi2=16.2452 , p=0.0010 , df=3 likelihood ratio test: chi2=16.1666 , p=0.0010 , df=3 parameter F test: F=5.3923 , p=0.0011 , df_denom=1661, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=5.2209 , p=0.0004 , df_denom=1658, df_num=4 ssr based chi2 test: chi2=20.9969 , p=0.0003 , df=4 likelihood ratio test: chi2=20.8658 , p=0.0003 , df=4 parameter F test: F=5.2209 , p=0.0004 , df_denom=1658, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=4.2131 , p=0.0008 , df_denom=1655, df_num=5 ssr based chi2 test: chi2=21.2055 , p=0.0007 , df=5 likelihood ratio test: chi2=21.0717 , p=0.0008 , df=5 parameter F test: F=4.2131 , p=0.0008 , df_denom=1655, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.0119 , p=0.9131 , df_denom=480, df_num=1 ssr based chi2 test: chi2=0.0120 , p=0.9128 , df=1 likelihood ratio test: chi2=0.0120 , p=0.9128 , df=1 parameter F test: F=0.0119 , p=0.9131 , df_denom=480, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.2497 , p=0.7792 , df_denom=477, df_num=2 ssr based chi2 test: chi2=0.5045 , p=0.7770 , df=2 likelihood ratio test: chi2=0.5043 , p=0.7771 , df=2 parameter F test: F=0.2497 , p=0.7792 , df_denom=477, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.8274 , p=0.4792 , df_denom=474, df_num=3 ssr based chi2 test: chi2=2.5189 , p=0.4719 , df=3 likelihood ratio test: chi2=2.5123 , p=0.4731 , df=3 parameter F test: F=0.8274 , p=0.4792 , df_denom=474, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.5598 , p=0.6920 , df_denom=471, df_num=4 ssr based chi2 test: chi2=2.2818 , p=0.6841 , df=4 likelihood ratio test: chi2=2.2764 , p=0.6851 , df=4 parameter F test: F=0.5598 , p=0.6920 , df_denom=471, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.7649 , p=0.5754 , df_denom=468, df_num=5 ssr based chi2 test: chi2=3.9146 , p=0.5618 , df=5 likelihood ratio test: chi2=3.8987 , p=0.5641 , df=5 parameter F test: F=0.7649 , p=0.5754 , df_denom=468, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.0119 , p=0.9131 , df_denom=480, df_num=1 ssr based chi2 test: chi2=0.0120 , p=0.9128 , df=1 likelihood ratio test: chi2=0.0120 , p=0.9128 , df=1 parameter F test: F=0.0119 , p=0.9131 , df_denom=480, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.2497 , p=0.7792 , df_denom=477, df_num=2 ssr based chi2 test: chi2=0.5045 , p=0.7770 , df=2 likelihood ratio test: chi2=0.5043 , p=0.7771 , df=2 parameter F test: F=0.2497 , p=0.7792 , df_denom=477, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.8274 , p=0.4792 , df_denom=474, df_num=3 ssr based chi2 test: chi2=2.5189 , p=0.4719 , df=3 likelihood ratio test: chi2=2.5123 , p=0.4731 , df=3 parameter F test: F=0.8274 , p=0.4792 , df_denom=474, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.5598 , p=0.6920 , df_denom=471, df_num=4 ssr based chi2 test: chi2=2.2818 , p=0.6841 , df=4 likelihood ratio test: chi2=2.2764 , p=0.6851 , df=4 parameter F test: F=0.5598 , p=0.6920 , df_denom=471, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.7649 , p=0.5754 , df_denom=468, df_num=5 ssr based chi2 test: chi2=3.9146 , p=0.5618 , df=5 likelihood ratio test: chi2=3.8987 , p=0.5641 , df=5 parameter F test: F=0.7649 , p=0.5754 , df_denom=468, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=1.3987 , p=0.2374 , df_denom=581, df_num=1 ssr based chi2 test: chi2=1.4059 , p=0.2357 , df=1 likelihood ratio test: chi2=1.4042 , p=0.2360 , df=1 parameter F test: F=1.3987 , p=0.2374 , df_denom=581, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.6616 , p=0.5164 , df_denom=578, df_num=2 ssr based chi2 test: chi2=1.3346 , p=0.5131 , df=2 likelihood ratio test: chi2=1.3330 , p=0.5135 , df=2 parameter F test: F=0.6616 , p=0.5164 , df_denom=578, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=2.2947 , p=0.0769 , df_denom=575, df_num=3 ssr based chi2 test: chi2=6.9679 , p=0.0729 , df=3 likelihood ratio test: chi2=6.9265 , p=0.0743 , df=3 parameter F test: F=2.2947 , p=0.0769 , df_denom=575, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=3.5188 , p=0.0075 , df_denom=572, df_num=4 ssr based chi2 test: chi2=14.2965 , p=0.0064 , df=4 likelihood ratio test: chi2=14.1235 , p=0.0069 , df=4 parameter F test: F=3.5188 , p=0.0075 , df_denom=572, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=3.4675 , p=0.0043 , df_denom=569, df_num=5 ssr based chi2 test: chi2=17.6725 , p=0.0034 , df=5 likelihood ratio test: chi2=17.4086 , p=0.0038 , df=5 parameter F test: F=3.4675 , p=0.0043 , df_denom=569, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=1.3987 , p=0.2374 , df_denom=581, df_num=1 ssr based chi2 test: chi2=1.4059 , p=0.2357 , df=1 likelihood ratio test: chi2=1.4042 , p=0.2360 , df=1 parameter F test: F=1.3987 , p=0.2374 , df_denom=581, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.6616 , p=0.5164 , df_denom=578, df_num=2 ssr based chi2 test: chi2=1.3346 , p=0.5131 , df=2 likelihood ratio test: chi2=1.3330 , p=0.5135 , df=2 parameter F test: F=0.6616 , p=0.5164 , df_denom=578, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=2.2947 , p=0.0769 , df_denom=575, df_num=3 ssr based chi2 test: chi2=6.9679 , p=0.0729 , df=3 likelihood ratio test: chi2=6.9265 , p=0.0743 , df=3 parameter F test: F=2.2947 , p=0.0769 , df_denom=575, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=3.5188 , p=0.0075 , df_denom=572, df_num=4 ssr based chi2 test: chi2=14.2965 , p=0.0064 , df=4 likelihood ratio test: chi2=14.1235 , p=0.0069 , df=4 parameter F test: F=3.5188 , p=0.0075 , df_denom=572, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=3.4675 , p=0.0043 , df_denom=569, df_num=5 ssr based chi2 test: chi2=17.6725 , p=0.0034 , df=5 likelihood ratio test: chi2=17.4086 , p=0.0038 , df=5 parameter F test: F=3.4675 , p=0.0043 , df_denom=569, df_num=5
| F_1 | P_1 | F_2 | P_2 | F_3 | P_3 | F_4 | P_4 | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.231293 | 0.630765 | 14.139497 | 0.000176 | 0.011917 | 0.913118 | 1.398681 | 0.237428 |
| 1 | 0.156545 | 0.855133 | 7.853313 | 0.000403 | 0.249655 | 0.779171 | 0.661555 | 0.516439 |
| 2 | 0.124406 | 0.945673 | 5.392336 | 0.001080 | 0.827400 | 0.479220 | 2.294701 | 0.076864 |
| 3 | 0.141521 | 0.966674 | 5.220893 | 0.000352 | 0.559758 | 0.691994 | 3.518767 | 0.007525 |
| 4 | 0.779913 | 0.564457 | 4.213102 | 0.000827 | 0.764937 | 0.575417 | 3.467471 | 0.004272 |
#日频数据——(SPOP,HSCL)
daily_3_df = pd.DataFrame()
daily_3_df['F_1'] = get_G_results(SP500_df_1['R_OP'], HS300_df_1['R_CL'], 5)['F']
daily_3_df['P_1'] = get_G_results(SP500_df_1['R_OP'], HS300_df_1['R_CL'], 5)['P']
daily_3_df['F_2'] = get_G_results(SP500_df_2['R_OP'], HS300_df_2['R_CL'], 5)['F']
daily_3_df['P_2'] = get_G_results(SP500_df_2['R_OP'], HS300_df_2['R_CL'], 5)['P']
daily_3_df['F_3'] = get_G_results(SP500_df_3['R_OP'], HS300_df_3['R_CL'], 5)['F']
daily_3_df['P_3'] = get_G_results(SP500_df_3['R_OP'], HS300_df_3['R_CL'], 5)['P']
daily_3_df['F_4'] = get_G_results(SP500_df_4['R_OP'], HS300_df_4['R_CL'], 5)['F']
daily_3_df['P_4'] = get_G_results(SP500_df_4['R_OP'], HS300_df_4['R_CL'], 5)['P']
daily_3_df
Granger Causality number of lags (no zero) 1 ssr based F test: F=0.7405 , p=0.3899 , df_denom=530, df_num=1 ssr based chi2 test: chi2=0.7447 , p=0.3881 , df=1 likelihood ratio test: chi2=0.7442 , p=0.3883 , df=1 parameter F test: F=0.7405 , p=0.3899 , df_denom=530, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.4705 , p=0.6250 , df_denom=527, df_num=2 ssr based chi2 test: chi2=0.9498 , p=0.6219 , df=2 likelihood ratio test: chi2=0.9490 , p=0.6222 , df=2 parameter F test: F=0.4705 , p=0.6250 , df_denom=527, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.3496 , p=0.7895 , df_denom=524, df_num=3 ssr based chi2 test: chi2=1.0627 , p=0.7861 , df=3 likelihood ratio test: chi2=1.0617 , p=0.7863 , df=3 parameter F test: F=0.3496 , p=0.7895 , df_denom=524, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.2603 , p=0.9033 , df_denom=521, df_num=4 ssr based chi2 test: chi2=1.0591 , p=0.9007 , df=4 likelihood ratio test: chi2=1.0581 , p=0.9009 , df=4 parameter F test: F=0.2603 , p=0.9033 , df_denom=521, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.2683 , p=0.9304 , df_denom=518, df_num=5 ssr based chi2 test: chi2=1.3700 , p=0.9276 , df=5 likelihood ratio test: chi2=1.3682 , p=0.9278 , df=5 parameter F test: F=0.2683 , p=0.9304 , df_denom=518, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.7405 , p=0.3899 , df_denom=530, df_num=1 ssr based chi2 test: chi2=0.7447 , p=0.3881 , df=1 likelihood ratio test: chi2=0.7442 , p=0.3883 , df=1 parameter F test: F=0.7405 , p=0.3899 , df_denom=530, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.4705 , p=0.6250 , df_denom=527, df_num=2 ssr based chi2 test: chi2=0.9498 , p=0.6219 , df=2 likelihood ratio test: chi2=0.9490 , p=0.6222 , df=2 parameter F test: F=0.4705 , p=0.6250 , df_denom=527, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.3496 , p=0.7895 , df_denom=524, df_num=3 ssr based chi2 test: chi2=1.0627 , p=0.7861 , df=3 likelihood ratio test: chi2=1.0617 , p=0.7863 , df=3 parameter F test: F=0.3496 , p=0.7895 , df_denom=524, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.2603 , p=0.9033 , df_denom=521, df_num=4 ssr based chi2 test: chi2=1.0591 , p=0.9007 , df=4 likelihood ratio test: chi2=1.0581 , p=0.9009 , df=4 parameter F test: F=0.2603 , p=0.9033 , df_denom=521, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.2683 , p=0.9304 , df_denom=518, df_num=5 ssr based chi2 test: chi2=1.3700 , p=0.9276 , df=5 likelihood ratio test: chi2=1.3682 , p=0.9278 , df=5 parameter F test: F=0.2683 , p=0.9304 , df_denom=518, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.2051 , p=0.6507 , df_denom=1667, df_num=1 ssr based chi2 test: chi2=0.2055 , p=0.6503 , df=1 likelihood ratio test: chi2=0.2055 , p=0.6503 , df=1 parameter F test: F=0.2051 , p=0.6507 , df_denom=1667, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.3392 , p=0.7124 , df_denom=1664, df_num=2 ssr based chi2 test: chi2=0.6805 , p=0.7116 , df=2 likelihood ratio test: chi2=0.6804 , p=0.7116 , df=2 parameter F test: F=0.3392 , p=0.7124 , df_denom=1664, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.4179 , p=0.7402 , df_denom=1661, df_num=3 ssr based chi2 test: chi2=1.2591 , p=0.7389 , df=3 likelihood ratio test: chi2=1.2586 , p=0.7390 , df=3 parameter F test: F=0.4179 , p=0.7402 , df_denom=1661, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.4558 , p=0.7682 , df_denom=1658, df_num=4 ssr based chi2 test: chi2=1.8329 , p=0.7665 , df=4 likelihood ratio test: chi2=1.8319 , p=0.7666 , df=4 parameter F test: F=0.4558 , p=0.7682 , df_denom=1658, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.3867 , p=0.8582 , df_denom=1655, df_num=5 ssr based chi2 test: chi2=1.9462 , p=0.8565 , df=5 likelihood ratio test: chi2=1.9450 , p=0.8567 , df=5 parameter F test: F=0.3867 , p=0.8582 , df_denom=1655, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.2051 , p=0.6507 , df_denom=1667, df_num=1 ssr based chi2 test: chi2=0.2055 , p=0.6503 , df=1 likelihood ratio test: chi2=0.2055 , p=0.6503 , df=1 parameter F test: F=0.2051 , p=0.6507 , df_denom=1667, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.3392 , p=0.7124 , df_denom=1664, df_num=2 ssr based chi2 test: chi2=0.6805 , p=0.7116 , df=2 likelihood ratio test: chi2=0.6804 , p=0.7116 , df=2 parameter F test: F=0.3392 , p=0.7124 , df_denom=1664, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.4179 , p=0.7402 , df_denom=1661, df_num=3 ssr based chi2 test: chi2=1.2591 , p=0.7389 , df=3 likelihood ratio test: chi2=1.2586 , p=0.7390 , df=3 parameter F test: F=0.4179 , p=0.7402 , df_denom=1661, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.4558 , p=0.7682 , df_denom=1658, df_num=4 ssr based chi2 test: chi2=1.8329 , p=0.7665 , df=4 likelihood ratio test: chi2=1.8319 , p=0.7666 , df=4 parameter F test: F=0.4558 , p=0.7682 , df_denom=1658, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.3867 , p=0.8582 , df_denom=1655, df_num=5 ssr based chi2 test: chi2=1.9462 , p=0.8565 , df=5 likelihood ratio test: chi2=1.9450 , p=0.8567 , df=5 parameter F test: F=0.3867 , p=0.8582 , df_denom=1655, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=4.7522 , p=0.0297 , df_denom=480, df_num=1 ssr based chi2 test: chi2=4.7819 , p=0.0288 , df=1 likelihood ratio test: chi2=4.7584 , p=0.0292 , df=1 parameter F test: F=4.7522 , p=0.0297 , df_denom=480, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=2.5590 , p=0.0784 , df_denom=477, df_num=2 ssr based chi2 test: chi2=5.1717 , p=0.0753 , df=2 likelihood ratio test: chi2=5.1441 , p=0.0764 , df=2 parameter F test: F=2.5590 , p=0.0784 , df_denom=477, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=1.8675 , p=0.1342 , df_denom=474, df_num=3 ssr based chi2 test: chi2=5.6853 , p=0.1280 , df=3 likelihood ratio test: chi2=5.6519 , p=0.1298 , df=3 parameter F test: F=1.8675 , p=0.1342 , df_denom=474, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=1.7434 , p=0.1393 , df_denom=471, df_num=4 ssr based chi2 test: chi2=7.1067 , p=0.1304 , df=4 likelihood ratio test: chi2=7.0546 , p=0.1330 , df=4 parameter F test: F=1.7434 , p=0.1393 , df_denom=471, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=1.3845 , p=0.2287 , df_denom=468, df_num=5 ssr based chi2 test: chi2=7.0853 , p=0.2144 , df=5 likelihood ratio test: chi2=7.0334 , p=0.2182 , df=5 parameter F test: F=1.3845 , p=0.2287 , df_denom=468, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=4.7522 , p=0.0297 , df_denom=480, df_num=1 ssr based chi2 test: chi2=4.7819 , p=0.0288 , df=1 likelihood ratio test: chi2=4.7584 , p=0.0292 , df=1 parameter F test: F=4.7522 , p=0.0297 , df_denom=480, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=2.5590 , p=0.0784 , df_denom=477, df_num=2 ssr based chi2 test: chi2=5.1717 , p=0.0753 , df=2 likelihood ratio test: chi2=5.1441 , p=0.0764 , df=2 parameter F test: F=2.5590 , p=0.0784 , df_denom=477, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=1.8675 , p=0.1342 , df_denom=474, df_num=3 ssr based chi2 test: chi2=5.6853 , p=0.1280 , df=3 likelihood ratio test: chi2=5.6519 , p=0.1298 , df=3 parameter F test: F=1.8675 , p=0.1342 , df_denom=474, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=1.7434 , p=0.1393 , df_denom=471, df_num=4 ssr based chi2 test: chi2=7.1067 , p=0.1304 , df=4 likelihood ratio test: chi2=7.0546 , p=0.1330 , df=4 parameter F test: F=1.7434 , p=0.1393 , df_denom=471, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=1.3845 , p=0.2287 , df_denom=468, df_num=5 ssr based chi2 test: chi2=7.0853 , p=0.2144 , df=5 likelihood ratio test: chi2=7.0334 , p=0.2182 , df=5 parameter F test: F=1.3845 , p=0.2287 , df_denom=468, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=6.2466 , p=0.0127 , df_denom=581, df_num=1 ssr based chi2 test: chi2=6.2789 , p=0.0122 , df=1 likelihood ratio test: chi2=6.2453 , p=0.0125 , df=1 parameter F test: F=6.2466 , p=0.0127 , df_denom=581, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=4.5417 , p=0.0110 , df_denom=578, df_num=2 ssr based chi2 test: chi2=9.1619 , p=0.0102 , df=2 likelihood ratio test: chi2=9.0907 , p=0.0106 , df=2 parameter F test: F=4.5417 , p=0.0110 , df_denom=578, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=3.0573 , p=0.0279 , df_denom=575, df_num=3 ssr based chi2 test: chi2=9.2836 , p=0.0257 , df=3 likelihood ratio test: chi2=9.2104 , p=0.0266 , df=3 parameter F test: F=3.0573 , p=0.0279 , df_denom=575, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=2.2253 , p=0.0650 , df_denom=572, df_num=4 ssr based chi2 test: chi2=9.0414 , p=0.0601 , df=4 likelihood ratio test: chi2=8.9717 , p=0.0618 , df=4 parameter F test: F=2.2253 , p=0.0650 , df_denom=572, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=1.9478 , p=0.0848 , df_denom=569, df_num=5 ssr based chi2 test: chi2=9.9273 , p=0.0773 , df=5 likelihood ratio test: chi2=9.8433 , p=0.0798 , df=5 parameter F test: F=1.9478 , p=0.0848 , df_denom=569, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=6.2466 , p=0.0127 , df_denom=581, df_num=1 ssr based chi2 test: chi2=6.2789 , p=0.0122 , df=1 likelihood ratio test: chi2=6.2453 , p=0.0125 , df=1 parameter F test: F=6.2466 , p=0.0127 , df_denom=581, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=4.5417 , p=0.0110 , df_denom=578, df_num=2 ssr based chi2 test: chi2=9.1619 , p=0.0102 , df=2 likelihood ratio test: chi2=9.0907 , p=0.0106 , df=2 parameter F test: F=4.5417 , p=0.0110 , df_denom=578, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=3.0573 , p=0.0279 , df_denom=575, df_num=3 ssr based chi2 test: chi2=9.2836 , p=0.0257 , df=3 likelihood ratio test: chi2=9.2104 , p=0.0266 , df=3 parameter F test: F=3.0573 , p=0.0279 , df_denom=575, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=2.2253 , p=0.0650 , df_denom=572, df_num=4 ssr based chi2 test: chi2=9.0414 , p=0.0601 , df=4 likelihood ratio test: chi2=8.9717 , p=0.0618 , df=4 parameter F test: F=2.2253 , p=0.0650 , df_denom=572, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=1.9478 , p=0.0848 , df_denom=569, df_num=5 ssr based chi2 test: chi2=9.9273 , p=0.0773 , df=5 likelihood ratio test: chi2=9.8433 , p=0.0798 , df=5 parameter F test: F=1.9478 , p=0.0848 , df_denom=569, df_num=5
| F_1 | P_1 | F_2 | P_2 | F_3 | P_3 | F_4 | P_4 | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.740539 | 0.389877 | 0.205117 | 0.650681 | 4.752224 | 0.029746 | 6.246600 | 0.012718 |
| 1 | 0.470454 | 0.624980 | 0.339250 | 0.712354 | 2.559012 | 0.078443 | 4.541672 | 0.011039 |
| 2 | 0.349571 | 0.789479 | 0.417933 | 0.740155 | 1.867515 | 0.134189 | 3.057327 | 0.027895 |
| 3 | 0.260291 | 0.903344 | 0.455760 | 0.768247 | 1.743361 | 0.139256 | 2.225324 | 0.065009 |
| 4 | 0.268299 | 0.930378 | 0.386660 | 0.858211 | 1.384521 | 0.228653 | 1.947802 | 0.084764 |
#日频数据——(SPCL,HSCL)
daily_4_df = pd.DataFrame()
daily_4_df['F_1'] = get_G_results(SP500_df_1['R_CL'], HS300_df_1['R_CL'], 5)['F']
daily_4_df['P_1'] = get_G_results(SP500_df_1['R_CL'], HS300_df_1['R_CL'], 5)['P']
daily_4_df['F_2'] = get_G_results(SP500_df_2['R_CL'], HS300_df_2['R_CL'], 5)['F']
daily_4_df['P_2'] = get_G_results(SP500_df_2['R_CL'], HS300_df_2['R_CL'], 5)['P']
daily_4_df['F_3'] = get_G_results(SP500_df_3['R_CL'], HS300_df_3['R_CL'], 5)['F']
daily_4_df['P_3'] = get_G_results(SP500_df_3['R_CL'], HS300_df_3['R_CL'], 5)['P']
daily_4_df['F_4'] = get_G_results(SP500_df_4['R_CL'], HS300_df_4['R_CL'], 5)['F']
daily_4_df['P_4'] = get_G_results(SP500_df_4['R_CL'], HS300_df_4['R_CL'], 5)['P']
daily_4_df
Granger Causality number of lags (no zero) 1 ssr based F test: F=0.2511 , p=0.6165 , df_denom=530, df_num=1 ssr based chi2 test: chi2=0.2526 , p=0.6153 , df=1 likelihood ratio test: chi2=0.2525 , p=0.6153 , df=1 parameter F test: F=0.2511 , p=0.6165 , df_denom=530, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.6375 , p=0.5290 , df_denom=527, df_num=2 ssr based chi2 test: chi2=1.2871 , p=0.5254 , df=2 likelihood ratio test: chi2=1.2855 , p=0.5258 , df=2 parameter F test: F=0.6375 , p=0.5290 , df_denom=527, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.4052 , p=0.7493 , df_denom=524, df_num=3 ssr based chi2 test: chi2=1.2319 , p=0.7454 , df=3 likelihood ratio test: chi2=1.2305 , p=0.7457 , df=3 parameter F test: F=0.4052 , p=0.7493 , df_denom=524, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.3147 , p=0.8682 , df_denom=521, df_num=4 ssr based chi2 test: chi2=1.2806 , p=0.8647 , df=4 likelihood ratio test: chi2=1.2790 , p=0.8649 , df=4 parameter F test: F=0.3147 , p=0.8682 , df_denom=521, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=3.3688 , p=0.0053 , df_denom=518, df_num=5 ssr based chi2 test: chi2=17.2019 , p=0.0041 , df=5 likelihood ratio test: chi2=16.9281 , p=0.0046 , df=5 parameter F test: F=3.3688 , p=0.0053 , df_denom=518, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.2511 , p=0.6165 , df_denom=530, df_num=1 ssr based chi2 test: chi2=0.2526 , p=0.6153 , df=1 likelihood ratio test: chi2=0.2525 , p=0.6153 , df=1 parameter F test: F=0.2511 , p=0.6165 , df_denom=530, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.6375 , p=0.5290 , df_denom=527, df_num=2 ssr based chi2 test: chi2=1.2871 , p=0.5254 , df=2 likelihood ratio test: chi2=1.2855 , p=0.5258 , df=2 parameter F test: F=0.6375 , p=0.5290 , df_denom=527, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.4052 , p=0.7493 , df_denom=524, df_num=3 ssr based chi2 test: chi2=1.2319 , p=0.7454 , df=3 likelihood ratio test: chi2=1.2305 , p=0.7457 , df=3 parameter F test: F=0.4052 , p=0.7493 , df_denom=524, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.3147 , p=0.8682 , df_denom=521, df_num=4 ssr based chi2 test: chi2=1.2806 , p=0.8647 , df=4 likelihood ratio test: chi2=1.2790 , p=0.8649 , df=4 parameter F test: F=0.3147 , p=0.8682 , df_denom=521, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=3.3688 , p=0.0053 , df_denom=518, df_num=5 ssr based chi2 test: chi2=17.2019 , p=0.0041 , df=5 likelihood ratio test: chi2=16.9281 , p=0.0046 , df=5 parameter F test: F=3.3688 , p=0.0053 , df_denom=518, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.0392 , p=0.8430 , df_denom=1667, df_num=1 ssr based chi2 test: chi2=0.0393 , p=0.8428 , df=1 likelihood ratio test: chi2=0.0393 , p=0.8428 , df=1 parameter F test: F=0.0392 , p=0.8430 , df_denom=1667, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.1393 , p=0.8700 , df_denom=1664, df_num=2 ssr based chi2 test: chi2=0.2793 , p=0.8696 , df=2 likelihood ratio test: chi2=0.2793 , p=0.8697 , df=2 parameter F test: F=0.1393 , p=0.8700 , df_denom=1664, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.1800 , p=0.9100 , df_denom=1661, df_num=3 ssr based chi2 test: chi2=0.5422 , p=0.9095 , df=3 likelihood ratio test: chi2=0.5421 , p=0.9096 , df=3 parameter F test: F=0.1800 , p=0.9100 , df_denom=1661, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.1709 , p=0.9533 , df_denom=1658, df_num=4 ssr based chi2 test: chi2=0.6875 , p=0.9529 , df=4 likelihood ratio test: chi2=0.6873 , p=0.9529 , df=4 parameter F test: F=0.1709 , p=0.9533 , df_denom=1658, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=1.9324 , p=0.0860 , df_denom=1655, df_num=5 ssr based chi2 test: chi2=9.7261 , p=0.0834 , df=5 likelihood ratio test: chi2=9.6978 , p=0.0843 , df=5 parameter F test: F=1.9324 , p=0.0860 , df_denom=1655, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.0392 , p=0.8430 , df_denom=1667, df_num=1 ssr based chi2 test: chi2=0.0393 , p=0.8428 , df=1 likelihood ratio test: chi2=0.0393 , p=0.8428 , df=1 parameter F test: F=0.0392 , p=0.8430 , df_denom=1667, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.1393 , p=0.8700 , df_denom=1664, df_num=2 ssr based chi2 test: chi2=0.2793 , p=0.8696 , df=2 likelihood ratio test: chi2=0.2793 , p=0.8697 , df=2 parameter F test: F=0.1393 , p=0.8700 , df_denom=1664, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.1800 , p=0.9100 , df_denom=1661, df_num=3 ssr based chi2 test: chi2=0.5422 , p=0.9095 , df=3 likelihood ratio test: chi2=0.5421 , p=0.9096 , df=3 parameter F test: F=0.1800 , p=0.9100 , df_denom=1661, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.1709 , p=0.9533 , df_denom=1658, df_num=4 ssr based chi2 test: chi2=0.6875 , p=0.9529 , df=4 likelihood ratio test: chi2=0.6873 , p=0.9529 , df=4 parameter F test: F=0.1709 , p=0.9533 , df_denom=1658, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=1.9324 , p=0.0860 , df_denom=1655, df_num=5 ssr based chi2 test: chi2=9.7261 , p=0.0834 , df=5 likelihood ratio test: chi2=9.6978 , p=0.0843 , df=5 parameter F test: F=1.9324 , p=0.0860 , df_denom=1655, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.7923 , p=0.3739 , df_denom=480, df_num=1 ssr based chi2 test: chi2=0.7972 , p=0.3719 , df=1 likelihood ratio test: chi2=0.7966 , p=0.3721 , df=1 parameter F test: F=0.7923 , p=0.3739 , df_denom=480, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.4907 , p=0.6125 , df_denom=477, df_num=2 ssr based chi2 test: chi2=0.9917 , p=0.6091 , df=2 likelihood ratio test: chi2=0.9906 , p=0.6094 , df=2 parameter F test: F=0.4907 , p=0.6125 , df_denom=477, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.3654 , p=0.7780 , df_denom=474, df_num=3 ssr based chi2 test: chi2=1.1125 , p=0.7741 , df=3 likelihood ratio test: chi2=1.1112 , p=0.7744 , df=3 parameter F test: F=0.3654 , p=0.7780 , df_denom=474, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=1.1348 , p=0.3394 , df_denom=471, df_num=4 ssr based chi2 test: chi2=4.6258 , p=0.3279 , df=4 likelihood ratio test: chi2=4.6036 , p=0.3304 , df=4 parameter F test: F=1.1348 , p=0.3394 , df_denom=471, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.9570 , p=0.4438 , df_denom=468, df_num=5 ssr based chi2 test: chi2=4.8975 , p=0.4285 , df=5 likelihood ratio test: chi2=4.8727 , p=0.4316 , df=5 parameter F test: F=0.9570 , p=0.4438 , df_denom=468, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.7923 , p=0.3739 , df_denom=480, df_num=1 ssr based chi2 test: chi2=0.7972 , p=0.3719 , df=1 likelihood ratio test: chi2=0.7966 , p=0.3721 , df=1 parameter F test: F=0.7923 , p=0.3739 , df_denom=480, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.4907 , p=0.6125 , df_denom=477, df_num=2 ssr based chi2 test: chi2=0.9917 , p=0.6091 , df=2 likelihood ratio test: chi2=0.9906 , p=0.6094 , df=2 parameter F test: F=0.4907 , p=0.6125 , df_denom=477, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.3654 , p=0.7780 , df_denom=474, df_num=3 ssr based chi2 test: chi2=1.1125 , p=0.7741 , df=3 likelihood ratio test: chi2=1.1112 , p=0.7744 , df=3 parameter F test: F=0.3654 , p=0.7780 , df_denom=474, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=1.1348 , p=0.3394 , df_denom=471, df_num=4 ssr based chi2 test: chi2=4.6258 , p=0.3279 , df=4 likelihood ratio test: chi2=4.6036 , p=0.3304 , df=4 parameter F test: F=1.1348 , p=0.3394 , df_denom=471, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.9570 , p=0.4438 , df_denom=468, df_num=5 ssr based chi2 test: chi2=4.8975 , p=0.4285 , df=5 likelihood ratio test: chi2=4.8727 , p=0.4316 , df=5 parameter F test: F=0.9570 , p=0.4438 , df_denom=468, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=4.7347 , p=0.0300 , df_denom=581, df_num=1 ssr based chi2 test: chi2=4.7592 , p=0.0291 , df=1 likelihood ratio test: chi2=4.7399 , p=0.0295 , df=1 parameter F test: F=4.7347 , p=0.0300 , df_denom=581, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=3.1316 , p=0.0444 , df_denom=578, df_num=2 ssr based chi2 test: chi2=6.3174 , p=0.0425 , df=2 likelihood ratio test: chi2=6.2834 , p=0.0432 , df=2 parameter F test: F=3.1316 , p=0.0444 , df_denom=578, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=2.3007 , p=0.0763 , df_denom=575, df_num=3 ssr based chi2 test: chi2=6.9862 , p=0.0723 , df=3 likelihood ratio test: chi2=6.9446 , p=0.0737 , df=3 parameter F test: F=2.3007 , p=0.0763 , df_denom=575, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=2.0588 , p=0.0848 , df_denom=572, df_num=4 ssr based chi2 test: chi2=8.3646 , p=0.0791 , df=4 likelihood ratio test: chi2=8.3049 , p=0.0810 , df=4 parameter F test: F=2.0588 , p=0.0848 , df_denom=572, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=1.4814 , p=0.1940 , df_denom=569, df_num=5 ssr based chi2 test: chi2=7.5504 , p=0.1828 , df=5 likelihood ratio test: chi2=7.5016 , p=0.1859 , df=5 parameter F test: F=1.4814 , p=0.1940 , df_denom=569, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=4.7347 , p=0.0300 , df_denom=581, df_num=1 ssr based chi2 test: chi2=4.7592 , p=0.0291 , df=1 likelihood ratio test: chi2=4.7399 , p=0.0295 , df=1 parameter F test: F=4.7347 , p=0.0300 , df_denom=581, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=3.1316 , p=0.0444 , df_denom=578, df_num=2 ssr based chi2 test: chi2=6.3174 , p=0.0425 , df=2 likelihood ratio test: chi2=6.2834 , p=0.0432 , df=2 parameter F test: F=3.1316 , p=0.0444 , df_denom=578, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=2.3007 , p=0.0763 , df_denom=575, df_num=3 ssr based chi2 test: chi2=6.9862 , p=0.0723 , df=3 likelihood ratio test: chi2=6.9446 , p=0.0737 , df=3 parameter F test: F=2.3007 , p=0.0763 , df_denom=575, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=2.0588 , p=0.0848 , df_denom=572, df_num=4 ssr based chi2 test: chi2=8.3646 , p=0.0791 , df=4 likelihood ratio test: chi2=8.3049 , p=0.0810 , df=4 parameter F test: F=2.0588 , p=0.0848 , df_denom=572, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=1.4814 , p=0.1940 , df_denom=569, df_num=5 ssr based chi2 test: chi2=7.5504 , p=0.1828 , df=5 likelihood ratio test: chi2=7.5016 , p=0.1859 , df=5 parameter F test: F=1.4814 , p=0.1940 , df_denom=569, df_num=5
| F_1 | P_1 | F_2 | P_2 | F_3 | P_3 | F_4 | P_4 | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.251147 | 0.616477 | 0.039239 | 0.842999 | 0.792295 | 0.373853 | 4.734708 | 0.029962 |
| 1 | 0.637485 | 0.529027 | 0.139252 | 0.870019 | 0.490684 | 0.612516 | 3.131624 | 0.044388 |
| 2 | 0.405234 | 0.749301 | 0.179967 | 0.910025 | 0.365435 | 0.777993 | 2.300713 | 0.076260 |
| 3 | 0.314701 | 0.868175 | 0.170944 | 0.953282 | 1.134754 | 0.339375 | 2.058752 | 0.084842 |
| 4 | 3.368842 | 0.005271 | 1.932377 | 0.086022 | 0.957013 | 0.443825 | 1.481431 | 0.193963 |
由统计结果可以看出，无论是对开盘收益还是收盘收益影响，标普500对沪深300影响都十分显著，并且在第二阶段开始，标普500收盘对沪深300开收盘在多个滞后期都是同级显著的。美股日内的异动对A股次日开盘以及随后的5个交易日都有较强的影响效果，但随着时间的增加因果关系逐渐减弱，两国股市是短期影响关系。可以认为，随着中国资本市场与全球资本市场联系逐渐紧密，中美两国股市的联动性也在不断增强。
观察周频与月频的数据可以发现，两种指数在周频与月频上的因果关系明显弱于日频数据，且时间周期越长因果关系越弱，这一观察与我们在上一节中得到的结论一致，说明随着时间推移，中美股市联动效应逐渐失效，也印证了中美， A股市场长期走势相对独立，不存在长期均衡的特征。
#筛选周频交易日
def get_weekly_trade_days(days_list):
weekly_trade_days = []
for item in days_list:
if (item - datetime.timedelta(1)) not in days_list:
weekly_trade_days.append(item)
return weekly_trade_days
#获取周频重合交易日
w_total_common_days = get_weekly_trade_days(total_common_days)
w_common_days_1 = get_weekly_trade_days(common_days_1)
w_common_days_2 = get_weekly_trade_days(common_days_2)
w_common_days_3 = get_weekly_trade_days(common_days_3)
w_common_days_4 = get_weekly_trade_days(common_days_4)
#整理周频量价数据
w_SP500_df = SP500_df.loc[w_total_common_days]
w_HS300_df = HS300_df.loc[w_total_common_days]
w_SP500_df_1 = SP500_df.loc[w_common_days_1]
w_HS300_df_1 = HS300_df.loc[w_common_days_1]
w_SP500_df_2 = SP500_df.loc[w_common_days_2]
w_HS300_df_2 = HS300_df.loc[w_common_days_2]
w_SP500_df_3 = SP500_df.loc[w_common_days_3]
w_HS300_df_3 = HS300_df.loc[w_common_days_3]
w_SP500_df_4 = SP500_df.loc[w_common_days_4]
w_HS300_df_4 = HS300_df.loc[w_common_days_4]
#周频数据——(HSOP,SPCL)
weekly_1_df = pd.DataFrame()
weekly_1_df['F_1'] = get_G_results(w_HS300_df_1['R_OP'], w_SP500_df_1['R_CL'], 5)['F']
weekly_1_df['P_1'] = get_G_results(w_HS300_df_1['R_OP'], w_SP500_df_1['R_CL'], 5)['P']
weekly_1_df['F_2'] = get_G_results(w_HS300_df_2['R_OP'], w_SP500_df_2['R_CL'], 5)['F']
weekly_1_df['P_2'] = get_G_results(w_HS300_df_2['R_OP'], w_SP500_df_2['R_CL'], 5)['P']
weekly_1_df['F_3'] = get_G_results(w_HS300_df_3['R_OP'], w_SP500_df_3['R_CL'], 5)['F']
weekly_1_df['P_3'] = get_G_results(w_HS300_df_3['R_OP'], w_SP500_df_3['R_CL'], 5)['P']
weekly_1_df['F_4'] = get_G_results(w_HS300_df_4['R_OP'], w_SP500_df_4['R_CL'], 5)['F']
weekly_1_df['P_4'] = get_G_results(w_HS300_df_4['R_OP'], w_SP500_df_4['R_CL'], 5)['P']
weekly_1_df
Granger Causality number of lags (no zero) 1 ssr based F test: F=0.5406 , p=0.4637 , df_denom=114, df_num=1 ssr based chi2 test: chi2=0.5548 , p=0.4564 , df=1 likelihood ratio test: chi2=0.5535 , p=0.4569 , df=1 parameter F test: F=0.5406 , p=0.4637 , df_denom=114, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=2.1280 , p=0.1239 , df_denom=111, df_num=2 ssr based chi2 test: chi2=4.4477 , p=0.1082 , df=2 likelihood ratio test: chi2=4.3646 , p=0.1128 , df=2 parameter F test: F=2.1280 , p=0.1239 , df_denom=111, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=2.8423 , p=0.0412 , df_denom=108, df_num=3 ssr based chi2 test: chi2=9.0796 , p=0.0283 , df=3 likelihood ratio test: chi2=8.7390 , p=0.0330 , df=3 parameter F test: F=2.8423 , p=0.0412 , df_denom=108, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=2.5124 , p=0.0460 , df_denom=105, df_num=4 ssr based chi2 test: chi2=10.9111 , p=0.0276 , df=4 likelihood ratio test: chi2=10.4200 , p=0.0339 , df=4 parameter F test: F=2.5124 , p=0.0460 , df_denom=105, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=2.4146 , p=0.0411 , df_denom=102, df_num=5 ssr based chi2 test: chi2=13.3750 , p=0.0201 , df=5 likelihood ratio test: chi2=12.6408 , p=0.0270 , df=5 parameter F test: F=2.4146 , p=0.0411 , df_denom=102, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.5406 , p=0.4637 , df_denom=114, df_num=1 ssr based chi2 test: chi2=0.5548 , p=0.4564 , df=1 likelihood ratio test: chi2=0.5535 , p=0.4569 , df=1 parameter F test: F=0.5406 , p=0.4637 , df_denom=114, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=2.1280 , p=0.1239 , df_denom=111, df_num=2 ssr based chi2 test: chi2=4.4477 , p=0.1082 , df=2 likelihood ratio test: chi2=4.3646 , p=0.1128 , df=2 parameter F test: F=2.1280 , p=0.1239 , df_denom=111, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=2.8423 , p=0.0412 , df_denom=108, df_num=3 ssr based chi2 test: chi2=9.0796 , p=0.0283 , df=3 likelihood ratio test: chi2=8.7390 , p=0.0330 , df=3 parameter F test: F=2.8423 , p=0.0412 , df_denom=108, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=2.5124 , p=0.0460 , df_denom=105, df_num=4 ssr based chi2 test: chi2=10.9111 , p=0.0276 , df=4 likelihood ratio test: chi2=10.4200 , p=0.0339 , df=4 parameter F test: F=2.5124 , p=0.0460 , df_denom=105, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=2.4146 , p=0.0411 , df_denom=102, df_num=5 ssr based chi2 test: chi2=13.3750 , p=0.0201 , df=5 likelihood ratio test: chi2=12.6408 , p=0.0270 , df=5 parameter F test: F=2.4146 , p=0.0411 , df_denom=102, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=1.4487 , p=0.2295 , df_denom=375, df_num=1 ssr based chi2 test: chi2=1.4603 , p=0.2269 , df=1 likelihood ratio test: chi2=1.4575 , p=0.2273 , df=1 parameter F test: F=1.4487 , p=0.2295 , df_denom=375, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=2.4629 , p=0.0866 , df_denom=372, df_num=2 ssr based chi2 test: chi2=4.9920 , p=0.0824 , df=2 likelihood ratio test: chi2=4.9593 , p=0.0838 , df=2 parameter F test: F=2.4629 , p=0.0866 , df_denom=372, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=1.8887 , p=0.1310 , df_denom=369, df_num=3 ssr based chi2 test: chi2=5.7736 , p=0.1232 , df=3 likelihood ratio test: chi2=5.7297 , p=0.1255 , df=3 parameter F test: F=1.8887 , p=0.1310 , df_denom=369, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=2.2013 , p=0.0684 , df_denom=366, df_num=4 ssr based chi2 test: chi2=9.0215 , p=0.0606 , df=4 likelihood ratio test: chi2=8.9147 , p=0.0633 , df=4 parameter F test: F=2.2013 , p=0.0684 , df_denom=366, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=1.7317 , p=0.1265 , df_denom=363, df_num=5 ssr based chi2 test: chi2=8.9210 , p=0.1123 , df=5 likelihood ratio test: chi2=8.8162 , p=0.1166 , df=5 parameter F test: F=1.7317 , p=0.1265 , df_denom=363, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=1.4487 , p=0.2295 , df_denom=375, df_num=1 ssr based chi2 test: chi2=1.4603 , p=0.2269 , df=1 likelihood ratio test: chi2=1.4575 , p=0.2273 , df=1 parameter F test: F=1.4487 , p=0.2295 , df_denom=375, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=2.4629 , p=0.0866 , df_denom=372, df_num=2 ssr based chi2 test: chi2=4.9920 , p=0.0824 , df=2 likelihood ratio test: chi2=4.9593 , p=0.0838 , df=2 parameter F test: F=2.4629 , p=0.0866 , df_denom=372, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=1.8887 , p=0.1310 , df_denom=369, df_num=3 ssr based chi2 test: chi2=5.7736 , p=0.1232 , df=3 likelihood ratio test: chi2=5.7297 , p=0.1255 , df=3 parameter F test: F=1.8887 , p=0.1310 , df_denom=369, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=2.2013 , p=0.0684 , df_denom=366, df_num=4 ssr based chi2 test: chi2=9.0215 , p=0.0606 , df=4 likelihood ratio test: chi2=8.9147 , p=0.0633 , df=4 parameter F test: F=2.2013 , p=0.0684 , df_denom=366, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=1.7317 , p=0.1265 , df_denom=363, df_num=5 ssr based chi2 test: chi2=8.9210 , p=0.1123 , df=5 likelihood ratio test: chi2=8.8162 , p=0.1166 , df=5 parameter F test: F=1.7317 , p=0.1265 , df_denom=363, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.6747 , p=0.4133 , df_denom=105, df_num=1 ssr based chi2 test: chi2=0.6940 , p=0.4048 , df=1 likelihood ratio test: chi2=0.6917 , p=0.4056 , df=1 parameter F test: F=0.6747 , p=0.4133 , df_denom=105, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=1.3465 , p=0.2647 , df_denom=102, df_num=2 ssr based chi2 test: chi2=2.8251 , p=0.2435 , df=2 likelihood ratio test: chi2=2.7884 , p=0.2480 , df=2 parameter F test: F=1.3465 , p=0.2647 , df_denom=102, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=1.0150 , p=0.3895 , df_denom=99, df_num=3 ssr based chi2 test: chi2=3.2601 , p=0.3532 , df=3 likelihood ratio test: chi2=3.2110 , p=0.3602 , df=3 parameter F test: F=1.0150 , p=0.3895 , df_denom=99, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.5506 , p=0.6990 , df_denom=96, df_num=4 ssr based chi2 test: chi2=2.4088 , p=0.6610 , df=4 likelihood ratio test: chi2=2.3816 , p=0.6660 , df=4 parameter F test: F=0.5506 , p=0.6990 , df_denom=96, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.3571 , p=0.8765 , df_denom=93, df_num=5 ssr based chi2 test: chi2=1.9966 , p=0.8496 , df=5 likelihood ratio test: chi2=1.9777 , p=0.8522 , df=5 parameter F test: F=0.3571 , p=0.8765 , df_denom=93, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.6747 , p=0.4133 , df_denom=105, df_num=1 ssr based chi2 test: chi2=0.6940 , p=0.4048 , df=1 likelihood ratio test: chi2=0.6917 , p=0.4056 , df=1 parameter F test: F=0.6747 , p=0.4133 , df_denom=105, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=1.3465 , p=0.2647 , df_denom=102, df_num=2 ssr based chi2 test: chi2=2.8251 , p=0.2435 , df=2 likelihood ratio test: chi2=2.7884 , p=0.2480 , df=2 parameter F test: F=1.3465 , p=0.2647 , df_denom=102, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=1.0150 , p=0.3895 , df_denom=99, df_num=3 ssr based chi2 test: chi2=3.2601 , p=0.3532 , df=3 likelihood ratio test: chi2=3.2110 , p=0.3602 , df=3 parameter F test: F=1.0150 , p=0.3895 , df_denom=99, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.5506 , p=0.6990 , df_denom=96, df_num=4 ssr based chi2 test: chi2=2.4088 , p=0.6610 , df=4 likelihood ratio test: chi2=2.3816 , p=0.6660 , df=4 parameter F test: F=0.5506 , p=0.6990 , df_denom=96, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.3571 , p=0.8765 , df_denom=93, df_num=5 ssr based chi2 test: chi2=1.9966 , p=0.8496 , df=5 likelihood ratio test: chi2=1.9777 , p=0.8522 , df=5 parameter F test: F=0.3571 , p=0.8765 , df_denom=93, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=1.7850 , p=0.1839 , df_denom=129, df_num=1 ssr based chi2 test: chi2=1.8265 , p=0.1765 , df=1 likelihood ratio test: chi2=1.8140 , p=0.1780 , df=1 parameter F test: F=1.7850 , p=0.1839 , df_denom=129, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=1.1986 , p=0.3050 , df_denom=126, df_num=2 ssr based chi2 test: chi2=2.4923 , p=0.2876 , df=2 likelihood ratio test: chi2=2.4689 , p=0.2910 , df=2 parameter F test: F=1.1986 , p=0.3050 , df_denom=126, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=1.1206 , p=0.3435 , df_denom=123, df_num=3 ssr based chi2 test: chi2=3.5533 , p=0.3139 , df=3 likelihood ratio test: chi2=3.5056 , p=0.3200 , df=3 parameter F test: F=1.1206 , p=0.3435 , df_denom=123, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.7775 , p=0.5419 , df_denom=120, df_num=4 ssr based chi2 test: chi2=3.3431 , p=0.5021 , df=4 likelihood ratio test: chi2=3.3006 , p=0.5088 , df=4 parameter F test: F=0.7775 , p=0.5419 , df_denom=120, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.5208 , p=0.7601 , df_denom=117, df_num=5 ssr based chi2 test: chi2=2.8488 , p=0.7233 , df=5 likelihood ratio test: chi2=2.8176 , p=0.7281 , df=5 parameter F test: F=0.5208 , p=0.7601 , df_denom=117, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=1.7850 , p=0.1839 , df_denom=129, df_num=1 ssr based chi2 test: chi2=1.8265 , p=0.1765 , df=1 likelihood ratio test: chi2=1.8140 , p=0.1780 , df=1 parameter F test: F=1.7850 , p=0.1839 , df_denom=129, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=1.1986 , p=0.3050 , df_denom=126, df_num=2 ssr based chi2 test: chi2=2.4923 , p=0.2876 , df=2 likelihood ratio test: chi2=2.4689 , p=0.2910 , df=2 parameter F test: F=1.1986 , p=0.3050 , df_denom=126, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=1.1206 , p=0.3435 , df_denom=123, df_num=3 ssr based chi2 test: chi2=3.5533 , p=0.3139 , df=3 likelihood ratio test: chi2=3.5056 , p=0.3200 , df=3 parameter F test: F=1.1206 , p=0.3435 , df_denom=123, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.7775 , p=0.5419 , df_denom=120, df_num=4 ssr based chi2 test: chi2=3.3431 , p=0.5021 , df=4 likelihood ratio test: chi2=3.3006 , p=0.5088 , df=4 parameter F test: F=0.7775 , p=0.5419 , df_denom=120, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.5208 , p=0.7601 , df_denom=117, df_num=5 ssr based chi2 test: chi2=2.8488 , p=0.7233 , df=5 likelihood ratio test: chi2=2.8176 , p=0.7281 , df=5 parameter F test: F=0.5208 , p=0.7601 , df_denom=117, df_num=5
| F_1 | P_1 | F_2 | P_2 | F_3 | P_3 | F_4 | P_4 | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.540577 | 0.463704 | 1.448725 | 0.229492 | 0.674676 | 0.413287 | 1.785004 | 0.183888 |
| 1 | 2.128012 | 0.123906 | 2.462921 | 0.086574 | 1.346520 | 0.264728 | 1.198610 | 0.305028 |
| 2 | 2.842318 | 0.041217 | 1.888690 | 0.131032 | 1.014951 | 0.389470 | 1.120646 | 0.343459 |
| 3 | 2.512420 | 0.046031 | 2.201258 | 0.068367 | 0.550581 | 0.699036 | 0.777475 | 0.541938 |
| 4 | 2.414603 | 0.041089 | 1.731716 | 0.126480 | 0.357082 | 0.876487 | 0.520803 | 0.760111 |
#周频数据——(HSCL,SPCL)
weekly_2_df = pd.DataFrame()
weekly_2_df['F_1'] = get_G_results(w_HS300_df_1['R_CL'], w_SP500_df_1['R_CL'], 5)['F']
weekly_2_df['P_1'] = get_G_results(w_HS300_df_1['R_CL'], w_SP500_df_1['R_CL'], 5)['P']
weekly_2_df['F_2'] = get_G_results(w_HS300_df_2['R_CL'], w_SP500_df_2['R_CL'], 5)['F']
weekly_2_df['P_2'] = get_G_results(w_HS300_df_2['R_CL'], w_SP500_df_2['R_CL'], 5)['P']
weekly_2_df['F_3'] = get_G_results(w_HS300_df_3['R_CL'], w_SP500_df_3['R_CL'], 5)['F']
weekly_2_df['P_3'] = get_G_results(w_HS300_df_3['R_CL'], w_SP500_df_3['R_CL'], 5)['P']
weekly_2_df['F_4'] = get_G_results(w_HS300_df_4['R_CL'], w_SP500_df_4['R_CL'], 5)['F']
weekly_2_df['P_4'] = get_G_results(w_HS300_df_4['R_CL'], w_SP500_df_4['R_CL'], 5)['P']
weekly_2_df
Granger Causality number of lags (no zero) 1 ssr based F test: F=1.4296 , p=0.2343 , df_denom=114, df_num=1 ssr based chi2 test: chi2=1.4672 , p=0.2258 , df=1 likelihood ratio test: chi2=1.4581 , p=0.2272 , df=1 parameter F test: F=1.4296 , p=0.2343 , df_denom=114, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.9474 , p=0.3908 , df_denom=111, df_num=2 ssr based chi2 test: chi2=1.9802 , p=0.3715 , df=2 likelihood ratio test: chi2=1.9635 , p=0.3747 , df=2 parameter F test: F=0.9474 , p=0.3908 , df_denom=111, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=2.0555 , p=0.1104 , df_denom=108, df_num=3 ssr based chi2 test: chi2=6.5662 , p=0.0871 , df=3 likelihood ratio test: chi2=6.3856 , p=0.0943 , df=3 parameter F test: F=2.0555 , p=0.1104 , df_denom=108, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=1.4508 , p=0.2226 , df_denom=105, df_num=4 ssr based chi2 test: chi2=6.3006 , p=0.1778 , df=4 likelihood ratio test: chi2=6.1326 , p=0.1895 , df=4 parameter F test: F=1.4508 , p=0.2226 , df_denom=105, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=2.0129 , p=0.0830 , df_denom=102, df_num=5 ssr based chi2 test: chi2=11.1496 , p=0.0485 , df=5 likelihood ratio test: chi2=10.6333 , p=0.0592 , df=5 parameter F test: F=2.0129 , p=0.0830 , df_denom=102, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=1.4296 , p=0.2343 , df_denom=114, df_num=1 ssr based chi2 test: chi2=1.4672 , p=0.2258 , df=1 likelihood ratio test: chi2=1.4581 , p=0.2272 , df=1 parameter F test: F=1.4296 , p=0.2343 , df_denom=114, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.9474 , p=0.3908 , df_denom=111, df_num=2 ssr based chi2 test: chi2=1.9802 , p=0.3715 , df=2 likelihood ratio test: chi2=1.9635 , p=0.3747 , df=2 parameter F test: F=0.9474 , p=0.3908 , df_denom=111, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=2.0555 , p=0.1104 , df_denom=108, df_num=3 ssr based chi2 test: chi2=6.5662 , p=0.0871 , df=3 likelihood ratio test: chi2=6.3856 , p=0.0943 , df=3 parameter F test: F=2.0555 , p=0.1104 , df_denom=108, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=1.4508 , p=0.2226 , df_denom=105, df_num=4 ssr based chi2 test: chi2=6.3006 , p=0.1778 , df=4 likelihood ratio test: chi2=6.1326 , p=0.1895 , df=4 parameter F test: F=1.4508 , p=0.2226 , df_denom=105, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=2.0129 , p=0.0830 , df_denom=102, df_num=5 ssr based chi2 test: chi2=11.1496 , p=0.0485 , df=5 likelihood ratio test: chi2=10.6333 , p=0.0592 , df=5 parameter F test: F=2.0129 , p=0.0830 , df_denom=102, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.5980 , p=0.4398 , df_denom=375, df_num=1 ssr based chi2 test: chi2=0.6028 , p=0.4375 , df=1 likelihood ratio test: chi2=0.6023 , p=0.4377 , df=1 parameter F test: F=0.5980 , p=0.4398 , df_denom=375, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.7601 , p=0.4684 , df_denom=372, df_num=2 ssr based chi2 test: chi2=1.5406 , p=0.4629 , df=2 likelihood ratio test: chi2=1.5374 , p=0.4636 , df=2 parameter F test: F=0.7601 , p=0.4684 , df_denom=372, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=2.5019 , p=0.0591 , df_denom=369, df_num=3 ssr based chi2 test: chi2=7.6482 , p=0.0539 , df=3 likelihood ratio test: chi2=7.5714 , p=0.0558 , df=3 parameter F test: F=2.5019 , p=0.0591 , df_denom=369, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=2.2706 , p=0.0612 , df_denom=366, df_num=4 ssr based chi2 test: chi2=9.3059 , p=0.0539 , df=4 likelihood ratio test: chi2=9.1923 , p=0.0565 , df=4 parameter F test: F=2.2706 , p=0.0612 , df_denom=366, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=1.9036 , p=0.0930 , df_denom=363, df_num=5 ssr based chi2 test: chi2=9.8062 , p=0.0809 , df=5 likelihood ratio test: chi2=9.6799 , p=0.0848 , df=5 parameter F test: F=1.9036 , p=0.0930 , df_denom=363, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.5980 , p=0.4398 , df_denom=375, df_num=1 ssr based chi2 test: chi2=0.6028 , p=0.4375 , df=1 likelihood ratio test: chi2=0.6023 , p=0.4377 , df=1 parameter F test: F=0.5980 , p=0.4398 , df_denom=375, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.7601 , p=0.4684 , df_denom=372, df_num=2 ssr based chi2 test: chi2=1.5406 , p=0.4629 , df=2 likelihood ratio test: chi2=1.5374 , p=0.4636 , df=2 parameter F test: F=0.7601 , p=0.4684 , df_denom=372, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=2.5019 , p=0.0591 , df_denom=369, df_num=3 ssr based chi2 test: chi2=7.6482 , p=0.0539 , df=3 likelihood ratio test: chi2=7.5714 , p=0.0558 , df=3 parameter F test: F=2.5019 , p=0.0591 , df_denom=369, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=2.2706 , p=0.0612 , df_denom=366, df_num=4 ssr based chi2 test: chi2=9.3059 , p=0.0539 , df=4 likelihood ratio test: chi2=9.1923 , p=0.0565 , df=4 parameter F test: F=2.2706 , p=0.0612 , df_denom=366, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=1.9036 , p=0.0930 , df_denom=363, df_num=5 ssr based chi2 test: chi2=9.8062 , p=0.0809 , df=5 likelihood ratio test: chi2=9.6799 , p=0.0848 , df=5 parameter F test: F=1.9036 , p=0.0930 , df_denom=363, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.0001 , p=0.9908 , df_denom=105, df_num=1 ssr based chi2 test: chi2=0.0001 , p=0.9907 , df=1 likelihood ratio test: chi2=0.0001 , p=0.9907 , df=1 parameter F test: F=0.0001 , p=0.9908 , df_denom=105, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=2.6228 , p=0.0775 , df_denom=102, df_num=2 ssr based chi2 test: chi2=5.5027 , p=0.0638 , df=2 likelihood ratio test: chi2=5.3659 , p=0.0684 , df=2 parameter F test: F=2.6228 , p=0.0775 , df_denom=102, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=2.1593 , p=0.0976 , df_denom=99, df_num=3 ssr based chi2 test: chi2=6.9360 , p=0.0740 , df=3 likelihood ratio test: chi2=6.7185 , p=0.0814 , df=3 parameter F test: F=2.1593 , p=0.0976 , df_denom=99, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=1.6521 , p=0.1675 , df_denom=96, df_num=4 ssr based chi2 test: chi2=7.2279 , p=0.1243 , df=4 likelihood ratio test: chi2=6.9900 , p=0.1364 , df=4 parameter F test: F=1.6521 , p=0.1675 , df_denom=96, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=2.1163 , p=0.0703 , df_denom=93, df_num=5 ssr based chi2 test: chi2=11.8333 , p=0.0371 , df=5 likelihood ratio test: chi2=11.2072 , p=0.0474 , df=5 parameter F test: F=2.1163 , p=0.0703 , df_denom=93, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.0001 , p=0.9908 , df_denom=105, df_num=1 ssr based chi2 test: chi2=0.0001 , p=0.9907 , df=1 likelihood ratio test: chi2=0.0001 , p=0.9907 , df=1 parameter F test: F=0.0001 , p=0.9908 , df_denom=105, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=2.6228 , p=0.0775 , df_denom=102, df_num=2 ssr based chi2 test: chi2=5.5027 , p=0.0638 , df=2 likelihood ratio test: chi2=5.3659 , p=0.0684 , df=2 parameter F test: F=2.6228 , p=0.0775 , df_denom=102, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=2.1593 , p=0.0976 , df_denom=99, df_num=3 ssr based chi2 test: chi2=6.9360 , p=0.0740 , df=3 likelihood ratio test: chi2=6.7185 , p=0.0814 , df=3 parameter F test: F=2.1593 , p=0.0976 , df_denom=99, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=1.6521 , p=0.1675 , df_denom=96, df_num=4 ssr based chi2 test: chi2=7.2279 , p=0.1243 , df=4 likelihood ratio test: chi2=6.9900 , p=0.1364 , df=4 parameter F test: F=1.6521 , p=0.1675 , df_denom=96, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=2.1163 , p=0.0703 , df_denom=93, df_num=5 ssr based chi2 test: chi2=11.8333 , p=0.0371 , df=5 likelihood ratio test: chi2=11.2072 , p=0.0474 , df=5 parameter F test: F=2.1163 , p=0.0703 , df_denom=93, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.6285 , p=0.4294 , df_denom=129, df_num=1 ssr based chi2 test: chi2=0.6431 , p=0.4226 , df=1 likelihood ratio test: chi2=0.6416 , p=0.4231 , df=1 parameter F test: F=0.6285 , p=0.4294 , df_denom=129, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.3287 , p=0.7205 , df_denom=126, df_num=2 ssr based chi2 test: chi2=0.6834 , p=0.7106 , df=2 likelihood ratio test: chi2=0.6816 , p=0.7112 , df=2 parameter F test: F=0.3287 , p=0.7205 , df_denom=126, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.4770 , p=0.6989 , df_denom=123, df_num=3 ssr based chi2 test: chi2=1.5123 , p=0.6794 , df=3 likelihood ratio test: chi2=1.5036 , p=0.6814 , df=3 parameter F test: F=0.4770 , p=0.6989 , df_denom=123, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.4534 , p=0.7697 , df_denom=120, df_num=4 ssr based chi2 test: chi2=1.9498 , p=0.7450 , df=4 likelihood ratio test: chi2=1.9352 , p=0.7477 , df=4 parameter F test: F=0.4534 , p=0.7697 , df_denom=120, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.3605 , p=0.8746 , df_denom=117, df_num=5 ssr based chi2 test: chi2=1.9720 , p=0.8530 , df=5 likelihood ratio test: chi2=1.9569 , p=0.8551 , df=5 parameter F test: F=0.3605 , p=0.8746 , df_denom=117, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.6285 , p=0.4294 , df_denom=129, df_num=1 ssr based chi2 test: chi2=0.6431 , p=0.4226 , df=1 likelihood ratio test: chi2=0.6416 , p=0.4231 , df=1 parameter F test: F=0.6285 , p=0.4294 , df_denom=129, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.3287 , p=0.7205 , df_denom=126, df_num=2 ssr based chi2 test: chi2=0.6834 , p=0.7106 , df=2 likelihood ratio test: chi2=0.6816 , p=0.7112 , df=2 parameter F test: F=0.3287 , p=0.7205 , df_denom=126, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.4770 , p=0.6989 , df_denom=123, df_num=3 ssr based chi2 test: chi2=1.5123 , p=0.6794 , df=3 likelihood ratio test: chi2=1.5036 , p=0.6814 , df=3 parameter F test: F=0.4770 , p=0.6989 , df_denom=123, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.4534 , p=0.7697 , df_denom=120, df_num=4 ssr based chi2 test: chi2=1.9498 , p=0.7450 , df=4 likelihood ratio test: chi2=1.9352 , p=0.7477 , df=4 parameter F test: F=0.4534 , p=0.7697 , df_denom=120, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.3605 , p=0.8746 , df_denom=117, df_num=5 ssr based chi2 test: chi2=1.9720 , p=0.8530 , df=5 likelihood ratio test: chi2=1.9569 , p=0.8551 , df=5 parameter F test: F=0.3605 , p=0.8746 , df_denom=117, df_num=5
| F_1 | P_1 | F_2 | P_2 | F_3 | P_3 | F_4 | P_4 | |
|---|---|---|---|---|---|---|---|---|
| 0 | 1.429561 | 0.234317 | 0.598033 | 0.439817 | 0.000133 | 0.990835 | 0.628527 | 0.429352 |
| 1 | 0.947436 | 0.390846 | 0.760072 | 0.468358 | 2.622796 | 0.077492 | 0.328654 | 0.720508 |
| 2 | 2.055505 | 0.110428 | 2.501929 | 0.059107 | 2.159328 | 0.097625 | 0.476965 | 0.698893 |
| 3 | 1.450791 | 0.222554 | 2.270639 | 0.061197 | 1.652086 | 0.167541 | 0.453437 | 0.769719 |
| 4 | 2.012854 | 0.083027 | 1.903562 | 0.092961 | 2.116343 | 0.070266 | 0.360498 | 0.874559 |
#周频数据——(SPOP,HSCL)
weekly_3_df = pd.DataFrame()
weekly_3_df['F_1'] = get_G_results(w_SP500_df_1['R_OP'], w_HS300_df_1['R_CL'], 5)['F']
weekly_3_df['P_1'] = get_G_results(w_SP500_df_1['R_OP'], w_HS300_df_1['R_CL'], 5)['P']
weekly_3_df['F_2'] = get_G_results(w_SP500_df_2['R_OP'], w_HS300_df_2['R_CL'], 5)['F']
weekly_3_df['P_2'] = get_G_results(w_SP500_df_2['R_OP'], w_HS300_df_2['R_CL'], 5)['P']
weekly_3_df['F_3'] = get_G_results(w_SP500_df_3['R_OP'], w_HS300_df_3['R_CL'], 5)['F']
weekly_3_df['P_3'] = get_G_results(w_SP500_df_3['R_OP'], w_HS300_df_3['R_CL'], 5)['P']
weekly_3_df['F_4'] = get_G_results(w_SP500_df_4['R_OP'], w_HS300_df_4['R_CL'], 5)['F']
weekly_3_df['P_4'] = get_G_results(w_SP500_df_4['R_OP'], w_HS300_df_4['R_CL'], 5)['P']
weekly_3_df
Granger Causality number of lags (no zero) 1 ssr based F test: F=0.0622 , p=0.8036 , df_denom=114, df_num=1 ssr based chi2 test: chi2=0.0638 , p=0.8006 , df=1 likelihood ratio test: chi2=0.0638 , p=0.8006 , df=1 parameter F test: F=0.0622 , p=0.8036 , df_denom=114, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.4018 , p=0.6701 , df_denom=111, df_num=2 ssr based chi2 test: chi2=0.8399 , p=0.6571 , df=2 likelihood ratio test: chi2=0.8368 , p=0.6581 , df=2 parameter F test: F=0.4018 , p=0.6701 , df_denom=111, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.5921 , p=0.6215 , df_denom=108, df_num=3 ssr based chi2 test: chi2=1.8915 , p=0.5952 , df=3 likelihood ratio test: chi2=1.8761 , p=0.5985 , df=3 parameter F test: F=0.5921 , p=0.6215 , df_denom=108, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.4138 , p=0.7983 , df_denom=105, df_num=4 ssr based chi2 test: chi2=1.7971 , p=0.7730 , df=4 likelihood ratio test: chi2=1.7831 , p=0.7756 , df=4 parameter F test: F=0.4138 , p=0.7983 , df_denom=105, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.3966 , p=0.8502 , df_denom=102, df_num=5 ssr based chi2 test: chi2=2.1966 , p=0.8213 , df=5 likelihood ratio test: chi2=2.1755 , p=0.8244 , df=5 parameter F test: F=0.3966 , p=0.8502 , df_denom=102, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.0622 , p=0.8036 , df_denom=114, df_num=1 ssr based chi2 test: chi2=0.0638 , p=0.8006 , df=1 likelihood ratio test: chi2=0.0638 , p=0.8006 , df=1 parameter F test: F=0.0622 , p=0.8036 , df_denom=114, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.4018 , p=0.6701 , df_denom=111, df_num=2 ssr based chi2 test: chi2=0.8399 , p=0.6571 , df=2 likelihood ratio test: chi2=0.8368 , p=0.6581 , df=2 parameter F test: F=0.4018 , p=0.6701 , df_denom=111, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.5921 , p=0.6215 , df_denom=108, df_num=3 ssr based chi2 test: chi2=1.8915 , p=0.5952 , df=3 likelihood ratio test: chi2=1.8761 , p=0.5985 , df=3 parameter F test: F=0.5921 , p=0.6215 , df_denom=108, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.4138 , p=0.7983 , df_denom=105, df_num=4 ssr based chi2 test: chi2=1.7971 , p=0.7730 , df=4 likelihood ratio test: chi2=1.7831 , p=0.7756 , df=4 parameter F test: F=0.4138 , p=0.7983 , df_denom=105, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.3966 , p=0.8502 , df_denom=102, df_num=5 ssr based chi2 test: chi2=2.1966 , p=0.8213 , df=5 likelihood ratio test: chi2=2.1755 , p=0.8244 , df=5 parameter F test: F=0.3966 , p=0.8502 , df_denom=102, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.4042 , p=0.5253 , df_denom=375, df_num=1 ssr based chi2 test: chi2=0.4075 , p=0.5233 , df=1 likelihood ratio test: chi2=0.4073 , p=0.5234 , df=1 parameter F test: F=0.4042 , p=0.5253 , df_denom=375, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=1.2372 , p=0.2914 , df_denom=372, df_num=2 ssr based chi2 test: chi2=2.5076 , p=0.2854 , df=2 likelihood ratio test: chi2=2.4993 , p=0.2866 , df=2 parameter F test: F=1.2372 , p=0.2914 , df_denom=372, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.8759 , p=0.4537 , df_denom=369, df_num=3 ssr based chi2 test: chi2=2.6776 , p=0.4441 , df=3 likelihood ratio test: chi2=2.6681 , p=0.4457 , df=3 parameter F test: F=0.8759 , p=0.4537 , df_denom=369, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=1.2524 , p=0.2884 , df_denom=366, df_num=4 ssr based chi2 test: chi2=5.1326 , p=0.2740 , df=4 likelihood ratio test: chi2=5.0978 , p=0.2774 , df=4 parameter F test: F=1.2524 , p=0.2884 , df_denom=366, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=1.0263 , p=0.4018 , df_denom=363, df_num=5 ssr based chi2 test: chi2=5.2870 , p=0.3819 , df=5 likelihood ratio test: chi2=5.2500 , p=0.3861 , df=5 parameter F test: F=1.0263 , p=0.4018 , df_denom=363, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.4042 , p=0.5253 , df_denom=375, df_num=1 ssr based chi2 test: chi2=0.4075 , p=0.5233 , df=1 likelihood ratio test: chi2=0.4073 , p=0.5234 , df=1 parameter F test: F=0.4042 , p=0.5253 , df_denom=375, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=1.2372 , p=0.2914 , df_denom=372, df_num=2 ssr based chi2 test: chi2=2.5076 , p=0.2854 , df=2 likelihood ratio test: chi2=2.4993 , p=0.2866 , df=2 parameter F test: F=1.2372 , p=0.2914 , df_denom=372, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.8759 , p=0.4537 , df_denom=369, df_num=3 ssr based chi2 test: chi2=2.6776 , p=0.4441 , df=3 likelihood ratio test: chi2=2.6681 , p=0.4457 , df=3 parameter F test: F=0.8759 , p=0.4537 , df_denom=369, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=1.2524 , p=0.2884 , df_denom=366, df_num=4 ssr based chi2 test: chi2=5.1326 , p=0.2740 , df=4 likelihood ratio test: chi2=5.0978 , p=0.2774 , df=4 parameter F test: F=1.2524 , p=0.2884 , df_denom=366, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=1.0263 , p=0.4018 , df_denom=363, df_num=5 ssr based chi2 test: chi2=5.2870 , p=0.3819 , df=5 likelihood ratio test: chi2=5.2500 , p=0.3861 , df=5 parameter F test: F=1.0263 , p=0.4018 , df_denom=363, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.0000 , p=0.9961 , df_denom=105, df_num=1 ssr based chi2 test: chi2=0.0000 , p=0.9960 , df=1 likelihood ratio test: chi2=0.0000 , p=0.9960 , df=1 parameter F test: F=0.0000 , p=0.9961 , df_denom=105, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.0128 , p=0.9873 , df_denom=102, df_num=2 ssr based chi2 test: chi2=0.0269 , p=0.9866 , df=2 likelihood ratio test: chi2=0.0269 , p=0.9866 , df=2 parameter F test: F=0.0128 , p=0.9873 , df_denom=102, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.1848 , p=0.9065 , df_denom=99, df_num=3 ssr based chi2 test: chi2=0.5936 , p=0.8979 , df=3 likelihood ratio test: chi2=0.5920 , p=0.8983 , df=3 parameter F test: F=0.1848 , p=0.9065 , df_denom=99, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.6009 , p=0.6629 , df_denom=96, df_num=4 ssr based chi2 test: chi2=2.6291 , p=0.6217 , df=4 likelihood ratio test: chi2=2.5967 , p=0.6274 , df=4 parameter F test: F=0.6009 , p=0.6629 , df_denom=96, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.7410 , p=0.5947 , df_denom=93, df_num=5 ssr based chi2 test: chi2=4.1433 , p=0.5290 , df=5 likelihood ratio test: chi2=4.0629 , p=0.5404 , df=5 parameter F test: F=0.7410 , p=0.5947 , df_denom=93, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.0000 , p=0.9961 , df_denom=105, df_num=1 ssr based chi2 test: chi2=0.0000 , p=0.9960 , df=1 likelihood ratio test: chi2=0.0000 , p=0.9960 , df=1 parameter F test: F=0.0000 , p=0.9961 , df_denom=105, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.0128 , p=0.9873 , df_denom=102, df_num=2 ssr based chi2 test: chi2=0.0269 , p=0.9866 , df=2 likelihood ratio test: chi2=0.0269 , p=0.9866 , df=2 parameter F test: F=0.0128 , p=0.9873 , df_denom=102, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.1848 , p=0.9065 , df_denom=99, df_num=3 ssr based chi2 test: chi2=0.5936 , p=0.8979 , df=3 likelihood ratio test: chi2=0.5920 , p=0.8983 , df=3 parameter F test: F=0.1848 , p=0.9065 , df_denom=99, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.6009 , p=0.6629 , df_denom=96, df_num=4 ssr based chi2 test: chi2=2.6291 , p=0.6217 , df=4 likelihood ratio test: chi2=2.5967 , p=0.6274 , df=4 parameter F test: F=0.6009 , p=0.6629 , df_denom=96, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.7410 , p=0.5947 , df_denom=93, df_num=5 ssr based chi2 test: chi2=4.1433 , p=0.5290 , df=5 likelihood ratio test: chi2=4.0629 , p=0.5404 , df=5 parameter F test: F=0.7410 , p=0.5947 , df_denom=93, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=2.9227 , p=0.0897 , df_denom=129, df_num=1 ssr based chi2 test: chi2=2.9907 , p=0.0837 , df=1 likelihood ratio test: chi2=2.9573 , p=0.0855 , df=1 parameter F test: F=2.9227 , p=0.0897 , df_denom=129, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=1.7912 , p=0.1710 , df_denom=126, df_num=2 ssr based chi2 test: chi2=3.7245 , p=0.1553 , df=2 likelihood ratio test: chi2=3.6725 , p=0.1594 , df=2 parameter F test: F=1.7912 , p=0.1710 , df_denom=126, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=2.2992 , p=0.0807 , df_denom=123, df_num=3 ssr based chi2 test: chi2=7.2901 , p=0.0632 , df=3 likelihood ratio test: chi2=7.0931 , p=0.0690 , df=3 parameter F test: F=2.2992 , p=0.0807 , df_denom=123, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=2.4825 , p=0.0474 , df_denom=120, df_num=4 ssr based chi2 test: chi2=10.6747 , p=0.0305 , df=4 likelihood ratio test: chi2=10.2559 , p=0.0363 , df=4 parameter F test: F=2.4825 , p=0.0474 , df_denom=120, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=2.3853 , p=0.0423 , df_denom=117, df_num=5 ssr based chi2 test: chi2=13.0478 , p=0.0229 , df=5 likelihood ratio test: chi2=12.4248 , p=0.0294 , df=5 parameter F test: F=2.3853 , p=0.0423 , df_denom=117, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=2.9227 , p=0.0897 , df_denom=129, df_num=1 ssr based chi2 test: chi2=2.9907 , p=0.0837 , df=1 likelihood ratio test: chi2=2.9573 , p=0.0855 , df=1 parameter F test: F=2.9227 , p=0.0897 , df_denom=129, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=1.7912 , p=0.1710 , df_denom=126, df_num=2 ssr based chi2 test: chi2=3.7245 , p=0.1553 , df=2 likelihood ratio test: chi2=3.6725 , p=0.1594 , df=2 parameter F test: F=1.7912 , p=0.1710 , df_denom=126, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=2.2992 , p=0.0807 , df_denom=123, df_num=3 ssr based chi2 test: chi2=7.2901 , p=0.0632 , df=3 likelihood ratio test: chi2=7.0931 , p=0.0690 , df=3 parameter F test: F=2.2992 , p=0.0807 , df_denom=123, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=2.4825 , p=0.0474 , df_denom=120, df_num=4 ssr based chi2 test: chi2=10.6747 , p=0.0305 , df=4 likelihood ratio test: chi2=10.2559 , p=0.0363 , df=4 parameter F test: F=2.4825 , p=0.0474 , df_denom=120, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=2.3853 , p=0.0423 , df_denom=117, df_num=5 ssr based chi2 test: chi2=13.0478 , p=0.0229 , df=5 likelihood ratio test: chi2=12.4248 , p=0.0294 , df=5 parameter F test: F=2.3853 , p=0.0423 , df_denom=117, df_num=5
| F_1 | P_1 | F_2 | P_2 | F_3 | P_3 | F_4 | P_4 | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.062162 | 0.803560 | 0.404245 | 0.525293 | 0.000024 | 0.996086 | 2.922741 | 0.089744 |
| 1 | 0.401830 | 0.670064 | 1.237169 | 0.291396 | 0.012819 | 0.987264 | 1.791170 | 0.170985 |
| 2 | 0.592117 | 0.621481 | 0.875910 | 0.453653 | 0.184811 | 0.906502 | 2.299196 | 0.080728 |
| 3 | 0.413817 | 0.798350 | 1.252365 | 0.288423 | 0.600937 | 0.662862 | 2.482478 | 0.047358 |
| 4 | 0.396557 | 0.850191 | 1.026305 | 0.401818 | 0.741013 | 0.594672 | 2.385304 | 0.042308 |
#周频数据——(SPCL,HSCL)
weekly_4_df = pd.DataFrame()
weekly_4_df['F_1'] = get_G_results(w_SP500_df_1['R_CL'], w_HS300_df_1['R_CL'], 5)['F']
weekly_4_df['P_1'] = get_G_results(w_SP500_df_1['R_CL'], w_HS300_df_1['R_CL'], 5)['P']
weekly_4_df['F_2'] = get_G_results(w_SP500_df_2['R_CL'], w_HS300_df_2['R_CL'], 5)['F']
weekly_4_df['P_2'] = get_G_results(w_SP500_df_2['R_CL'], w_HS300_df_2['R_CL'], 5)['P']
weekly_4_df['F_3'] = get_G_results(w_SP500_df_3['R_CL'], w_HS300_df_3['R_CL'], 5)['F']
weekly_4_df['P_3'] = get_G_results(w_SP500_df_3['R_CL'], w_HS300_df_3['R_CL'], 5)['P']
weekly_4_df['F_4'] = get_G_results(w_SP500_df_4['R_CL'], w_HS300_df_4['R_CL'], 5)['F']
weekly_4_df['P_4'] = get_G_results(w_SP500_df_4['R_CL'], w_HS300_df_4['R_CL'], 5)['P']
weekly_4_df
Granger Causality number of lags (no zero) 1 ssr based F test: F=0.5307 , p=0.4678 , df_denom=114, df_num=1 ssr based chi2 test: chi2=0.5447 , p=0.4605 , df=1 likelihood ratio test: chi2=0.5434 , p=0.4610 , df=1 parameter F test: F=0.5307 , p=0.4678 , df_denom=114, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.3171 , p=0.7289 , df_denom=111, df_num=2 ssr based chi2 test: chi2=0.6627 , p=0.7179 , df=2 likelihood ratio test: chi2=0.6608 , p=0.7186 , df=2 parameter F test: F=0.3171 , p=0.7289 , df_denom=111, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.2842 , p=0.8367 , df_denom=108, df_num=3 ssr based chi2 test: chi2=0.9078 , p=0.8236 , df=3 likelihood ratio test: chi2=0.9042 , p=0.8244 , df=3 parameter F test: F=0.2842 , p=0.8367 , df_denom=108, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.3917 , p=0.8142 , df_denom=105, df_num=4 ssr based chi2 test: chi2=1.7009 , p=0.7905 , df=4 likelihood ratio test: chi2=1.6884 , p=0.7928 , df=4 parameter F test: F=0.3917 , p=0.8142 , df_denom=105, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.7895 , p=0.5596 , df_denom=102, df_num=5 ssr based chi2 test: chi2=4.3732 , p=0.4970 , df=5 likelihood ratio test: chi2=4.2907 , p=0.5084 , df=5 parameter F test: F=0.7895 , p=0.5596 , df_denom=102, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.5307 , p=0.4678 , df_denom=114, df_num=1 ssr based chi2 test: chi2=0.5447 , p=0.4605 , df=1 likelihood ratio test: chi2=0.5434 , p=0.4610 , df=1 parameter F test: F=0.5307 , p=0.4678 , df_denom=114, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.3171 , p=0.7289 , df_denom=111, df_num=2 ssr based chi2 test: chi2=0.6627 , p=0.7179 , df=2 likelihood ratio test: chi2=0.6608 , p=0.7186 , df=2 parameter F test: F=0.3171 , p=0.7289 , df_denom=111, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.2842 , p=0.8367 , df_denom=108, df_num=3 ssr based chi2 test: chi2=0.9078 , p=0.8236 , df=3 likelihood ratio test: chi2=0.9042 , p=0.8244 , df=3 parameter F test: F=0.2842 , p=0.8367 , df_denom=108, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.3917 , p=0.8142 , df_denom=105, df_num=4 ssr based chi2 test: chi2=1.7009 , p=0.7905 , df=4 likelihood ratio test: chi2=1.6884 , p=0.7928 , df=4 parameter F test: F=0.3917 , p=0.8142 , df_denom=105, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.7895 , p=0.5596 , df_denom=102, df_num=5 ssr based chi2 test: chi2=4.3732 , p=0.4970 , df=5 likelihood ratio test: chi2=4.2907 , p=0.5084 , df=5 parameter F test: F=0.7895 , p=0.5596 , df_denom=102, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.9023 , p=0.3428 , df_denom=375, df_num=1 ssr based chi2 test: chi2=0.9095 , p=0.3403 , df=1 likelihood ratio test: chi2=0.9084 , p=0.3405 , df=1 parameter F test: F=0.9023 , p=0.3428 , df_denom=375, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=2.2407 , p=0.1078 , df_denom=372, df_num=2 ssr based chi2 test: chi2=4.5417 , p=0.1032 , df=2 likelihood ratio test: chi2=4.5146 , p=0.1046 , df=2 parameter F test: F=2.2407 , p=0.1078 , df_denom=372, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=1.6897 , p=0.1688 , df_denom=369, df_num=3 ssr based chi2 test: chi2=5.1652 , p=0.1601 , df=3 likelihood ratio test: chi2=5.1300 , p=0.1625 , df=3 parameter F test: F=1.6897 , p=0.1688 , df_denom=369, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=2.2644 , p=0.0618 , df_denom=366, df_num=4 ssr based chi2 test: chi2=9.2805 , p=0.0545 , df=4 likelihood ratio test: chi2=9.1675 , p=0.0570 , df=4 parameter F test: F=2.2644 , p=0.0618 , df_denom=366, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=1.7806 , p=0.1160 , df_denom=363, df_num=5 ssr based chi2 test: chi2=9.1727 , p=0.1024 , df=5 likelihood ratio test: chi2=9.0620 , p=0.1066 , df=5 parameter F test: F=1.7806 , p=0.1160 , df_denom=363, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.9023 , p=0.3428 , df_denom=375, df_num=1 ssr based chi2 test: chi2=0.9095 , p=0.3403 , df=1 likelihood ratio test: chi2=0.9084 , p=0.3405 , df=1 parameter F test: F=0.9023 , p=0.3428 , df_denom=375, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=2.2407 , p=0.1078 , df_denom=372, df_num=2 ssr based chi2 test: chi2=4.5417 , p=0.1032 , df=2 likelihood ratio test: chi2=4.5146 , p=0.1046 , df=2 parameter F test: F=2.2407 , p=0.1078 , df_denom=372, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=1.6897 , p=0.1688 , df_denom=369, df_num=3 ssr based chi2 test: chi2=5.1652 , p=0.1601 , df=3 likelihood ratio test: chi2=5.1300 , p=0.1625 , df=3 parameter F test: F=1.6897 , p=0.1688 , df_denom=369, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=2.2644 , p=0.0618 , df_denom=366, df_num=4 ssr based chi2 test: chi2=9.2805 , p=0.0545 , df=4 likelihood ratio test: chi2=9.1675 , p=0.0570 , df=4 parameter F test: F=2.2644 , p=0.0618 , df_denom=366, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=1.7806 , p=0.1160 , df_denom=363, df_num=5 ssr based chi2 test: chi2=9.1727 , p=0.1024 , df=5 likelihood ratio test: chi2=9.0620 , p=0.1066 , df=5 parameter F test: F=1.7806 , p=0.1160 , df_denom=363, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.1439 , p=0.7052 , df_denom=105, df_num=1 ssr based chi2 test: chi2=0.1480 , p=0.7004 , df=1 likelihood ratio test: chi2=0.1479 , p=0.7005 , df=1 parameter F test: F=0.1439 , p=0.7052 , df_denom=105, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.1852 , p=0.8312 , df_denom=102, df_num=2 ssr based chi2 test: chi2=0.3887 , p=0.8234 , df=2 likelihood ratio test: chi2=0.3880 , p=0.8237 , df=2 parameter F test: F=0.1852 , p=0.8312 , df_denom=102, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.0503 , p=0.9850 , df_denom=99, df_num=3 ssr based chi2 test: chi2=0.1615 , p=0.9836 , df=3 likelihood ratio test: chi2=0.1613 , p=0.9836 , df=3 parameter F test: F=0.0503 , p=0.9850 , df_denom=99, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.0364 , p=0.9974 , df_denom=96, df_num=4 ssr based chi2 test: chi2=0.1593 , p=0.9970 , df=4 likelihood ratio test: chi2=0.1591 , p=0.9970 , df=4 parameter F test: F=0.0364 , p=0.9974 , df_denom=96, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.0702 , p=0.9965 , df_denom=93, df_num=5 ssr based chi2 test: chi2=0.3926 , p=0.9955 , df=5 likelihood ratio test: chi2=0.3918 , p=0.9956 , df=5 parameter F test: F=0.0702 , p=0.9965 , df_denom=93, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.1439 , p=0.7052 , df_denom=105, df_num=1 ssr based chi2 test: chi2=0.1480 , p=0.7004 , df=1 likelihood ratio test: chi2=0.1479 , p=0.7005 , df=1 parameter F test: F=0.1439 , p=0.7052 , df_denom=105, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.1852 , p=0.8312 , df_denom=102, df_num=2 ssr based chi2 test: chi2=0.3887 , p=0.8234 , df=2 likelihood ratio test: chi2=0.3880 , p=0.8237 , df=2 parameter F test: F=0.1852 , p=0.8312 , df_denom=102, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.0503 , p=0.9850 , df_denom=99, df_num=3 ssr based chi2 test: chi2=0.1615 , p=0.9836 , df=3 likelihood ratio test: chi2=0.1613 , p=0.9836 , df=3 parameter F test: F=0.0503 , p=0.9850 , df_denom=99, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.0364 , p=0.9974 , df_denom=96, df_num=4 ssr based chi2 test: chi2=0.1593 , p=0.9970 , df=4 likelihood ratio test: chi2=0.1591 , p=0.9970 , df=4 parameter F test: F=0.0364 , p=0.9974 , df_denom=96, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.0702 , p=0.9965 , df_denom=93, df_num=5 ssr based chi2 test: chi2=0.3926 , p=0.9955 , df=5 likelihood ratio test: chi2=0.3918 , p=0.9956 , df=5 parameter F test: F=0.0702 , p=0.9965 , df_denom=93, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.2372 , p=0.6271 , df_denom=129, df_num=1 ssr based chi2 test: chi2=0.2427 , p=0.6223 , df=1 likelihood ratio test: chi2=0.2425 , p=0.6224 , df=1 parameter F test: F=0.2372 , p=0.6271 , df_denom=129, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.5105 , p=0.6014 , df_denom=126, df_num=2 ssr based chi2 test: chi2=1.0615 , p=0.5882 , df=2 likelihood ratio test: chi2=1.0572 , p=0.5894 , df=2 parameter F test: F=0.5105 , p=0.6014 , df_denom=126, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.3343 , p=0.8006 , df_denom=123, df_num=3 ssr based chi2 test: chi2=1.0599 , p=0.7868 , df=3 likelihood ratio test: chi2=1.0556 , p=0.7878 , df=3 parameter F test: F=0.3343 , p=0.8006 , df_denom=123, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.2638 , p=0.9007 , df_denom=120, df_num=4 ssr based chi2 test: chi2=1.1343 , p=0.8888 , df=4 likelihood ratio test: chi2=1.1294 , p=0.8896 , df=4 parameter F test: F=0.2638 , p=0.9007 , df_denom=120, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.3551 , p=0.8781 , df_denom=117, df_num=5 ssr based chi2 test: chi2=1.9424 , p=0.8571 , df=5 likelihood ratio test: chi2=1.9278 , p=0.8590 , df=5 parameter F test: F=0.3551 , p=0.8781 , df_denom=117, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.2372 , p=0.6271 , df_denom=129, df_num=1 ssr based chi2 test: chi2=0.2427 , p=0.6223 , df=1 likelihood ratio test: chi2=0.2425 , p=0.6224 , df=1 parameter F test: F=0.2372 , p=0.6271 , df_denom=129, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.5105 , p=0.6014 , df_denom=126, df_num=2 ssr based chi2 test: chi2=1.0615 , p=0.5882 , df=2 likelihood ratio test: chi2=1.0572 , p=0.5894 , df=2 parameter F test: F=0.5105 , p=0.6014 , df_denom=126, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.3343 , p=0.8006 , df_denom=123, df_num=3 ssr based chi2 test: chi2=1.0599 , p=0.7868 , df=3 likelihood ratio test: chi2=1.0556 , p=0.7878 , df=3 parameter F test: F=0.3343 , p=0.8006 , df_denom=123, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.2638 , p=0.9007 , df_denom=120, df_num=4 ssr based chi2 test: chi2=1.1343 , p=0.8888 , df=4 likelihood ratio test: chi2=1.1294 , p=0.8896 , df=4 parameter F test: F=0.2638 , p=0.9007 , df_denom=120, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.3551 , p=0.8781 , df_denom=117, df_num=5 ssr based chi2 test: chi2=1.9424 , p=0.8571 , df=5 likelihood ratio test: chi2=1.9278 , p=0.8590 , df=5 parameter F test: F=0.3551 , p=0.8781 , df_denom=117, df_num=5
| F_1 | P_1 | F_2 | P_2 | F_3 | P_3 | F_4 | P_4 | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.530746 | 0.467787 | 0.902266 | 0.342787 | 0.143902 | 0.705199 | 0.237187 | 0.627072 |
| 1 | 0.317082 | 0.728928 | 2.240742 | 0.107814 | 0.185250 | 0.831176 | 0.510495 | 0.601434 |
| 2 | 0.284173 | 0.836732 | 1.689673 | 0.168796 | 0.050267 | 0.985019 | 0.334271 | 0.800577 |
| 3 | 0.391662 | 0.814210 | 2.264430 | 0.061808 | 0.036403 | 0.997427 | 0.263802 | 0.900674 |
| 4 | 0.789500 | 0.559613 | 1.780576 | 0.115970 | 0.070211 | 0.996455 | 0.355097 | 0.878074 |
#筛选月频交易日
def get_monthly_trade_days(df):
df['year-month'] = [str(i)[0:7] for i in df.index]
return df.drop_duplicates('year-month').index
#获取月频重合交易日
m_total_common_days = get_monthly_trade_days(SP500_df)
m_common_days_1 = get_monthly_trade_days(SP500_df_1)
m_common_days_2 = get_monthly_trade_days(SP500_df_2)
m_common_days_3 = get_monthly_trade_days(SP500_df_3)
m_common_days_4 = get_monthly_trade_days(SP500_df_4)
#整理月频量价数据
m_SP500_df = SP500_df.loc[m_total_common_days]
m_HS300_df = HS300_df.loc[m_total_common_days]
m_SP500_df_1 = SP500_df.loc[m_common_days_1]
m_HS300_df_1 = HS300_df.loc[m_common_days_1]
m_SP500_df_2 = SP500_df.loc[m_common_days_2]
m_HS300_df_2 = HS300_df.loc[m_common_days_2]
m_SP500_df_3 = SP500_df.loc[m_common_days_3]
m_HS300_df_3 = HS300_df.loc[m_common_days_3]
m_SP500_df_4 = SP500_df.loc[m_common_days_4]
m_HS300_df_4 = HS300_df.loc[m_common_days_4]
#月频数据——(HSOP,SPCL)
monthly_1_df = pd.DataFrame()
monthly_1_df['F_1'] = get_G_results(m_HS300_df_1['R_OP'], m_SP500_df_1['R_CL'], 5)['F']
monthly_1_df['P_1'] = get_G_results(m_HS300_df_1['R_OP'], m_SP500_df_1['R_CL'], 5)['P']
monthly_1_df['F_2'] = get_G_results(m_HS300_df_2['R_OP'], m_SP500_df_2['R_CL'], 5)['F']
monthly_1_df['P_2'] = get_G_results(m_HS300_df_2['R_OP'], m_SP500_df_2['R_CL'], 5)['P']
monthly_1_df['F_3'] = get_G_results(m_HS300_df_3['R_OP'], m_SP500_df_3['R_CL'], 5)['F']
monthly_1_df['P_3'] = get_G_results(m_HS300_df_3['R_OP'], m_SP500_df_3['R_CL'], 5)['P']
monthly_1_df['F_4'] = get_G_results(m_HS300_df_4['R_OP'], m_SP500_df_4['R_CL'], 5)['F']
monthly_1_df['P_4'] = get_G_results(m_HS300_df_4['R_OP'], m_SP500_df_4['R_CL'], 5)['P']
monthly_1_df
Granger Causality number of lags (no zero) 1 ssr based F test: F=1.2514 , p=0.2744 , df_denom=24, df_num=1 ssr based chi2 test: chi2=1.4078 , p=0.2354 , df=1 likelihood ratio test: chi2=1.3723 , p=0.2414 , df=1 parameter F test: F=1.2514 , p=0.2744 , df_denom=24, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.7478 , p=0.4856 , df_denom=21, df_num=2 ssr based chi2 test: chi2=1.8516 , p=0.3962 , df=2 likelihood ratio test: chi2=1.7887 , p=0.4089 , df=2 parameter F test: F=0.7478 , p=0.4856 , df_denom=21, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=1.7067 , p=0.2013 , df_denom=18, df_num=3 ssr based chi2 test: chi2=7.1114 , p=0.0684 , df=3 likelihood ratio test: chi2=6.2583 , p=0.0997 , df=3 parameter F test: F=1.7067 , p=0.2013 , df_denom=18, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.9377 , p=0.4688 , df_denom=15, df_num=4 ssr based chi2 test: chi2=6.0013 , p=0.1991 , df=4 likelihood ratio test: chi2=5.3564 , p=0.2526 , df=4 parameter F test: F=0.9377 , p=0.4688 , df_denom=15, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.4060 , p=0.8356 , df_denom=12, df_num=5 ssr based chi2 test: chi2=3.8904 , p=0.5653 , df=5 likelihood ratio test: chi2=3.5943 , p=0.6092 , df=5 parameter F test: F=0.4060 , p=0.8356 , df_denom=12, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=1.2514 , p=0.2744 , df_denom=24, df_num=1 ssr based chi2 test: chi2=1.4078 , p=0.2354 , df=1 likelihood ratio test: chi2=1.3723 , p=0.2414 , df=1 parameter F test: F=1.2514 , p=0.2744 , df_denom=24, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.7478 , p=0.4856 , df_denom=21, df_num=2 ssr based chi2 test: chi2=1.8516 , p=0.3962 , df=2 likelihood ratio test: chi2=1.7887 , p=0.4089 , df=2 parameter F test: F=0.7478 , p=0.4856 , df_denom=21, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=1.7067 , p=0.2013 , df_denom=18, df_num=3 ssr based chi2 test: chi2=7.1114 , p=0.0684 , df=3 likelihood ratio test: chi2=6.2583 , p=0.0997 , df=3 parameter F test: F=1.7067 , p=0.2013 , df_denom=18, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.9377 , p=0.4688 , df_denom=15, df_num=4 ssr based chi2 test: chi2=6.0013 , p=0.1991 , df=4 likelihood ratio test: chi2=5.3564 , p=0.2526 , df=4 parameter F test: F=0.9377 , p=0.4688 , df_denom=15, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.4060 , p=0.8356 , df_denom=12, df_num=5 ssr based chi2 test: chi2=3.8904 , p=0.5653 , df=5 likelihood ratio test: chi2=3.5943 , p=0.6092 , df=5 parameter F test: F=0.4060 , p=0.8356 , df_denom=12, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.9952 , p=0.3214 , df_denom=82, df_num=1 ssr based chi2 test: chi2=1.0316 , p=0.3098 , df=1 likelihood ratio test: chi2=1.0254 , p=0.3112 , df=1 parameter F test: F=0.9952 , p=0.3214 , df_denom=82, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.8481 , p=0.4321 , df_denom=79, df_num=2 ssr based chi2 test: chi2=1.8035 , p=0.4059 , df=2 likelihood ratio test: chi2=1.7844 , p=0.4098 , df=2 parameter F test: F=0.8481 , p=0.4321 , df_denom=79, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.6859 , p=0.5634 , df_denom=76, df_num=3 ssr based chi2 test: chi2=2.2472 , p=0.5227 , df=3 likelihood ratio test: chi2=2.2173 , p=0.5285 , df=3 parameter F test: F=0.6859 , p=0.5634 , df_denom=76, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.6042 , p=0.6608 , df_denom=73, df_num=4 ssr based chi2 test: chi2=2.7150 , p=0.6066 , df=4 likelihood ratio test: chi2=2.6710 , p=0.6143 , df=4 parameter F test: F=0.6042 , p=0.6608 , df_denom=73, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.7357 , p=0.5992 , df_denom=70, df_num=5 ssr based chi2 test: chi2=4.2568 , p=0.5131 , df=5 likelihood ratio test: chi2=4.1487 , p=0.5282 , df=5 parameter F test: F=0.7357 , p=0.5992 , df_denom=70, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.9952 , p=0.3214 , df_denom=82, df_num=1 ssr based chi2 test: chi2=1.0316 , p=0.3098 , df=1 likelihood ratio test: chi2=1.0254 , p=0.3112 , df=1 parameter F test: F=0.9952 , p=0.3214 , df_denom=82, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.8481 , p=0.4321 , df_denom=79, df_num=2 ssr based chi2 test: chi2=1.8035 , p=0.4059 , df=2 likelihood ratio test: chi2=1.7844 , p=0.4098 , df=2 parameter F test: F=0.8481 , p=0.4321 , df_denom=79, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.6859 , p=0.5634 , df_denom=76, df_num=3 ssr based chi2 test: chi2=2.2472 , p=0.5227 , df=3 likelihood ratio test: chi2=2.2173 , p=0.5285 , df=3 parameter F test: F=0.6859 , p=0.5634 , df_denom=76, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.6042 , p=0.6608 , df_denom=73, df_num=4 ssr based chi2 test: chi2=2.7150 , p=0.6066 , df=4 likelihood ratio test: chi2=2.6710 , p=0.6143 , df=4 parameter F test: F=0.6042 , p=0.6608 , df_denom=73, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.7357 , p=0.5992 , df_denom=70, df_num=5 ssr based chi2 test: chi2=4.2568 , p=0.5131 , df=5 likelihood ratio test: chi2=4.1487 , p=0.5282 , df=5 parameter F test: F=0.7357 , p=0.5992 , df_denom=70, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=1.6736 , p=0.2092 , df_denom=22, df_num=1 ssr based chi2 test: chi2=1.9019 , p=0.1679 , df=1 likelihood ratio test: chi2=1.8330 , p=0.1758 , df=1 parameter F test: F=1.6736 , p=0.2092 , df_denom=22, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.7293 , p=0.4953 , df_denom=19, df_num=2 ssr based chi2 test: chi2=1.8424 , p=0.3980 , df=2 likelihood ratio test: chi2=1.7751 , p=0.4117 , df=2 parameter F test: F=0.7293 , p=0.4953 , df_denom=19, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.0801 , p=0.9699 , df_denom=16, df_num=3 ssr based chi2 test: chi2=0.3455 , p=0.9513 , df=3 likelihood ratio test: chi2=0.3429 , p=0.9518 , df=3 parameter F test: F=0.0801 , p=0.9699 , df_denom=16, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.5796 , p=0.6827 , df_denom=13, df_num=4 ssr based chi2 test: chi2=3.9232 , p=0.4165 , df=4 likelihood ratio test: chi2=3.6101 , p=0.4613 , df=4 parameter F test: F=0.5796 , p=0.6827 , df_denom=13, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.7967 , p=0.5762 , df_denom=10, df_num=5 ssr based chi2 test: chi2=8.3649 , p=0.1372 , df=5 likelihood ratio test: chi2=7.0408 , p=0.2176 , df=5 parameter F test: F=0.7967 , p=0.5762 , df_denom=10, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=1.6736 , p=0.2092 , df_denom=22, df_num=1 ssr based chi2 test: chi2=1.9019 , p=0.1679 , df=1 likelihood ratio test: chi2=1.8330 , p=0.1758 , df=1 parameter F test: F=1.6736 , p=0.2092 , df_denom=22, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.7293 , p=0.4953 , df_denom=19, df_num=2 ssr based chi2 test: chi2=1.8424 , p=0.3980 , df=2 likelihood ratio test: chi2=1.7751 , p=0.4117 , df=2 parameter F test: F=0.7293 , p=0.4953 , df_denom=19, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.0801 , p=0.9699 , df_denom=16, df_num=3 ssr based chi2 test: chi2=0.3455 , p=0.9513 , df=3 likelihood ratio test: chi2=0.3429 , p=0.9518 , df=3 parameter F test: F=0.0801 , p=0.9699 , df_denom=16, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.5796 , p=0.6827 , df_denom=13, df_num=4 ssr based chi2 test: chi2=3.9232 , p=0.4165 , df=4 likelihood ratio test: chi2=3.6101 , p=0.4613 , df=4 parameter F test: F=0.5796 , p=0.6827 , df_denom=13, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.7967 , p=0.5762 , df_denom=10, df_num=5 ssr based chi2 test: chi2=8.3649 , p=0.1372 , df=5 likelihood ratio test: chi2=7.0408 , p=0.2176 , df=5 parameter F test: F=0.7967 , p=0.5762 , df_denom=10, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.1755 , p=0.6787 , df_denom=26, df_num=1 ssr based chi2 test: chi2=0.1958 , p=0.6581 , df=1 likelihood ratio test: chi2=0.1951 , p=0.6587 , df=1 parameter F test: F=0.1755 , p=0.6787 , df_denom=26, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.2537 , p=0.7780 , df_denom=23, df_num=2 ssr based chi2 test: chi2=0.6178 , p=0.7343 , df=2 likelihood ratio test: chi2=0.6111 , p=0.7367 , df=2 parameter F test: F=0.2537 , p=0.7780 , df_denom=23, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.1875 , p=0.9036 , df_denom=20, df_num=3 ssr based chi2 test: chi2=0.7595 , p=0.8591 , df=3 likelihood ratio test: chi2=0.7490 , p=0.8616 , df=3 parameter F test: F=0.1875 , p=0.9036 , df_denom=20, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.3405 , p=0.8469 , df_denom=17, df_num=4 ssr based chi2 test: chi2=2.0828 , p=0.7205 , df=4 likelihood ratio test: chi2=2.0035 , p=0.7351 , df=4 parameter F test: F=0.3405 , p=0.8469 , df_denom=17, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=1.1200 , p=0.3941 , df_denom=14, df_num=5 ssr based chi2 test: chi2=9.9998 , p=0.0752 , df=5 likelihood ratio test: chi2=8.4117 , p=0.1350 , df=5 parameter F test: F=1.1200 , p=0.3941 , df_denom=14, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.1755 , p=0.6787 , df_denom=26, df_num=1 ssr based chi2 test: chi2=0.1958 , p=0.6581 , df=1 likelihood ratio test: chi2=0.1951 , p=0.6587 , df=1 parameter F test: F=0.1755 , p=0.6787 , df_denom=26, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.2537 , p=0.7780 , df_denom=23, df_num=2 ssr based chi2 test: chi2=0.6178 , p=0.7343 , df=2 likelihood ratio test: chi2=0.6111 , p=0.7367 , df=2 parameter F test: F=0.2537 , p=0.7780 , df_denom=23, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.1875 , p=0.9036 , df_denom=20, df_num=3 ssr based chi2 test: chi2=0.7595 , p=0.8591 , df=3 likelihood ratio test: chi2=0.7490 , p=0.8616 , df=3 parameter F test: F=0.1875 , p=0.9036 , df_denom=20, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.3405 , p=0.8469 , df_denom=17, df_num=4 ssr based chi2 test: chi2=2.0828 , p=0.7205 , df=4 likelihood ratio test: chi2=2.0035 , p=0.7351 , df=4 parameter F test: F=0.3405 , p=0.8469 , df_denom=17, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=1.1200 , p=0.3941 , df_denom=14, df_num=5 ssr based chi2 test: chi2=9.9998 , p=0.0752 , df=5 likelihood ratio test: chi2=8.4117 , p=0.1350 , df=5 parameter F test: F=1.1200 , p=0.3941 , df_denom=14, df_num=5
| F_1 | P_1 | F_2 | P_2 | F_3 | P_3 | F_4 | P_4 | |
|---|---|---|---|---|---|---|---|---|
| 0 | 1.251356 | 0.274366 | 0.995187 | 0.321413 | 1.673639 | 0.209190 | 0.175548 | 0.678669 |
| 1 | 0.747769 | 0.485613 | 0.848065 | 0.432104 | 0.729290 | 0.495270 | 0.253730 | 0.778045 |
| 2 | 1.706724 | 0.201344 | 0.685893 | 0.563413 | 0.080105 | 0.969880 | 0.187536 | 0.903627 |
| 3 | 0.937696 | 0.468838 | 0.604246 | 0.660803 | 0.579564 | 0.682730 | 0.340450 | 0.846897 |
| 4 | 0.405955 | 0.835638 | 0.735735 | 0.599157 | 0.796657 | 0.576192 | 1.119978 | 0.394066 |
#月频数据——(HSCL,SPCL)
monthly_2_df = pd.DataFrame()
monthly_2_df['F_1'] = get_G_results(m_HS300_df_1['R_CL'], m_SP500_df_1['R_CL'], 5)['F']
monthly_2_df['P_1'] = get_G_results(m_HS300_df_1['R_CL'], m_SP500_df_1['R_CL'], 5)['P']
monthly_2_df['F_2'] = get_G_results(m_HS300_df_2['R_CL'], m_SP500_df_2['R_CL'], 5)['F']
monthly_2_df['P_2'] = get_G_results(m_HS300_df_2['R_CL'], m_SP500_df_2['R_CL'], 5)['P']
monthly_2_df['F_3'] = get_G_results(m_HS300_df_3['R_CL'], m_SP500_df_3['R_CL'], 5)['F']
monthly_2_df['P_3'] = get_G_results(m_HS300_df_3['R_CL'], m_SP500_df_3['R_CL'], 5)['P']
monthly_2_df['F_4'] = get_G_results(m_HS300_df_4['R_CL'], m_SP500_df_4['R_CL'], 5)['F']
monthly_2_df['P_4'] = get_G_results(m_HS300_df_4['R_CL'], m_SP500_df_4['R_CL'], 5)['P']
monthly_2_df
Granger Causality number of lags (no zero) 1 ssr based F test: F=0.2790 , p=0.6022 , df_denom=24, df_num=1 ssr based chi2 test: chi2=0.3138 , p=0.5753 , df=1 likelihood ratio test: chi2=0.3120 , p=0.5764 , df=1 parameter F test: F=0.2790 , p=0.6022 , df_denom=24, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.2645 , p=0.7701 , df_denom=21, df_num=2 ssr based chi2 test: chi2=0.6550 , p=0.7207 , df=2 likelihood ratio test: chi2=0.6468 , p=0.7237 , df=2 parameter F test: F=0.2645 , p=0.7701 , df_denom=21, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.1337 , p=0.9387 , df_denom=18, df_num=3 ssr based chi2 test: chi2=0.5572 , p=0.9062 , df=3 likelihood ratio test: chi2=0.5511 , p=0.9075 , df=3 parameter F test: F=0.1337 , p=0.9387 , df_denom=18, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.1483 , p=0.9609 , df_denom=15, df_num=4 ssr based chi2 test: chi2=0.9494 , p=0.9174 , df=4 likelihood ratio test: chi2=0.9311 , p=0.9201 , df=4 parameter F test: F=0.1483 , p=0.9609 , df_denom=15, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.3045 , p=0.9009 , df_denom=12, df_num=5 ssr based chi2 test: chi2=2.9181 , p=0.7126 , df=5 likelihood ratio test: chi2=2.7473 , p=0.7389 , df=5 parameter F test: F=0.3045 , p=0.9009 , df_denom=12, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.2790 , p=0.6022 , df_denom=24, df_num=1 ssr based chi2 test: chi2=0.3138 , p=0.5753 , df=1 likelihood ratio test: chi2=0.3120 , p=0.5764 , df=1 parameter F test: F=0.2790 , p=0.6022 , df_denom=24, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.2645 , p=0.7701 , df_denom=21, df_num=2 ssr based chi2 test: chi2=0.6550 , p=0.7207 , df=2 likelihood ratio test: chi2=0.6468 , p=0.7237 , df=2 parameter F test: F=0.2645 , p=0.7701 , df_denom=21, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.1337 , p=0.9387 , df_denom=18, df_num=3 ssr based chi2 test: chi2=0.5572 , p=0.9062 , df=3 likelihood ratio test: chi2=0.5511 , p=0.9075 , df=3 parameter F test: F=0.1337 , p=0.9387 , df_denom=18, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.1483 , p=0.9609 , df_denom=15, df_num=4 ssr based chi2 test: chi2=0.9494 , p=0.9174 , df=4 likelihood ratio test: chi2=0.9311 , p=0.9201 , df=4 parameter F test: F=0.1483 , p=0.9609 , df_denom=15, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.3045 , p=0.9009 , df_denom=12, df_num=5 ssr based chi2 test: chi2=2.9181 , p=0.7126 , df=5 likelihood ratio test: chi2=2.7473 , p=0.7389 , df=5 parameter F test: F=0.3045 , p=0.9009 , df_denom=12, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=1.6605 , p=0.2012 , df_denom=82, df_num=1 ssr based chi2 test: chi2=1.7212 , p=0.1895 , df=1 likelihood ratio test: chi2=1.7040 , p=0.1918 , df=1 parameter F test: F=1.6605 , p=0.2012 , df_denom=82, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.8824 , p=0.4178 , df_denom=79, df_num=2 ssr based chi2 test: chi2=1.8764 , p=0.3913 , df=2 likelihood ratio test: chi2=1.8558 , p=0.3954 , df=2 parameter F test: F=0.8824 , p=0.4178 , df_denom=79, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.7244 , p=0.5405 , df_denom=76, df_num=3 ssr based chi2 test: chi2=2.3732 , p=0.4986 , df=3 likelihood ratio test: chi2=2.3400 , p=0.5049 , df=3 parameter F test: F=0.7244 , p=0.5405 , df_denom=76, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.5722 , p=0.6836 , df_denom=73, df_num=4 ssr based chi2 test: chi2=2.5712 , p=0.6319 , df=4 likelihood ratio test: chi2=2.5317 , p=0.6390 , df=4 parameter F test: F=0.5722 , p=0.6836 , df_denom=73, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.5663 , p=0.7255 , df_denom=70, df_num=5 ssr based chi2 test: chi2=3.2764 , p=0.6575 , df=5 likelihood ratio test: chi2=3.2119 , p=0.6674 , df=5 parameter F test: F=0.5663 , p=0.7255 , df_denom=70, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=1.6605 , p=0.2012 , df_denom=82, df_num=1 ssr based chi2 test: chi2=1.7212 , p=0.1895 , df=1 likelihood ratio test: chi2=1.7040 , p=0.1918 , df=1 parameter F test: F=1.6605 , p=0.2012 , df_denom=82, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.8824 , p=0.4178 , df_denom=79, df_num=2 ssr based chi2 test: chi2=1.8764 , p=0.3913 , df=2 likelihood ratio test: chi2=1.8558 , p=0.3954 , df=2 parameter F test: F=0.8824 , p=0.4178 , df_denom=79, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.7244 , p=0.5405 , df_denom=76, df_num=3 ssr based chi2 test: chi2=2.3732 , p=0.4986 , df=3 likelihood ratio test: chi2=2.3400 , p=0.5049 , df=3 parameter F test: F=0.7244 , p=0.5405 , df_denom=76, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.5722 , p=0.6836 , df_denom=73, df_num=4 ssr based chi2 test: chi2=2.5712 , p=0.6319 , df=4 likelihood ratio test: chi2=2.5317 , p=0.6390 , df=4 parameter F test: F=0.5722 , p=0.6836 , df_denom=73, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.5663 , p=0.7255 , df_denom=70, df_num=5 ssr based chi2 test: chi2=3.2764 , p=0.6575 , df=5 likelihood ratio test: chi2=3.2119 , p=0.6674 , df=5 parameter F test: F=0.5663 , p=0.7255 , df_denom=70, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.0003 , p=0.9864 , df_denom=22, df_num=1 ssr based chi2 test: chi2=0.0003 , p=0.9853 , df=1 likelihood ratio test: chi2=0.0003 , p=0.9853 , df=1 parameter F test: F=0.0003 , p=0.9864 , df_denom=22, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.0837 , p=0.9201 , df_denom=19, df_num=2 ssr based chi2 test: chi2=0.2113 , p=0.8997 , df=2 likelihood ratio test: chi2=0.2104 , p=0.9001 , df=2 parameter F test: F=0.0837 , p=0.9201 , df_denom=19, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.2527 , p=0.8583 , df_denom=16, df_num=3 ssr based chi2 test: chi2=1.0896 , p=0.7796 , df=3 likelihood ratio test: chi2=1.0646 , p=0.7856 , df=3 parameter F test: F=0.2527 , p=0.8583 , df_denom=16, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.7637 , p=0.5673 , df_denom=13, df_num=4 ssr based chi2 test: chi2=5.1700 , p=0.2703 , df=4 likelihood ratio test: chi2=4.6436 , p=0.3259 , df=4 parameter F test: F=0.7637 , p=0.5673 , df_denom=13, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.5119 , p=0.7619 , df_denom=10, df_num=5 ssr based chi2 test: chi2=5.3746 , p=0.3719 , df=5 likelihood ratio test: chi2=4.7854 , p=0.4426 , df=5 parameter F test: F=0.5119 , p=0.7619 , df_denom=10, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.0003 , p=0.9864 , df_denom=22, df_num=1 ssr based chi2 test: chi2=0.0003 , p=0.9853 , df=1 likelihood ratio test: chi2=0.0003 , p=0.9853 , df=1 parameter F test: F=0.0003 , p=0.9864 , df_denom=22, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.0837 , p=0.9201 , df_denom=19, df_num=2 ssr based chi2 test: chi2=0.2113 , p=0.8997 , df=2 likelihood ratio test: chi2=0.2104 , p=0.9001 , df=2 parameter F test: F=0.0837 , p=0.9201 , df_denom=19, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.2527 , p=0.8583 , df_denom=16, df_num=3 ssr based chi2 test: chi2=1.0896 , p=0.7796 , df=3 likelihood ratio test: chi2=1.0646 , p=0.7856 , df=3 parameter F test: F=0.2527 , p=0.8583 , df_denom=16, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.7637 , p=0.5673 , df_denom=13, df_num=4 ssr based chi2 test: chi2=5.1700 , p=0.2703 , df=4 likelihood ratio test: chi2=4.6436 , p=0.3259 , df=4 parameter F test: F=0.7637 , p=0.5673 , df_denom=13, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.5119 , p=0.7619 , df_denom=10, df_num=5 ssr based chi2 test: chi2=5.3746 , p=0.3719 , df=5 likelihood ratio test: chi2=4.7854 , p=0.4426 , df=5 parameter F test: F=0.5119 , p=0.7619 , df_denom=10, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.4551 , p=0.5059 , df_denom=26, df_num=1 ssr based chi2 test: chi2=0.5076 , p=0.4762 , df=1 likelihood ratio test: chi2=0.5032 , p=0.4781 , df=1 parameter F test: F=0.4551 , p=0.5059 , df_denom=26, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=1.3878 , p=0.2697 , df_denom=23, df_num=2 ssr based chi2 test: chi2=3.3791 , p=0.1846 , df=2 likelihood ratio test: chi2=3.1902 , p=0.2029 , df=2 parameter F test: F=1.3878 , p=0.2697 , df_denom=23, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=3.6339 , p=0.0306 , df_denom=20, df_num=3 ssr based chi2 test: chi2=14.7173 , p=0.0021 , df=3 likelihood ratio test: chi2=11.7472 , p=0.0083 , df=3 parameter F test: F=3.6339 , p=0.0306 , df_denom=20, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=2.5733 , p=0.0752 , df_denom=17, df_num=4 ssr based chi2 test: chi2=15.7427 , p=0.0034 , df=4 likelihood ratio test: chi2=12.3091 , p=0.0152 , df=4 parameter F test: F=2.5733 , p=0.0752 , df_denom=17, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=3.2035 , p=0.0390 , df_denom=14, df_num=5 ssr based chi2 test: chi2=28.6030 , p=0.0000 , df=5 likelihood ratio test: chi2=19.0683 , p=0.0019 , df=5 parameter F test: F=3.2035 , p=0.0390 , df_denom=14, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.4551 , p=0.5059 , df_denom=26, df_num=1 ssr based chi2 test: chi2=0.5076 , p=0.4762 , df=1 likelihood ratio test: chi2=0.5032 , p=0.4781 , df=1 parameter F test: F=0.4551 , p=0.5059 , df_denom=26, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=1.3878 , p=0.2697 , df_denom=23, df_num=2 ssr based chi2 test: chi2=3.3791 , p=0.1846 , df=2 likelihood ratio test: chi2=3.1902 , p=0.2029 , df=2 parameter F test: F=1.3878 , p=0.2697 , df_denom=23, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=3.6339 , p=0.0306 , df_denom=20, df_num=3 ssr based chi2 test: chi2=14.7173 , p=0.0021 , df=3 likelihood ratio test: chi2=11.7472 , p=0.0083 , df=3 parameter F test: F=3.6339 , p=0.0306 , df_denom=20, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=2.5733 , p=0.0752 , df_denom=17, df_num=4 ssr based chi2 test: chi2=15.7427 , p=0.0034 , df=4 likelihood ratio test: chi2=12.3091 , p=0.0152 , df=4 parameter F test: F=2.5733 , p=0.0752 , df_denom=17, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=3.2035 , p=0.0390 , df_denom=14, df_num=5 ssr based chi2 test: chi2=28.6030 , p=0.0000 , df=5 likelihood ratio test: chi2=19.0683 , p=0.0019 , df=5 parameter F test: F=3.2035 , p=0.0390 , df_denom=14, df_num=5
| F_1 | P_1 | F_2 | P_2 | F_3 | P_3 | F_4 | P_4 | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.278964 | 0.602231 | 1.660461 | 0.201165 | 0.000299 | 0.986368 | 0.455052 | 0.505900 |
| 1 | 0.264502 | 0.770107 | 0.882358 | 0.417844 | 0.083658 | 0.920083 | 1.387843 | 0.269744 |
| 2 | 0.133732 | 0.938680 | 0.724365 | 0.540549 | 0.252661 | 0.858284 | 3.633909 | 0.030555 |
| 3 | 0.148342 | 0.960885 | 0.572242 | 0.683610 | 0.763749 | 0.567284 | 2.573321 | 0.075193 |
| 4 | 0.304500 | 0.900886 | 0.566291 | 0.725485 | 0.511865 | 0.761867 | 3.203541 | 0.039029 |
#月频数据——(SPOP,HSCL)
monthly_3_df = pd.DataFrame()
monthly_3_df['F_1'] = get_G_results(m_SP500_df_1['R_OP'], m_HS300_df_1['R_CL'], 5)['F']
monthly_3_df['P_1'] = get_G_results(m_SP500_df_1['R_OP'], m_HS300_df_1['R_CL'], 5)['P']
monthly_3_df['F_2'] = get_G_results(m_SP500_df_2['R_OP'], m_HS300_df_2['R_CL'], 5)['F']
monthly_3_df['P_2'] = get_G_results(m_SP500_df_2['R_OP'], m_HS300_df_2['R_CL'], 5)['P']
monthly_3_df['F_3'] = get_G_results(m_SP500_df_3['R_OP'], m_HS300_df_3['R_CL'], 5)['F']
monthly_3_df['P_3'] = get_G_results(m_SP500_df_3['R_OP'], m_HS300_df_3['R_CL'], 5)['P']
monthly_3_df['F_4'] = get_G_results(m_SP500_df_4['R_OP'], m_HS300_df_4['R_CL'], 5)['F']
monthly_3_df['P_4'] = get_G_results(m_SP500_df_4['R_OP'], m_HS300_df_4['R_CL'], 5)['P']
monthly_3_df
Granger Causality number of lags (no zero) 1 ssr based F test: F=0.2411 , p=0.6279 , df_denom=24, df_num=1 ssr based chi2 test: chi2=0.2712 , p=0.6025 , df=1 likelihood ratio test: chi2=0.2699 , p=0.6034 , df=1 parameter F test: F=0.2411 , p=0.6279 , df_denom=24, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=1.9093 , p=0.1730 , df_denom=21, df_num=2 ssr based chi2 test: chi2=4.7279 , p=0.0940 , df=2 likelihood ratio test: chi2=4.3439 , p=0.1140 , df=2 parameter F test: F=1.9093 , p=0.1730 , df_denom=21, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=3.3619 , p=0.0417 , df_denom=18, df_num=3 ssr based chi2 test: chi2=14.0081 , p=0.0029 , df=3 likelihood ratio test: chi2=11.1223 , p=0.0111 , df=3 parameter F test: F=3.3619 , p=0.0417 , df_denom=18, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=3.4910 , p=0.0332 , df_denom=15, df_num=4 ssr based chi2 test: chi2=22.3424 , p=0.0002 , df=4 likelihood ratio test: chi2=15.7921 , p=0.0033 , df=4 parameter F test: F=3.4910 , p=0.0332 , df_denom=15, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=1.6497 , p=0.2210 , df_denom=12, df_num=5 ssr based chi2 test: chi2=15.8100 , p=0.0074 , df=5 likelihood ratio test: chi2=12.0332 , p=0.0343 , df=5 parameter F test: F=1.6497 , p=0.2210 , df_denom=12, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.2411 , p=0.6279 , df_denom=24, df_num=1 ssr based chi2 test: chi2=0.2712 , p=0.6025 , df=1 likelihood ratio test: chi2=0.2699 , p=0.6034 , df=1 parameter F test: F=0.2411 , p=0.6279 , df_denom=24, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=1.9093 , p=0.1730 , df_denom=21, df_num=2 ssr based chi2 test: chi2=4.7279 , p=0.0940 , df=2 likelihood ratio test: chi2=4.3439 , p=0.1140 , df=2 parameter F test: F=1.9093 , p=0.1730 , df_denom=21, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=3.3619 , p=0.0417 , df_denom=18, df_num=3 ssr based chi2 test: chi2=14.0081 , p=0.0029 , df=3 likelihood ratio test: chi2=11.1223 , p=0.0111 , df=3 parameter F test: F=3.3619 , p=0.0417 , df_denom=18, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=3.4910 , p=0.0332 , df_denom=15, df_num=4 ssr based chi2 test: chi2=22.3424 , p=0.0002 , df=4 likelihood ratio test: chi2=15.7921 , p=0.0033 , df=4 parameter F test: F=3.4910 , p=0.0332 , df_denom=15, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=1.6497 , p=0.2210 , df_denom=12, df_num=5 ssr based chi2 test: chi2=15.8100 , p=0.0074 , df=5 likelihood ratio test: chi2=12.0332 , p=0.0343 , df=5 parameter F test: F=1.6497 , p=0.2210 , df_denom=12, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.0011 , p=0.9736 , df_denom=82, df_num=1 ssr based chi2 test: chi2=0.0011 , p=0.9730 , df=1 likelihood ratio test: chi2=0.0011 , p=0.9730 , df=1 parameter F test: F=0.0011 , p=0.9736 , df_denom=82, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.0570 , p=0.9446 , df_denom=79, df_num=2 ssr based chi2 test: chi2=0.1213 , p=0.9412 , df=2 likelihood ratio test: chi2=0.1212 , p=0.9412 , df=2 parameter F test: F=0.0570 , p=0.9446 , df_denom=79, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=1.1057 , p=0.3521 , df_denom=76, df_num=3 ssr based chi2 test: chi2=3.6226 , p=0.3052 , df=3 likelihood ratio test: chi2=3.5458 , p=0.3149 , df=3 parameter F test: F=1.1057 , p=0.3521 , df_denom=76, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.8494 , p=0.4986 , df_denom=73, df_num=4 ssr based chi2 test: chi2=3.8165 , p=0.4314 , df=4 likelihood ratio test: chi2=3.7304 , p=0.4437 , df=4 parameter F test: F=0.8494 , p=0.4986 , df_denom=73, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.8598 , p=0.5125 , df_denom=70, df_num=5 ssr based chi2 test: chi2=4.9748 , p=0.4190 , df=5 likelihood ratio test: chi2=4.8280 , p=0.4372 , df=5 parameter F test: F=0.8598 , p=0.5125 , df_denom=70, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.0011 , p=0.9736 , df_denom=82, df_num=1 ssr based chi2 test: chi2=0.0011 , p=0.9730 , df=1 likelihood ratio test: chi2=0.0011 , p=0.9730 , df=1 parameter F test: F=0.0011 , p=0.9736 , df_denom=82, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.0570 , p=0.9446 , df_denom=79, df_num=2 ssr based chi2 test: chi2=0.1213 , p=0.9412 , df=2 likelihood ratio test: chi2=0.1212 , p=0.9412 , df=2 parameter F test: F=0.0570 , p=0.9446 , df_denom=79, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=1.1057 , p=0.3521 , df_denom=76, df_num=3 ssr based chi2 test: chi2=3.6226 , p=0.3052 , df=3 likelihood ratio test: chi2=3.5458 , p=0.3149 , df=3 parameter F test: F=1.1057 , p=0.3521 , df_denom=76, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.8494 , p=0.4986 , df_denom=73, df_num=4 ssr based chi2 test: chi2=3.8165 , p=0.4314 , df=4 likelihood ratio test: chi2=3.7304 , p=0.4437 , df=4 parameter F test: F=0.8494 , p=0.4986 , df_denom=73, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.8598 , p=0.5125 , df_denom=70, df_num=5 ssr based chi2 test: chi2=4.9748 , p=0.4190 , df=5 likelihood ratio test: chi2=4.8280 , p=0.4372 , df=5 parameter F test: F=0.8598 , p=0.5125 , df_denom=70, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=1.5830 , p=0.2215 , df_denom=22, df_num=1 ssr based chi2 test: chi2=1.7989 , p=0.1798 , df=1 likelihood ratio test: chi2=1.7371 , p=0.1875 , df=1 parameter F test: F=1.5830 , p=0.2215 , df_denom=22, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=1.2777 , p=0.3016 , df_denom=19, df_num=2 ssr based chi2 test: chi2=3.2278 , p=0.1991 , df=2 likelihood ratio test: chi2=3.0284 , p=0.2200 , df=2 parameter F test: F=1.2777 , p=0.3016 , df_denom=19, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=1.1034 , p=0.3766 , df_denom=16, df_num=3 ssr based chi2 test: chi2=4.7584 , p=0.1904 , df=3 likelihood ratio test: chi2=4.3250 , p=0.2284 , df=3 parameter F test: F=1.1034 , p=0.3766 , df_denom=16, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=1.2558 , p=0.3363 , df_denom=13, df_num=4 ssr based chi2 test: chi2=8.5008 , p=0.0749 , df=4 likelihood ratio test: chi2=7.1876 , p=0.1263 , df=4 parameter F test: F=1.2558 , p=0.3363 , df_denom=13, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=3.3025 , p=0.0510 , df_denom=10, df_num=5 ssr based chi2 test: chi2=34.6764 , p=0.0000 , df=5 likelihood ratio test: chi2=20.4757 , p=0.0010 , df=5 parameter F test: F=3.3025 , p=0.0510 , df_denom=10, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=1.5830 , p=0.2215 , df_denom=22, df_num=1 ssr based chi2 test: chi2=1.7989 , p=0.1798 , df=1 likelihood ratio test: chi2=1.7371 , p=0.1875 , df=1 parameter F test: F=1.5830 , p=0.2215 , df_denom=22, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=1.2777 , p=0.3016 , df_denom=19, df_num=2 ssr based chi2 test: chi2=3.2278 , p=0.1991 , df=2 likelihood ratio test: chi2=3.0284 , p=0.2200 , df=2 parameter F test: F=1.2777 , p=0.3016 , df_denom=19, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=1.1034 , p=0.3766 , df_denom=16, df_num=3 ssr based chi2 test: chi2=4.7584 , p=0.1904 , df=3 likelihood ratio test: chi2=4.3250 , p=0.2284 , df=3 parameter F test: F=1.1034 , p=0.3766 , df_denom=16, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=1.2558 , p=0.3363 , df_denom=13, df_num=4 ssr based chi2 test: chi2=8.5008 , p=0.0749 , df=4 likelihood ratio test: chi2=7.1876 , p=0.1263 , df=4 parameter F test: F=1.2558 , p=0.3363 , df_denom=13, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=3.3025 , p=0.0510 , df_denom=10, df_num=5 ssr based chi2 test: chi2=34.6764 , p=0.0000 , df=5 likelihood ratio test: chi2=20.4757 , p=0.0010 , df=5 parameter F test: F=3.3025 , p=0.0510 , df_denom=10, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=1.3130 , p=0.2623 , df_denom=26, df_num=1 ssr based chi2 test: chi2=1.4645 , p=0.2262 , df=1 likelihood ratio test: chi2=1.4287 , p=0.2320 , df=1 parameter F test: F=1.3130 , p=0.2623 , df_denom=26, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.8508 , p=0.4401 , df_denom=23, df_num=2 ssr based chi2 test: chi2=2.0715 , p=0.3550 , df=2 likelihood ratio test: chi2=1.9985 , p=0.3682 , df=2 parameter F test: F=0.8508 , p=0.4401 , df_denom=23, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.9233 , p=0.4476 , df_denom=20, df_num=3 ssr based chi2 test: chi2=3.7393 , p=0.2910 , df=3 likelihood ratio test: chi2=3.5021 , p=0.3205 , df=3 parameter F test: F=0.9233 , p=0.4476 , df_denom=20, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=1.0571 , p=0.4076 , df_denom=17, df_num=4 ssr based chi2 test: chi2=6.4672 , p=0.1669 , df=4 likelihood ratio test: chi2=5.7754 , p=0.2166 , df=4 parameter F test: F=1.0571 , p=0.4076 , df_denom=17, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.9566 , p=0.4761 , df_denom=14, df_num=5 ssr based chi2 test: chi2=8.5412 , p=0.1288 , df=5 likelihood ratio test: chi2=7.3475 , p=0.1961 , df=5 parameter F test: F=0.9566 , p=0.4761 , df_denom=14, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=1.3130 , p=0.2623 , df_denom=26, df_num=1 ssr based chi2 test: chi2=1.4645 , p=0.2262 , df=1 likelihood ratio test: chi2=1.4287 , p=0.2320 , df=1 parameter F test: F=1.3130 , p=0.2623 , df_denom=26, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.8508 , p=0.4401 , df_denom=23, df_num=2 ssr based chi2 test: chi2=2.0715 , p=0.3550 , df=2 likelihood ratio test: chi2=1.9985 , p=0.3682 , df=2 parameter F test: F=0.8508 , p=0.4401 , df_denom=23, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.9233 , p=0.4476 , df_denom=20, df_num=3 ssr based chi2 test: chi2=3.7393 , p=0.2910 , df=3 likelihood ratio test: chi2=3.5021 , p=0.3205 , df=3 parameter F test: F=0.9233 , p=0.4476 , df_denom=20, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=1.0571 , p=0.4076 , df_denom=17, df_num=4 ssr based chi2 test: chi2=6.4672 , p=0.1669 , df=4 likelihood ratio test: chi2=5.7754 , p=0.2166 , df=4 parameter F test: F=1.0571 , p=0.4076 , df_denom=17, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=0.9566 , p=0.4761 , df_denom=14, df_num=5 ssr based chi2 test: chi2=8.5412 , p=0.1288 , df=5 likelihood ratio test: chi2=7.3475 , p=0.1961 , df=5 parameter F test: F=0.9566 , p=0.4761 , df_denom=14, df_num=5
| F_1 | P_1 | F_2 | P_2 | F_3 | P_3 | F_4 | P_4 | |
|---|---|---|---|---|---|---|---|---|
| 0 | 0.241103 | 0.627871 | 0.001104 | 0.973576 | 1.583046 | 0.221513 | 1.312992 | 0.262291 |
| 1 | 1.909332 | 0.173033 | 0.057033 | 0.944602 | 1.277661 | 0.301572 | 0.850808 | 0.440077 |
| 2 | 3.361936 | 0.041728 | 1.105691 | 0.352137 | 1.103386 | 0.376633 | 0.923293 | 0.447591 |
| 3 | 3.490997 | 0.033189 | 0.849409 | 0.498551 | 1.255795 | 0.336264 | 1.057131 | 0.407618 |
| 4 | 1.649738 | 0.221017 | 0.859841 | 0.512540 | 3.302511 | 0.050957 | 0.956616 | 0.476142 |
#月频数据——(SPCL,HSCL)
monthly_4_df = pd.DataFrame()
monthly_4_df['F_1'] = get_G_results(m_SP500_df_1['R_CL'], m_HS300_df_1['R_CL'], 5)['F']
monthly_4_df['P_1'] = get_G_results(m_SP500_df_1['R_CL'], m_HS300_df_1['R_CL'], 5)['P']
monthly_4_df['F_2'] = get_G_results(m_SP500_df_2['R_CL'], m_HS300_df_2['R_CL'], 5)['F']
monthly_4_df['P_2'] = get_G_results(m_SP500_df_2['R_CL'], m_HS300_df_2['R_CL'], 5)['P']
monthly_4_df['F_3'] = get_G_results(m_SP500_df_3['R_CL'], m_HS300_df_3['R_CL'], 5)['F']
monthly_4_df['P_3'] = get_G_results(m_SP500_df_3['R_CL'], m_HS300_df_3['R_CL'], 5)['P']
monthly_4_df['F_4'] = get_G_results(m_SP500_df_4['R_CL'], m_HS300_df_4['R_CL'], 5)['F']
monthly_4_df['P_4'] = get_G_results(m_SP500_df_4['R_CL'], m_HS300_df_4['R_CL'], 5)['P']
monthly_4_df
Granger Causality number of lags (no zero) 1 ssr based F test: F=1.2226 , p=0.2798 , df_denom=24, df_num=1 ssr based chi2 test: chi2=1.3754 , p=0.2409 , df=1 likelihood ratio test: chi2=1.3416 , p=0.2468 , df=1 parameter F test: F=1.2226 , p=0.2798 , df_denom=24, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=1.1625 , p=0.3320 , df_denom=21, df_num=2 ssr based chi2 test: chi2=2.8786 , p=0.2371 , df=2 likelihood ratio test: chi2=2.7301 , p=0.2554 , df=2 parameter F test: F=1.1625 , p=0.3320 , df_denom=21, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.6649 , p=0.5844 , df_denom=18, df_num=3 ssr based chi2 test: chi2=2.7702 , p=0.4284 , df=3 likelihood ratio test: chi2=2.6272 , p=0.4527 , df=3 parameter F test: F=0.6649 , p=0.5844 , df_denom=18, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.9672 , p=0.4540 , df_denom=15, df_num=4 ssr based chi2 test: chi2=6.1902 , p=0.1854 , df=4 likelihood ratio test: chi2=5.5072 , p=0.2391 , df=4 parameter F test: F=0.9672 , p=0.4540 , df_denom=15, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=1.0301 , p=0.4431 , df_denom=12, df_num=5 ssr based chi2 test: chi2=9.8719 , p=0.0789 , df=5 likelihood ratio test: chi2=8.2138 , p=0.1448 , df=5 parameter F test: F=1.0301 , p=0.4431 , df_denom=12, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=1.2226 , p=0.2798 , df_denom=24, df_num=1 ssr based chi2 test: chi2=1.3754 , p=0.2409 , df=1 likelihood ratio test: chi2=1.3416 , p=0.2468 , df=1 parameter F test: F=1.2226 , p=0.2798 , df_denom=24, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=1.1625 , p=0.3320 , df_denom=21, df_num=2 ssr based chi2 test: chi2=2.8786 , p=0.2371 , df=2 likelihood ratio test: chi2=2.7301 , p=0.2554 , df=2 parameter F test: F=1.1625 , p=0.3320 , df_denom=21, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=0.6649 , p=0.5844 , df_denom=18, df_num=3 ssr based chi2 test: chi2=2.7702 , p=0.4284 , df=3 likelihood ratio test: chi2=2.6272 , p=0.4527 , df=3 parameter F test: F=0.6649 , p=0.5844 , df_denom=18, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.9672 , p=0.4540 , df_denom=15, df_num=4 ssr based chi2 test: chi2=6.1902 , p=0.1854 , df=4 likelihood ratio test: chi2=5.5072 , p=0.2391 , df=4 parameter F test: F=0.9672 , p=0.4540 , df_denom=15, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=1.0301 , p=0.4431 , df_denom=12, df_num=5 ssr based chi2 test: chi2=9.8719 , p=0.0789 , df=5 likelihood ratio test: chi2=8.2138 , p=0.1448 , df=5 parameter F test: F=1.0301 , p=0.4431 , df_denom=12, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=1.9780 , p=0.1634 , df_denom=82, df_num=1 ssr based chi2 test: chi2=2.0504 , p=0.1522 , df=1 likelihood ratio test: chi2=2.0260 , p=0.1546 , df=1 parameter F test: F=1.9780 , p=0.1634 , df_denom=82, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=1.1344 , p=0.3268 , df_denom=79, df_num=2 ssr based chi2 test: chi2=2.4123 , p=0.2993 , df=2 likelihood ratio test: chi2=2.3783 , p=0.3045 , df=2 parameter F test: F=1.1344 , p=0.3268 , df_denom=79, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=1.0698 , p=0.3670 , df_denom=76, df_num=3 ssr based chi2 test: chi2=3.5051 , p=0.3201 , df=3 likelihood ratio test: chi2=3.4331 , p=0.3295 , df=3 parameter F test: F=1.0698 , p=0.3670 , df_denom=76, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.8604 , p=0.4919 , df_denom=73, df_num=4 ssr based chi2 test: chi2=3.8659 , p=0.4245 , df=4 likelihood ratio test: chi2=3.7776 , p=0.4369 , df=4 parameter F test: F=0.8604 , p=0.4919 , df_denom=73, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=2.0001 , p=0.0892 , df_denom=70, df_num=5 ssr based chi2 test: chi2=11.5723 , p=0.0411 , df=5 likelihood ratio test: chi2=10.8168 , p=0.0551 , df=5 parameter F test: F=2.0001 , p=0.0892 , df_denom=70, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=1.9780 , p=0.1634 , df_denom=82, df_num=1 ssr based chi2 test: chi2=2.0504 , p=0.1522 , df=1 likelihood ratio test: chi2=2.0260 , p=0.1546 , df=1 parameter F test: F=1.9780 , p=0.1634 , df_denom=82, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=1.1344 , p=0.3268 , df_denom=79, df_num=2 ssr based chi2 test: chi2=2.4123 , p=0.2993 , df=2 likelihood ratio test: chi2=2.3783 , p=0.3045 , df=2 parameter F test: F=1.1344 , p=0.3268 , df_denom=79, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=1.0698 , p=0.3670 , df_denom=76, df_num=3 ssr based chi2 test: chi2=3.5051 , p=0.3201 , df=3 likelihood ratio test: chi2=3.4331 , p=0.3295 , df=3 parameter F test: F=1.0698 , p=0.3670 , df_denom=76, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.8604 , p=0.4919 , df_denom=73, df_num=4 ssr based chi2 test: chi2=3.8659 , p=0.4245 , df=4 likelihood ratio test: chi2=3.7776 , p=0.4369 , df=4 parameter F test: F=0.8604 , p=0.4919 , df_denom=73, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=2.0001 , p=0.0892 , df_denom=70, df_num=5 ssr based chi2 test: chi2=11.5723 , p=0.0411 , df=5 likelihood ratio test: chi2=10.8168 , p=0.0551 , df=5 parameter F test: F=2.0001 , p=0.0892 , df_denom=70, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.0065 , p=0.9364 , df_denom=22, df_num=1 ssr based chi2 test: chi2=0.0074 , p=0.9314 , df=1 likelihood ratio test: chi2=0.0074 , p=0.9314 , df=1 parameter F test: F=0.0065 , p=0.9364 , df_denom=22, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.0166 , p=0.9835 , df_denom=19, df_num=2 ssr based chi2 test: chi2=0.0420 , p=0.9792 , df=2 likelihood ratio test: chi2=0.0419 , p=0.9792 , df=2 parameter F test: F=0.0166 , p=0.9835 , df_denom=19, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=1.1582 , p=0.3563 , df_denom=16, df_num=3 ssr based chi2 test: chi2=4.9947 , p=0.1722 , df=3 likelihood ratio test: chi2=4.5200 , p=0.2105 , df=3 parameter F test: F=1.1582 , p=0.3563 , df_denom=16, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.6380 , p=0.6446 , df_denom=13, df_num=4 ssr based chi2 test: chi2=4.3189 , p=0.3646 , df=4 likelihood ratio test: chi2=3.9434 , p=0.4137 , df=4 parameter F test: F=0.6380 , p=0.6446 , df_denom=13, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=1.6451 , p=0.2350 , df_denom=10, df_num=5 ssr based chi2 test: chi2=17.2736 , p=0.0040 , df=5 likelihood ratio test: chi2=12.6050 , p=0.0274 , df=5 parameter F test: F=1.6451 , p=0.2350 , df_denom=10, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.0065 , p=0.9364 , df_denom=22, df_num=1 ssr based chi2 test: chi2=0.0074 , p=0.9314 , df=1 likelihood ratio test: chi2=0.0074 , p=0.9314 , df=1 parameter F test: F=0.0065 , p=0.9364 , df_denom=22, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.0166 , p=0.9835 , df_denom=19, df_num=2 ssr based chi2 test: chi2=0.0420 , p=0.9792 , df=2 likelihood ratio test: chi2=0.0419 , p=0.9792 , df=2 parameter F test: F=0.0166 , p=0.9835 , df_denom=19, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=1.1582 , p=0.3563 , df_denom=16, df_num=3 ssr based chi2 test: chi2=4.9947 , p=0.1722 , df=3 likelihood ratio test: chi2=4.5200 , p=0.2105 , df=3 parameter F test: F=1.1582 , p=0.3563 , df_denom=16, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=0.6380 , p=0.6446 , df_denom=13, df_num=4 ssr based chi2 test: chi2=4.3189 , p=0.3646 , df=4 likelihood ratio test: chi2=3.9434 , p=0.4137 , df=4 parameter F test: F=0.6380 , p=0.6446 , df_denom=13, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=1.6451 , p=0.2350 , df_denom=10, df_num=5 ssr based chi2 test: chi2=17.2736 , p=0.0040 , df=5 likelihood ratio test: chi2=12.6050 , p=0.0274 , df=5 parameter F test: F=1.6451 , p=0.2350 , df_denom=10, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.1135 , p=0.7389 , df_denom=26, df_num=1 ssr based chi2 test: chi2=0.1266 , p=0.7220 , df=1 likelihood ratio test: chi2=0.1263 , p=0.7223 , df=1 parameter F test: F=0.1135 , p=0.7389 , df_denom=26, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.1120 , p=0.8945 , df_denom=23, df_num=2 ssr based chi2 test: chi2=0.2727 , p=0.8725 , df=2 likelihood ratio test: chi2=0.2714 , p=0.8731 , df=2 parameter F test: F=0.1120 , p=0.8945 , df_denom=23, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=2.4920 , p=0.0895 , df_denom=20, df_num=3 ssr based chi2 test: chi2=10.0928 , p=0.0178 , df=3 likelihood ratio test: chi2=8.5748 , p=0.0355 , df=3 parameter F test: F=2.4920 , p=0.0895 , df_denom=20, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=1.7493 , p=0.1857 , df_denom=17, df_num=4 ssr based chi2 test: chi2=10.7019 , p=0.0301 , df=4 likelihood ratio test: chi2=8.9630 , p=0.0620 , df=4 parameter F test: F=1.7493 , p=0.1857 , df_denom=17, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=1.2195 , p=0.3507 , df_denom=14, df_num=5 ssr based chi2 test: chi2=10.8880 , p=0.0536 , df=5 likelihood ratio test: chi2=9.0382 , p=0.1076 , df=5 parameter F test: F=1.2195 , p=0.3507 , df_denom=14, df_num=5 Granger Causality number of lags (no zero) 1 ssr based F test: F=0.1135 , p=0.7389 , df_denom=26, df_num=1 ssr based chi2 test: chi2=0.1266 , p=0.7220 , df=1 likelihood ratio test: chi2=0.1263 , p=0.7223 , df=1 parameter F test: F=0.1135 , p=0.7389 , df_denom=26, df_num=1 Granger Causality number of lags (no zero) 2 ssr based F test: F=0.1120 , p=0.8945 , df_denom=23, df_num=2 ssr based chi2 test: chi2=0.2727 , p=0.8725 , df=2 likelihood ratio test: chi2=0.2714 , p=0.8731 , df=2 parameter F test: F=0.1120 , p=0.8945 , df_denom=23, df_num=2 Granger Causality number of lags (no zero) 3 ssr based F test: F=2.4920 , p=0.0895 , df_denom=20, df_num=3 ssr based chi2 test: chi2=10.0928 , p=0.0178 , df=3 likelihood ratio test: chi2=8.5748 , p=0.0355 , df=3 parameter F test: F=2.4920 , p=0.0895 , df_denom=20, df_num=3 Granger Causality number of lags (no zero) 4 ssr based F test: F=1.7493 , p=0.1857 , df_denom=17, df_num=4 ssr based chi2 test: chi2=10.7019 , p=0.0301 , df=4 likelihood ratio test: chi2=8.9630 , p=0.0620 , df=4 parameter F test: F=1.7493 , p=0.1857 , df_denom=17, df_num=4 Granger Causality number of lags (no zero) 5 ssr based F test: F=1.2195 , p=0.3507 , df_denom=14, df_num=5 ssr based chi2 test: chi2=10.8880 , p=0.0536 , df=5 likelihood ratio test: chi2=9.0382 , p=0.1076 , df=5 parameter F test: F=1.2195 , p=0.3507 , df_denom=14, df_num=5
| F_1 | P_1 | F_2 | P_2 | F_3 | P_3 | F_4 | P_4 | |
|---|---|---|---|---|---|---|---|---|
| 0 | 1.222621 | 0.279808 | 1.977997 | 0.163380 | 0.006514 | 0.936403 | 0.113519 | 0.738878 |
| 1 | 1.162509 | 0.332026 | 1.134365 | 0.326808 | 0.016616 | 0.983535 | 0.112007 | 0.894523 |
| 2 | 0.664855 | 0.584427 | 1.069824 | 0.367017 | 1.158192 | 0.356293 | 2.492045 | 0.089541 |
| 3 | 0.967225 | 0.453988 | 0.860409 | 0.491919 | 0.638023 | 0.644571 | 1.749342 | 0.185703 |
| 4 | 1.030109 | 0.443054 | 2.000150 | 0.089226 | 1.645106 | 0.234988 | 1.219454 | 0.350664 |
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