from kuanke.wizard import
from jqdata import
import numpy as np
import pandas as pd
import talib
import datetime

初始化函数，设定要操作的股票、基准等等

def initialize(context):

# 设定基准
set_benchmark('000300.XSHG')
# 设定滑点
set_slippage(FixedSlippage(0.02))
# True为开启动态复权模式，使用真实价格交易
set_option('use_real_price', True)
# 设定成交量比例
set_option('order_volume_ratio', 1)
# 股票类交易手续费是：买入时佣金万分之三，卖出时佣金万分之三加千分之一印花税, 每笔交易佣金最低扣5块钱
set_order_cost(OrderCost(open_tax=0, close_tax=0.001, open_commission=0.0003, close_commission=0.0003, min_commission=5), type='stock')
# 个股最大持仓比重
g.security_max_proportion = 1
# 选股频率
g.check_stocks_refresh_rate = 22
# 买入频率
g.buy_refresh_rate = 1
# 卖出频率
g.sell_refresh_rate = 1
# 最大建仓数量
g.max_hold_stocknum = 30

# 选股频率计数器
g.check_stocks_days = 0
# 买卖交易频率计数器
g.buy_trade_days=0
g.sell_trade_days=0
# 获取未卖出的股票
g.open_sell_securities = []
# 卖出股票的dict
g.selled_security_list={}

# 股票筛选初始化函数
check_stocks_initialize()
# 股票筛选排序初始化函数
check_stocks_sort_initialize()
# 出场初始化函数
sell_initialize()
# 入场初始化函数
buy_initialize()
# 风控初始化函数
risk_management_initialize()

# 关闭提示
log.set_level('order', 'info')

# 运行函数
run_daily(sell_every_day,'open') #卖出未卖出成功的股票
run_daily(risk_management, 'every_bar') #风险控制
run_daily(check_stocks, 'open') #选股
run_daily(trade, 'open') #交易
run_daily(selled_security_list_count, 'after_close') #卖出股票日期计数

股票筛选初始化函数

def check_stocks_initialize():

# 是否过滤停盘
g.filter_paused = True
# 是否过滤退市
g.filter_delisted = True
# 是否只有ST
g.only_st = False
# 是否过滤ST
g.filter_st = True
# 股票池
g.security_universe_index = ["000300.XSHG","000905.XSHG"]
g.security_universe_user_securities = []
# 行业列表
g.industry_list = ["801010","801020","801030","801040","801050","801080","801110","801120","801130","801140","801150","801160","801170","801180","801200","801210","801230","801710","801720","801730","801740","801750","801760","801770","801780","801790","801880","801890"]
# 概念列表
g.concept_list = []

股票筛选排序初始化函数

def check_stocks_sort_initialize():

# 总排序准则： desc-降序、asc-升序
g.check_out_lists_ascending = 'desc'

出场初始化函数

def sell_initialize():

# 设定是否卖出buy_lists中的股票
g.sell_will_buy = False

# 固定出仓的数量或者百分比
g.sell_by_amount = None
g.sell_by_percent = None

入场初始化函数

def buy_initialize():

# 是否可重复买入
g.filter_holded = False

# 委托类型
g.order_style_str = 'by_cap_mean'
g.order_style_value = 100

风控初始化函数

def risk_management_initialize():

# 策略风控信号
g.risk_management_signal = True

# 策略当日触发风控清仓信号
g.daily_risk_management = True

# 单只最大买入股数或金额
g.max_buy_value = None
g.max_buy_amount = None

卖出未卖出成功的股票

def sell_every_day(context):
g.open_sell_securities = list(set(g.open_sell_securities))
open_sell_securities = [s for s in context.portfolio.positions.keys() if s in g.open_sell_securities]
if len(open_sell_securities)>0:
for stock in open_sell_securities:
order_target_value(stock, 0)
g.open_sell_securities = [s for s in g.open_sell_securities if s in context.portfolio.positions.keys()]
return

风控

def risk_management(context):

### _风控函数筛选-开始 ###
### _风控函数筛选-结束 ###
return

股票筛选

def check_stocks(context):
if g.check_stocks_days%g.check_stocks_refresh_rate != 0:

    # 计数器加一
    g.check_stocks_days  = 1
    return
# 股票池赋值
g.check_out_lists = get_security_universe(context, g.security_universe_index, g.security_universe_user_securities)
# 行业过滤
g.check_out_lists = industry_filter(context, g.check_out_lists, g.industry_list)
# 概念过滤
g.check_out_lists = concept_filter(context, g.check_out_lists, g.concept_list)
# 过滤ST股票
g.check_out_lists = st_filter(context, g.check_out_lists)
# 过滤退市股票
g.check_out_lists = delisted_filter(context, g.check_out_lists)
# 财务筛选
g.check_out_lists = financial_statements_filter(context, g.check_out_lists)
# 行情筛选
g.check_out_lists = situation_filter(context, g.check_out_lists)
# 技术指标筛选
g.check_out_lists = technical_indicators_filter(context, g.check_out_lists)
# 形态指标筛选函数
g.check_out_lists = pattern_recognition_filter(context, g.check_out_lists)
# 其他筛选函数
g.check_out_lists = other_func_filter(context, g.check_out_lists)

# 排序
input_dict = get_check_stocks_sort_input_dict()
g.check_out_lists = check_stocks_sort(context,g.check_out_lists,input_dict,g.check_out_lists_ascending)

# 计数器归一
g.check_stocks_days = 1
return

交易函数

def trade(context):

初始化买入列表

buy_lists = []

# 买入股票筛选
if g.buy_trade_days%g.buy_refresh_rate == 0:
    # 获取 buy_lists 列表
    buy_lists = g.check_out_lists
    # 过滤ST股票
    buy_lists = st_filter(context, buy_lists)
    # 过滤停牌股票
    buy_lists = paused_filter(context, buy_lists)
    # 过滤退市股票
    buy_lists = delisted_filter(context, buy_lists)
    # 过滤涨停股票
    buy_lists = high_limit_filter(context, buy_lists)

    ### _入场函数筛选-开始 ###
    ### _入场函数筛选-结束 ###

# 卖出操作
if g.sell_trade_days%g.sell_refresh_rate != 0:
    # 计数器加一
    g.sell_trade_days  = 1
else:
    # 卖出股票
    sell(context, buy_lists)
    # 计数器归一
    g.sell_trade_days = 1


# 买入操作
if g.buy_trade_days%g.buy_refresh_rate != 0:
    # 计数器加一
    g.buy_trade_days  = 1
else:
    # 卖出股票
    buy(context, buy_lists)
    # 计数器归一
    g.buy_trade_days = 1

卖出股票日期计数

def selled_security_list_count(context):
g.daily_risk_management = True
if len(g.selled_security_list)>0:
for stock in g.selled_security_list.keys():
g.selled_security_list[stock] = 1

############################ 选股函数群

财务指标筛选函数

def financial_statements_filter(context, security_list):

### _财务指标筛选函数-开始 ###
security_list = financial_data_filter_qujian(security_list, valuation.pe_ratio, (15,25))
### _财务指标筛选函数-结束 ###

# 返回列表
return security_list

行情筛选函数

def situation_filter(context, security_list):

### _行情筛选函数-开始 ###
### _行情筛选函数-结束 ###

# 返回列表
return security_list

技术指标筛选函数

def technical_indicators_filter(context, security_list):

### _技术指标筛选函数-开始 ###
### _技术指标筛选函数-结束 ###

# 返回列表
return security_list

形态指标筛选函数

def pattern_recognition_filter(context, security_list):

### _形态指标筛选函数-开始 ###
### _形态指标筛选函数-结束 ###

# 返回列表
return security_list

其他方式筛选函数

def other_func_filter(context, security_list):

### _其他方式筛选函数-开始 ###
### _其他方式筛选函数-结束 ###

# 返回列表
return security_list

获取选股排序的 input_dict

def get_check_stocks_sort_input_dict():
input_dict = {
}

# 返回结果
return input_dict

############################ 交易函数群

交易函数 - 出场

def sell(context, buy_lists):

# 获取 sell_lists 列表
init_sl = context.portfolio.positions.keys()
sell_lists = context.portfolio.positions.keys()

# 判断是否卖出buy_lists中的股票
if not g.sell_will_buy:
    sell_lists = [security for security in sell_lists if security not in buy_lists]

### _出场函数筛选-开始 ###
### _出场函数筛选-结束 ###

# 卖出股票
if len(sell_lists)>0:
    for stock in sell_lists:
        sell_by_amount_or_percent_or_none(context,stock, g.sell_by_amount, g.sell_by_percent, g.open_sell_securities)

# 获取卖出的股票, 并加入到 g.selled_security_list中
selled_security_list_dict(context,init_sl)

return

交易函数 - 入场

def buy(context, buy_lists):

# 风控信号判断
if not g.risk_management_signal:
    return

# 判断当日是否触发风控清仓止损
if not g.daily_risk_management:
    return
# 判断是否可重复买入
buy_lists = holded_filter(context,buy_lists)

# 获取最终的 buy_lists 列表
Num = g.max_hold_stocknum - len(context.portfolio.positions)
buy_lists = buy_lists[:Num]

# 买入股票
if len(buy_lists)>0:
    # 分配资金
    result = order_style(context,buy_lists,g.max_hold_stocknum, g.order_style_str, g.order_style_value)
    for stock in buy_lists:
        if len(context.portfolio.positions) < g.max_hold_stocknum:
            # 获取资金
            Cash = result[stock]
            # 判断个股最大持仓比重
            value = judge_security_max_proportion(context,stock,Cash,g.security_max_proportion)
            # 判断单只最大买入股数或金额
            amount = max_buy_value_or_amount(stock,value,g.max_buy_value,g.max_buy_amount)
            # 下单
            order(stock, amount, MarketOrderStyle())
return

############################# 公用函数群

排序

def check_stocks_sort(context,security_list,input_dict,ascending='desc'):
if (len(security_list) == 0) or (len(input_dict) == 0):
return security_list
else:

    # 生成 key 的 list
    idk = list(input_dict.keys())
    # 生成矩阵
    a = pd.DataFrame()
    for i in idk:
        b = get_sort_dataframe(security_list, i, input_dict[i])
        a = pd.concat([a,b],axis = 1)
    # 生成 score 列
    a['score'] = a.sum(1,False)
    # 根据 score 排序
    if ascending == 'asc':# 升序
        if hasattr(a, 'sort'):
            a = a.sort(['score'],ascending = True)
        else:
            a = a.sort_values(['score'],ascending = True)
    elif ascending == 'desc':# 降序
        if hasattr(a, 'sort'):
            a = a.sort(['score'],ascending = False)
        else:
            a = a.sort_values(['score'],ascending = False)
    # 返回结果
    return list(a.index)

过滤同一标的继上次卖出N天不再买入

def filter_n_tradeday_not_buy(security, n=0):
try:
if (security in g.selled_security_list.keys()) and (g.selled_security_list[security]0:
for stock in selled_sl:
g.selled_security_list[stock] = 0

过滤停牌股票

def paused_filter(context, security_list):
if g.filter_paused:
current_data = get_current_data()
security_list = [stock for stock in security_list if not current_data[stock].paused]

# 返回结果
return security_list

过滤退市股票

def delisted_filter(context, security_list):
if g.filter_delisted:
current_data = get_current_data()
security_list = [stock for stock in security_list if not (('退' in current_data[stock].name) or ('*' in current_data[stock].name))]

# 返回结果
return security_list

过滤ST股票

def st_filter(context, security_list):
if g.only_st:
current_data = get_current_data()
security_list = [stock for stock in security_list if current_data[stock].is_st]
else:
if g.filter_st:
current_data = get_current_data()
security_list = [stock for stock in security_list if not current_data[stock].is_st]

# 返回结果
return security_list

过滤涨停股票

def high_limit_filter(context, security_list):
current_data = get_current_data()
security_list = [stock for stock in security_list if not (current_data[stock].day_open >= current_data[stock].high_limit)]

# 返回结果
return security_list

获取股票股票池

def get_security_universe(context, security_universe_index, security_universe_user_securities):
temp_index = []
for s in security_universe_index:
if s == 'all_a_securities':
temp_index = list(get_all_securities(['stock'], context.current_dt.date()).index)
else:
temp_index = get_index_stocks(s)
for x in security_universe_user_securities:
temp_index = x
return sorted(list(set(temp_index)))

行业过滤

def industry_filter(context, security_list, industry_list):
if len(industry_list) == 0:

    # 返回股票列表
    return security_list
else:
    securities = []
    for s in industry_list:
        temp_securities = get_industry_stocks(s)
        securities  = temp_securities
    security_list = [stock for stock in security_list if stock in securities]
    # 返回股票列表
    return security_list

概念过滤

def concept_filter(context, security_list, concept_list):
if len(concept_list) == 0:
return security_list
else:
securities = []
for s in concept_list:
temp_securities = get_concept_stocks(s)
securities = temp_securities
security_list = [stock for stock in security_list if stock in securities]

    # 返回股票列表
    return security_list

自定义函数