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量化交易吧 /  量化平台 帖子：3365818 新帖：25

【API解析】create_backtest

到此一游发表于：5 月 10 日 05：19回复(1)

概述

这两个API小伙伴们在使用过程中经常存在疑惑，特地在此多解释下。
（1）这两个API目前只能在投资研究环境（官网和客户端）中使用，不能在回测、模拟交易及实盘中使用；
（2）create_backtest中的algorithm_id为：官网策略网址algorithmId后的部分，或者客户端策略ID（1，2，3...）；
id2.png
id.png
（3）create_backtest中的extras与初始化中的g对象后的参数一一对应：如 extras={'x':1, 'y':2}，则回测中 g.x = 1, g.y = 2；
（4）get_backtest中的backtest_id为回测或者模拟交易的backtestId后面的部分；
回测.png
模拟交易.png
（5）get_backtest中的gt.get_status()表示获取回测状态，只有状态为done后，才能获取其他的信息；

注意事项

（1）客户端和官网是独立的，不能在客户端读取官网的回测及模拟交易；

相关教程

【量化课堂】多回测运行和参数分析框架
关于回测中的绘图,多基准,策略对比等问题
Get API 新技能，研究中写策略并回测

下面的研究为在客户端使用create_backtest的教程

研究模块创建/读取回测功能¶

为了进一步打通研究模块与回测模块，我们增加了在研究中调用回测的新功能。

主要功能如下：

  1. 可以在研究中创建回测
  2. 设定初始持仓
  3. 设定全局变量值
  4. 获取回测状态
  5. 获得回测参数
  6. 获得收益曲线
  7. 获得持仓详情
  8. 获得交易详情
  9. 获得所有 record 记录
  10. 获得总的风险指标
  11. 获得分月计算的风险指标

具体功能参看API - 研究中创建回测函数、研究中获取回测信息

首先打我的策略标签，找到策略 ID， 如下所示(上方红色框内的部分)：

img

测试所使用的代码如下所示：

def initialize(context):
    # 定义一个全局变量, 保存要操作的股票
    # 000001(股票:平安银行)
    g.security = '000001.XSHE'
    # 初始化此策略
    # 设置我们要操作的股票池, 这里我们只操作一支股票
    set_universe([g.security])
    # 设置均线长度
    g.ma_long = 5
    g.m = 1.01

# 每个单位时间(如果按天回测,则每天调用一次,如果按分钟,则每分钟调用一次)调用一次
def handle_data(context, data):
    security = g.security
    # 取得过去五天的平均价格
    average_price = data[security].mavg(g.ma_long, 'close')
    # 取得上一时间点价格
    current_price = data[security].close
    # 取得当前的现金
    cash = context.portfolio.cash

    # 如果上一时间点价格高出五天平均价1%, 则全仓买入
    if current_price > g.m*average_price:
        # 用所有 cash 买入股票
        order_value(security, cash)
        # 记录这次买入
        log.info("Buying %s" % (security))
    # 如果上一时间点价格低于五天平均价, 则空仓卖出
    elif current_price < average_price and context.portfolio.positions[security].sellable_amount > 0:
        # 卖出所有股票,使这只股票的最终持有量为0
        order_target(security, 0)
        # 记录这次卖出
        log.info("Selling %s" % (security))
    # 画出上一时间点价格
    record(stock_price=current_price)

接下来设定初始化仓位，设定g.全局变量的值，当然也可以选择不设置：

# 设定初始仓位
InitialPositions = [
    {
        'security': '000001.XSHE',
        'amount': '1000',  # 100股
        'avg_cost': '10.0' # 持仓均价10元
    }
]

# 设定g.全局变量的值
extra_vars = {'ma_long': 5, 'm': 1.01}

# 记得此处传入你自己的 algorithmId
out_algorithm_id = create_backtest('1', '2015-06-01', '2015-12-31', frequency="day",\
                                   initial_cash=100000, initial_positions=InitialPositions, extras=extra_vars, name=None)
out_algorithm_id

118

out_algorithm_id 即为生成的回测 ID，在回测列表中可以查看到。

img

下面介绍如何在研究获取回测结果¶

# 研究中获取回测信息
gt = get_backtest(out_algorithm_id)

gt.get_status()        # 获取回测状态

u'done'
gt.get_params()        # 获取回测参数

{u'algorithm_id': 1,
 u'end_date': u'2015-12-31 00:00:00',
 u'extras': {},
 u'frequency': u'day',
 u'initial_cash': 100000,
 u'initial_positions': [],
 u'name': u'\u8fd9\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u7b56\u7565-1',
 u'start_date': u'2015-06-01 00:00:00'}
gt.get_results()       # 获取收益曲线

[{u'benchmark_returns': 0.04861770576899138,
  u'returns': 0.0,
  u'time': u'2015-06-01 16:00:00'},
 {u'benchmark_returns': 0.06631942586693307,
  u'returns': 0.0,
  u'time': u'2015-06-02 16:00:00'},
 {u'benchmark_returns': 0.0625432131562591,
  u'returns': 0.0,
  u'time': u'2015-06-03 16:00:00'},
 {u'benchmark_returns': 0.07035716403120218,
  u'returns': 0.030503200000000064,
  u'time': u'2015-06-04 16:00:00'},
 {u'benchmark_returns': 0.08050749158873405,
  u'returns': 0.025883199999999995,
  u'time': u'2015-06-05 16:00:00'},
 {u'benchmark_returns': 0.10595747133393907,
  u'returns': 0.0874832000000001,
  u'time': u'2015-06-08 16:00:00'},
 {u'benchmark_returns': 0.09846082148326252,
  u'returns': 0.0682332000000001,
  u'time': u'2015-06-09 16:00:00'},
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  u'returns': 0.04975320000000005,
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  u'returns': 0.04686389999999996,
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 {u'benchmark_returns': -0.29637836825056196,
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 {u'benchmark_returns': -0.27970705017673625,
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 {u'benchmark_returns': -0.26994632530915674,
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 {u'benchmark_returns': -0.26992215589519897,
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 {u'benchmark_returns': -0.28250842985777846,
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 {u'benchmark_returns': -0.27191520295387417,
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 {u'benchmark_returns': -0.26226664895620144,
  u'returns': -0.0970259,
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 {u'benchmark_returns': -0.2585441460543225,
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 {u'benchmark_returns': -0.2577967534073192,
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 {u'benchmark_returns': -0.26994343324252923,
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 {u'benchmark_returns': -0.2819490215415582,
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 {u'benchmark_returns': -0.2841116676503136,
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  u'time': u'2015-11-03 16:00:00'},
 {u'benchmark_returns': -0.25043045313106493,
  u'returns': -0.12339730000000027,
  u'time': u'2015-11-04 16:00:00'},
 {u'benchmark_returns': -0.2344348457671196,
  u'returns': -0.08924960000000037,
  u'time': u'2015-11-05 16:00:00'},
 {u'benchmark_returns': -0.21637926065969282,
  u'returns': -0.06506960000000017,
  u'time': u'2015-11-06 16:00:00'},
 {u'benchmark_returns': -0.20667410478659742,
  u'returns': -0.024149600000000104,
  u'time': u'2015-11-09 16:00:00'},
 {u'benchmark_returns': -0.20814430751427082,
  u'returns': -0.03809960000000012,
  u'time': u'2015-11-10 16:00:00'},
 {u'benchmark_returns': -0.20806002442969984,
  u'returns': -0.05297960000000013,
  u'time': u'2015-11-11 16:00:00'},
 {u'benchmark_returns': -0.21597643709372916,
  u'returns': -0.06413960000000007,
  u'time': u'2015-11-12 16:00:00'},
 {u'benchmark_returns': -0.22611560953712673,
  u'returns': -0.08021410000000029,
  u'time': u'2015-11-13 16:00:00'},
 {u'benchmark_returns': -0.22242120099677132,
  u'returns': -0.08021410000000018,
  u'time': u'2015-11-16 16:00:00'},
 {u'benchmark_returns': -0.22360674173783035,
  u'returns': -0.08021410000000018,
  u'time': u'2015-11-17 16:00:00'},
 {u'benchmark_returns': -0.23244964860357598,
  u'returns': -0.08021410000000018,
  u'time': u'2015-11-18 16:00:00'},
 {u'benchmark_returns': -0.22018129539382614,
  u'returns': -0.08021410000000018,
  u'time': u'2015-11-19 16:00:00'},
 {u'benchmark_returns': -0.22030234903980284,
  u'returns': -0.08021410000000018,
  u'time': u'2015-11-20 16:00:00'},
 {u'benchmark_returns': -0.22465036463795762,
  u'returns': -0.08021410000000018,
  u'time': u'2015-11-23 16:00:00'},
 {u'benchmark_returns': -0.22453592142998635,
  u'returns': -0.08021410000000018,
  u'time': u'2015-11-24 16:00:00'},
 {u'benchmark_returns': -0.21881004266004844,
  u'returns': -0.08021410000000018,
  u'time': u'2015-11-25 16:00:00'},
 {u'benchmark_returns': -0.22339148935027442,
  u'returns': -0.08021410000000018,
  u'time': u'2015-11-26 16:00:00'},
 {u'benchmark_returns': -0.26521015305436313,
  u'returns': -0.08021410000000018,
  u'time': u'2015-11-27 16:00:00'},
 {u'benchmark_returns': -0.26326420536647754,
  u'returns': -0.08021410000000018,
  u'time': u'2015-11-30 16:00:00'},
 {u'benchmark_returns': -0.2580411330373372,
  u'returns': -0.08021410000000018,
  u'time': u'2015-12-01 16:00:00'},
 {u'benchmark_returns': -0.23113272540715646,
  u'returns': -0.08021410000000018,
  u'time': u'2015-12-02 16:00:00'},
 {u'benchmark_returns': -0.22548410613140846,
  u'returns': -0.07684820000000026,
  u'time': u'2015-12-03 16:00:00'},
 {u'benchmark_returns': -0.24029706482092217,
  u'returns': -0.10141820000000001,
  u'time': u'2015-12-04 16:00:00'},
 {u'benchmark_returns': -0.2382282043013707,
  u'returns': -0.09959819999999997,
  u'time': u'2015-12-07 16:00:00'},
 {u'benchmark_returns': -0.2515703405346481,
  u'returns': -0.10712279999999985,
  u'time': u'2015-12-08 16:00:00'},
 {u'benchmark_returns': -0.2489017893422799,
  u'returns': -0.10712280000000007,
  u'time': u'2015-12-09 16:00:00'},
 {u'benchmark_returns': -0.2515571196586369,
  u'returns': -0.10712280000000007,
  u'time': u'2015-12-10 16:00:00'},
 {u'benchmark_returns': -0.25466092687843334,
  u'returns': -0.10712280000000007,
  u'time': u'2015-12-11 16:00:00'},
 {u'benchmark_returns': -0.23332925001069027,
  u'returns': -0.10712280000000007,
  u'time': u'2015-12-14 16:00:00'},
 {u'benchmark_returns': -0.23682720459656803,
  u'returns': -0.10712280000000007,
  u'time': u'2015-12-15 16:00:00'},
 {u'benchmark_returns': -0.23867585490005938,
  u'returns': -0.10712280000000007,
  u'time': u'2015-12-16 16:00:00'},
 {u'benchmark_returns': -0.22412297563082684,
  u'returns': -0.10712280000000007,
  u'time': u'2015-12-17 16:00:00'},
 {u'benchmark_returns': -0.22163889697405126,
  u'returns': -0.10712280000000007,
  u'time': u'2015-12-18 16:00:00'},
 {u'benchmark_returns': -0.20138368862027545,
  u'returns': -0.0812885000000001,
  u'time': u'2015-12-21 16:00:00'},
 {u'benchmark_returns': -0.19915927623140572,
  u'returns': -0.08758850000000018,
  u'time': u'2015-12-22 16:00:00'},
 {u'benchmark_returns': -0.20129775292620333,
  u'returns': -0.08398850000000013,
  u'time': u'2015-12-23 16:00:00'},
 {u'benchmark_returns': -0.20893673377018684,
  u'returns': -0.09388850000000015,
  u'time': u'2015-12-24 16:00:00'},
 {u'benchmark_returns': -0.20711906989484652,
  u'returns': -0.09325970000000017,
  u'time': u'2015-12-25 16:00:00'},
 {u'benchmark_returns': -0.2299599923897332,
  u'returns': -0.09325970000000017,
  u'time': u'2015-12-28 16:00:00'},
 {u'benchmark_returns': -0.22288620399522474,
  u'returns': -0.09325970000000017,
  u'time': u'2015-12-29 16:00:00'},
 {u'benchmark_returns': -0.22220450257590174,
  u'returns': -0.09325970000000017,
  u'time': u'2015-12-30 16:00:00'}]
gt.get_positions()     # 获取所有持仓列表

[{u'amount': 7700,
  u'avg_cost': 12.85,
  u'closeable_amount': 0,
  u'price': 13.25,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-06-04 16:00:00'},
 {u'amount': 7700,
  u'avg_cost': 12.85,
  u'closeable_amount': 7700,
  u'price': 13.19,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-06-05 16:00:00'},
 {u'amount': 7700,
  u'avg_cost': 12.85,
  u'closeable_amount': 7700,
  u'price': 13.99,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-06-08 16:00:00'},
 {u'amount': 7700,
  u'avg_cost': 12.85,
  u'closeable_amount': 7700,
  u'price': 13.74,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-06-09 16:00:00'},
 {u'amount': 7700,
  u'avg_cost': 12.85,
  u'closeable_amount': 7700,
  u'price': 13.5,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-06-10 16:00:00'},
 {u'amount': 9000,
  u'avg_cost': 11.62,
  u'closeable_amount': 0,
  u'price': 11.27,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-07-01 16:00:00'},
 {u'amount': 9000,
  u'avg_cost': 11.19,
  u'closeable_amount': 0,
  u'price': 10.68,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-07-08 16:00:00'},
 {u'amount': 8500,
  u'avg_cost': 11.22,
  u'closeable_amount': 0,
  u'price': 12.03,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-07-10 16:00:00'},
 {u'amount': 8500,
  u'avg_cost': 11.22,
  u'closeable_amount': 8500,
  u'price': 11.69,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-07-13 16:00:00'},
 {u'amount': 8500,
  u'avg_cost': 11.22,
  u'closeable_amount': 8500,
  u'price': 11.23,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-07-14 16:00:00'},
 {u'amount': 9100,
  u'avg_cost': 10.35,
  u'closeable_amount': 0,
  u'price': 10.41,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-08-04 16:00:00'},
 {u'amount': 9100,
  u'avg_cost': 10.35,
  u'closeable_amount': 9100,
  u'price': 10.19,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-08-05 16:00:00'},
 {u'amount': 9100,
  u'avg_cost': 10.35,
  u'closeable_amount': 9100,
  u'price': 10.14,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-08-06 16:00:00'},
 {u'amount': 8900,
  u'avg_cost': 10.46,
  u'closeable_amount': 0,
  u'price': 10.39,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-08-11 16:00:00'},
 {u'amount': 8900,
  u'avg_cost': 10.46,
  u'closeable_amount': 8900,
  u'price': 10.17,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-08-12 16:00:00'},
 {u'amount': 10200,
  u'avg_cost': 8.82,
  u'closeable_amount': 0,
  u'price': 8.77,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-08-28 16:00:00'},
 {u'amount': 10200,
  u'avg_cost': 8.82,
  u'closeable_amount': 10200,
  u'price': 8.96,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-08-31 16:00:00'},
 {u'amount': 10200,
  u'avg_cost': 8.82,
  u'closeable_amount': 10200,
  u'price': 9.36,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-09-01 16:00:00'},
 {u'amount': 10200,
  u'avg_cost': 8.82,
  u'closeable_amount': 10200,
  u'price': 9.58,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-09-02 16:00:00'},
 {u'amount': 10200,
  u'avg_cost': 8.82,
  u'closeable_amount': 10200,
  u'price': 8.81,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-09-07 16:00:00'},
 {u'amount': 10300,
  u'avg_cost': 8.71,
  u'closeable_amount': 0,
  u'price': 8.82,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-10-09 16:00:00'},
 {u'amount': 10300,
  u'avg_cost': 8.71,
  u'closeable_amount': 10300,
  u'price': 9.09,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-10-12 16:00:00'},
 {u'amount': 10300,
  u'avg_cost': 8.71,
  u'closeable_amount': 10300,
  u'price': 9.01,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-10-13 16:00:00'},
 {u'amount': 10300,
  u'avg_cost': 8.71,
  u'closeable_amount': 10300,
  u'price': 8.89,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-10-14 16:00:00'},
 {u'amount': 9900,
  u'avg_cost': 9.15,
  u'closeable_amount': 0,
  u'price': 9.08,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-10-21 16:00:00'},
 {u'amount': 9600,
  u'avg_cost': 9.4,
  u'closeable_amount': 0,
  u'price': 9.32,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-10-26 16:00:00'},
 {u'amount': 9600,
  u'avg_cost': 9.4,
  u'closeable_amount': 9600,
  u'price': 9.29,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-10-27 16:00:00'},
 {u'amount': 9600,
  u'avg_cost': 9.4,
  u'closeable_amount': 9600,
  u'price': 9.12,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-10-28 16:00:00'},
 {u'amount': 9300,
  u'avg_cost': 9.4,
  u'closeable_amount': 0,
  u'price': 9.77,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-11-05 16:00:00'},
 {u'amount': 9300,
  u'avg_cost': 9.4,
  u'closeable_amount': 9300,
  u'price': 10.03,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-11-06 16:00:00'},
 {u'amount': 9300,
  u'avg_cost': 9.4,
  u'closeable_amount': 9300,
  u'price': 10.47,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-11-09 16:00:00'},
 {u'amount': 9300,
  u'avg_cost': 9.4,
  u'closeable_amount': 9300,
  u'price': 10.32,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-11-10 16:00:00'},
 {u'amount': 9300,
  u'avg_cost': 9.4,
  u'closeable_amount': 9300,
  u'price': 10.16,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-11-11 16:00:00'},
 {u'amount': 9300,
  u'avg_cost': 9.4,
  u'closeable_amount': 9300,
  u'price': 10.04,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-11-12 16:00:00'},
 {u'amount': 9100,
  u'avg_cost': 10.04,
  u'closeable_amount': 0,
  u'price': 10.08,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-12-03 16:00:00'},
 {u'amount': 9100,
  u'avg_cost': 10.04,
  u'closeable_amount': 9100,
  u'price': 9.81,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-12-04 16:00:00'},
 {u'amount': 9100,
  u'avg_cost': 10.04,
  u'closeable_amount': 9100,
  u'price': 9.83,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-12-07 16:00:00'},
 {u'amount': 9000,
  u'avg_cost': 9.84,
  u'closeable_amount': 0,
  u'price': 10.13,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-12-21 16:00:00'},
 {u'amount': 9000,
  u'avg_cost': 9.84,
  u'closeable_amount': 9000,
  u'price': 10.06,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-12-22 16:00:00'},
 {u'amount': 9000,
  u'avg_cost': 9.84,
  u'closeable_amount': 9000,
  u'price': 10.1,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-12-23 16:00:00'},
 {u'amount': 9000,
  u'avg_cost': 9.84,
  u'closeable_amount': 9000,
  u'price': 9.99,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-12-24 16:00:00'}]
gt.get_orders()        # 获取交易列表

[{u'action': u'open',
  u'amount': 7700,
  u'commission': 29.68,
  u'filled': 7700,
  u'price': 12.85,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-06-04 09:30:00'},
 {u'action': u'close',
  u'amount': 7700,
  u'commission': 134.93,
  u'filled': 7700,
  u'price': 13.48,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-06-11 09:30:00'},
 {u'action': u'open',
  u'amount': 9000,
  u'commission': 31.37,
  u'filled': 9000,
  u'price': 11.62,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-07-01 09:30:00'},
 {u'action': u'close',
  u'amount': 9000,
  u'commission': 131.51,
  u'filled': 9000,
  u'price': 11.24,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-07-02 09:30:00'},
 {u'action': u'open',
  u'amount': 9000,
  u'commission': 30.21,
  u'filled': 9000,
  u'price': 11.19,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-07-08 09:30:00'},
 {u'action': u'close',
  u'amount': 9000,
  u'commission': 124.84,
  u'filled': 9000,
  u'price': 10.67,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-07-09 09:30:00'},
 {u'action': u'open',
  u'amount': 8500,
  u'commission': 28.61,
  u'filled': 8500,
  u'price': 11.22,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-07-10 09:30:00'},
 {u'action': u'close',
  u'amount': 8500,
  u'commission': 122.1,
  u'filled': 8500,
  u'price': 11.05,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-07-15 09:30:00'},
 {u'action': u'open',
  u'amount': 9100,
  u'commission': 28.26,
  u'filled': 9100,
  u'price': 10.35,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-08-04 09:30:00'},
 {u'action': u'close',
  u'amount': 9100,
  u'commission': 120.67,
  u'filled': 9100,
  u'price': 10.2,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-08-07 09:30:00'},
 {u'action': u'open',
  u'amount': 8900,
  u'commission': 27.93,
  u'filled': 8900,
  u'price': 10.46,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-08-11 09:30:00'},
 {u'action': u'close',
  u'amount': 8900,
  u'commission': 117.09,
  u'filled': 8900,
  u'price': 10.12,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-08-13 09:30:00'},
 {u'action': u'open',
  u'amount': 10200,
  u'commission': 26.99,
  u'filled': 10200,
  u'price': 8.82,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-08-28 09:30:00'},
 {u'action': u'close',
  u'amount': 10200,
  u'commission': 116.69,
  u'filled': 10200,
  u'price': 8.8,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-09-08 09:30:00'},
 {u'action': u'open',
  u'amount': 10300,
  u'commission': 26.91,
  u'filled': 10300,
  u'price': 8.71,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-10-09 09:30:00'},
 {u'action': u'close',
  u'amount': 10300,
  u'commission': 118.5,
  u'filled': 10300,
  u'price': 8.85,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-10-15 09:30:00'},
 {u'action': u'open',
  u'amount': 9900,
  u'commission': 27.18,
  u'filled': 9900,
  u'price': 9.15,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-10-21 09:30:00'},
 {u'action': u'close',
  u'amount': 9900,
  u'commission': 117.12,
  u'filled': 9900,
  u'price': 9.1,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-10-22 09:30:00'},
 {u'action': u'open',
  u'amount': 9600,
  u'commission': 27.07,
  u'filled': 9600,
  u'price': 9.4,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-10-26 09:30:00'},
 {u'action': u'close',
  u'amount': 9600,
  u'commission': 114.07,
  u'filled': 9600,
  u'price': 9.14,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-10-29 09:30:00'},
 {u'action': u'open',
  u'amount': 9300,
  u'commission': 26.23,
  u'filled': 9300,
  u'price': 9.4,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-11-05 09:30:00'},
 {u'action': u'close',
  u'amount': 9300,
  u'commission': 119.45,
  u'filled': 9300,
  u'price': 9.88,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-11-13 09:30:00'},
 {u'action': u'open',
  u'amount': 9100,
  u'commission': 27.41,
  u'filled': 9100,
  u'price': 10.04,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-12-03 09:30:00'},
 {u'action': u'close',
  u'amount': 9100,
  u'commission': 115.46,
  u'filled': 9100,
  u'price': 9.76,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-12-08 09:30:00'},
 {u'action': u'open',
  u'amount': 9000,
  u'commission': 26.57,
  u'filled': 9000,
  u'price': 9.84,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-12-21 09:30:00'},
 {u'action': u'close',
  u'amount': 9000,
  u'commission': 117.12,
  u'filled': 9000,
  u'price': 10.01,
  u'security': u'000001.XSHE',
  u'security_name': u'\u5e73\u5b89\u94f6\u884c',
  u'time': u'2015-12-25 09:30:00'}]
gt.get_records()       # 获取所有record()记录

[{u'stock_price': 12.4, u'time': u'2015-06-01'},
 {u'stock_price': 12.87, u'time': u'2015-06-02'},
 {u'stock_price': 12.76, u'time': u'2015-06-03'},
 {u'stock_price': 12.81, u'time': u'2015-06-04'},
 {u'stock_price': 13.25, u'time': u'2015-06-05'},
 {u'stock_price': 13.19, u'time': u'2015-06-08'},
 {u'stock_price': 13.99, u'time': u'2015-06-09'},
 {u'stock_price': 13.74, u'time': u'2015-06-10'},
 {u'stock_price': 13.5, u'time': u'2015-06-11'},
 {u'stock_price': 13.34, u'time': u'2015-06-12'},
 {u'stock_price': 13.36, u'time': u'2015-06-15'},
 {u'stock_price': 12.89, u'time': u'2015-06-16'},
 {u'stock_price': 12.66, u'time': u'2015-06-17'},
 {u'stock_price': 12.73, u'time': u'2015-06-18'},
 {u'stock_price': 12.45, u'time': u'2015-06-19'},
 {u'stock_price': 11.84, u'time': u'2015-06-23'},
 {u'stock_price': 12.1, u'time': u'2015-06-24'},
 {u'stock_price': 12.24, u'time': u'2015-06-25'},
 {u'stock_price': 12.04, u'time': u'2015-06-26'},
 {u'stock_price': 11.15, u'time': u'2015-06-29'},
 {u'stock_price': 10.98, u'time': u'2015-06-30'},
 {u'stock_price': 11.77, u'time': u'2015-07-01'},
 {u'stock_price': 11.27, u'time': u'2015-07-02'},
 {u'stock_price': 11.13, u'time': u'2015-07-03'},
 {u'stock_price': 10.58, u'time': u'2015-07-06'},
 {u'stock_price': 11.23, u'time': u'2015-07-07'},
 {u'stock_price': 11.86, u'time': u'2015-07-08'},
 {u'stock_price': 10.68, u'time': u'2015-07-09'},
 {u'stock_price': 11.54, u'time': u'2015-07-10'},
 {u'stock_price': 12.03, u'time': u'2015-07-13'},
 {u'stock_price': 11.69, u'time': u'2015-07-14'},
 {u'stock_price': 11.23, u'time': u'2015-07-15'},
 {u'stock_price': 10.99, u'time': u'2015-07-16'},
 {u'stock_price': 11.01, u'time': u'2015-07-17'},
 {u'stock_price': 11.19, u'time': u'2015-07-20'},
 {u'stock_price': 11.01, u'time': u'2015-07-21'},
 {u'stock_price': 10.98, u'time': u'2015-07-22'},
 {u'stock_price': 10.94, u'time': u'2015-07-23'},
 {u'stock_price': 11.06, u'time': u'2015-07-24'},
 {u'stock_price': 10.83, u'time': u'2015-07-27'},
 {u'stock_price': 10.07, u'time': u'2015-07-28'},
 {u'stock_price': 10.21, u'time': u'2015-07-29'},
 {u'stock_price': 10.2, u'time': u'2015-07-30'},
 {u'stock_price': 9.92, u'time': u'2015-07-31'},
 {u'stock_price': 10.0, u'time': u'2015-08-03'},
 {u'stock_price': 10.38, u'time': u'2015-08-04'},
 {u'stock_price': 10.41, u'time': u'2015-08-05'},
 {u'stock_price': 10.19, u'time': u'2015-08-06'},
 {u'stock_price': 10.14, u'time': u'2015-08-07'},
 {u'stock_price': 10.21, u'time': u'2015-08-10'},
 {u'stock_price': 10.46, u'time': u'2015-08-11'},
 {u'stock_price': 10.39, u'time': u'2015-08-12'},
 {u'stock_price': 10.17, u'time': u'2015-08-13'},
 {u'stock_price': 10.17, u'time': u'2015-08-14'},
 {u'stock_price': 10.23, u'time': u'2015-08-17'},
 {u'stock_price': 10.15, u'time': u'2015-08-18'},
 {u'stock_price': 9.93, u'time': u'2015-08-19'},
 {u'stock_price': 9.9, u'time': u'2015-08-20'},
 {u'stock_price': 9.75, u'time': u'2015-08-21'},
 {u'stock_price': 9.31, u'time': u'2015-08-24'},
 {u'stock_price': 8.38, u'time': u'2015-08-25'},
 {u'stock_price': 7.66, u'time': u'2015-08-26'},
 {u'stock_price': 8.02, u'time': u'2015-08-27'},
 {u'stock_price': 8.74, u'time': u'2015-08-28'},
 {u'stock_price': 8.77, u'time': u'2015-08-31'},
 {u'stock_price': 8.96, u'time': u'2015-09-01'},
 {u'stock_price': 9.36, u'time': u'2015-09-02'},
 {u'stock_price': 9.58, u'time': u'2015-09-07'},
 {u'stock_price': 8.81, u'time': u'2015-09-08'},
 {u'stock_price': 8.9, u'time': u'2015-09-09'},
 {u'stock_price': 8.98, u'time': u'2015-09-10'},
 {u'stock_price': 8.94, u'time': u'2015-09-11'},
 {u'stock_price': 8.87, u'time': u'2015-09-14'},
 {u'stock_price': 8.8, u'time': u'2015-09-15'},
 {u'stock_price': 8.56, u'time': u'2015-09-16'},
 {u'stock_price': 8.82, u'time': u'2015-09-17'},
 {u'stock_price': 8.72, u'time': u'2015-09-18'},
 {u'stock_price': 8.75, u'time': u'2015-09-21'},
 {u'stock_price': 8.76, u'time': u'2015-09-22'},
 {u'stock_price': 8.87, u'time': u'2015-09-23'},
 {u'stock_price': 8.66, u'time': u'2015-09-24'},
 {u'stock_price': 8.67, u'time': u'2015-09-25'},
 {u'stock_price': 8.54, u'time': u'2015-09-28'},
 {u'stock_price': 8.52, u'time': u'2015-09-29'},
 {u'stock_price': 8.4, u'time': u'2015-09-30'},
 {u'stock_price': 8.49, u'time': u'2015-10-08'},
 {u'stock_price': 8.66, u'time': u'2015-10-09'},
 {u'stock_price': 8.82, u'time': u'2015-10-12'},
 {u'stock_price': 9.09, u'time': u'2015-10-13'},
 {u'stock_price': 9.01, u'time': u'2015-10-14'},
 {u'stock_price': 8.89, u'time': u'2015-10-15'},
 {u'stock_price': 9.04, u'time': u'2015-10-16'},
 {u'stock_price': 9.09, u'time': u'2015-10-19'},
 {u'stock_price': 9.11, u'time': u'2015-10-20'},
 {u'stock_price': 9.16, u'time': u'2015-10-21'},
 {u'stock_price': 9.08, u'time': u'2015-10-22'},
 {u'stock_price': 9.17, u'time': u'2015-10-23'},
 {u'stock_price': 9.28, u'time': u'2015-10-26'},
 {u'stock_price': 9.32, u'time': u'2015-10-27'},
 {u'stock_price': 9.29, u'time': u'2015-10-28'},
 {u'stock_price': 9.12, u'time': u'2015-10-29'},
 {u'stock_price': 9.12, u'time': u'2015-10-30'},
 {u'stock_price': 9.19, u'time': u'2015-11-02'},
 {u'stock_price': 9.02, u'time': u'2015-11-03'},
 {u'stock_price': 8.94, u'time': u'2015-11-04'},
 {u'stock_price': 9.46, u'time': u'2015-11-05'},
 {u'stock_price': 9.77, u'time': u'2015-11-06'},
 {u'stock_price': 10.03, u'time': u'2015-11-09'},
 {u'stock_price': 10.47, u'time': u'2015-11-10'},
 {u'stock_price': 10.32, u'time': u'2015-11-11'},
 {u'stock_price': 10.16, u'time': u'2015-11-12'},
 {u'stock_price': 10.04, u'time': u'2015-11-13'},
 {u'stock_price': 9.91, u'time': u'2015-11-16'},
 {u'stock_price': 9.99, u'time': u'2015-11-17'},
 {u'stock_price': 10.12, u'time': u'2015-11-18'},
 {u'stock_price': 10.05, u'time': u'2015-11-19'},
 {u'stock_price': 10.12, u'time': u'2015-11-20'},
 {u'stock_price': 10.16, u'time': u'2015-11-23'},
 {u'stock_price': 10.08, u'time': u'2015-11-24'},
 {u'stock_price': 9.94, u'time': u'2015-11-25'},
 {u'stock_price': 9.97, u'time': u'2015-11-26'},
 {u'stock_price': 9.9, u'time': u'2015-11-27'},
 {u'stock_price': 9.49, u'time': u'2015-11-30'},
 {u'stock_price': 9.5, u'time': u'2015-12-01'},
 {u'stock_price': 9.51, u'time': u'2015-12-02'},
 {u'stock_price': 10.13, u'time': u'2015-12-03'},
 {u'stock_price': 10.08, u'time': u'2015-12-04'},
 {u'stock_price': 9.81, u'time': u'2015-12-07'},
 {u'stock_price': 9.83, u'time': u'2015-12-08'},
 {u'stock_price': 9.68, u'time': u'2015-12-09'},
 {u'stock_price': 9.7, u'time': u'2015-12-10'},
 {u'stock_price': 9.68, u'time': u'2015-12-11'},
 {u'stock_price': 9.58, u'time': u'2015-12-14'},
 {u'stock_price': 9.77, u'time': u'2015-12-15'},
 {u'stock_price': 9.65, u'time': u'2015-12-16'},
 {u'stock_price': 9.62, u'time': u'2015-12-17'},
 {u'stock_price': 9.77, u'time': u'2015-12-18'},
 {u'stock_price': 9.9, u'time': u'2015-12-21'},
 {u'stock_price': 10.13, u'time': u'2015-12-22'},
 {u'stock_price': 10.06, u'time': u'2015-12-23'},
 {u'stock_price': 10.1, u'time': u'2015-12-24'},
 {u'stock_price': 9.99, u'time': u'2015-12-25'},
 {u'stock_price': 10.04, u'time': u'2015-12-28'},
 {u'stock_price': 9.7, u'time': u'2015-12-29'},
 {u'stock_price': 9.79, u'time': u'2015-12-30'}]
gt.get_risk()          # 获取总的风险指标

{u'__version': 101,
 u'algorithm_return': -0.09325970000000006,
 u'algorithm_volatility': 0.24686601869782554,
 u'alpha': -0.1264840086118137,
 u'annual_algo_return': -0.15531518517855092,
 u'annual_bm_return': -0.3516090579148625,
 u'benchmark_return': -0.22220450257590085,
 u'benchmark_volatility': 0.44370449985970895,
 u'beta': 0.17576502681840783,
 u'day_win_ratio': 0.42758620689655175,
 u'excess_return': -0.11649257671232882,
 u'information': 0.44992933161432286,
 u'lose_count': 9,
 u'max_drawdown': 0.19463270788918885,
 u'max_drawdown_period': [u'2015-06-08', u'2015-10-28'],
 u'max_leverage': 0.0,
 u'period_label': u'2015-12',
 u'profit_loss_ratio': 0.6243711570709893,
 u'sharpe': -0.79117890023424,
 u'sortino': -0.867468062186946,
 u'trading_days': 145,
 u'treasury_return': 0.02323287671232877,
 u'win_count': 4,
 u'win_ratio': 0.3076923076923077}
k = gt.get_risk()
k['max_drawdown_period'] = [(u'2015-04-16', u'2015-10-28')]
import pandas as pd 
pd.DataFrame(k)
.dataframe thead tr:only-child th { text-align: right; } .dataframe thead th { text-align: left; } .dataframe tbody tr th { vertical-align: top; }
__version algorithm_return algorithm_volatility alpha annual_algo_return annual_bm_return benchmark_return benchmark_volatility beta day_win_ratio ... max_drawdown_period max_leverage period_label profit_loss_ratio sharpe sortino trading_days treasury_return win_count win_ratio
0 101 -0.09326 0.246866 -0.126484 -0.155315 -0.351609 -0.222205 0.443704 0.175765 0.427586 ... (2015-04-16, 2015-10-28) 0.0 2015-12 0.624371 -0.791179 -0.867468 145 0.023233 4 0.307692

1 rows × 24 columns

gt.get_period_risks()  # 获取分月计算的风险指标

{'algorithm_return':          one_month  three_month  six_month  twelve_month
 2015-06   0.046864          NaN        NaN           NaN
 2015-07  -0.095654          NaN        NaN           NaN
 2015-08  -0.034687    -0.086112        NaN           NaN
 2015-09  -0.019135    -0.143727        NaN           NaN
 2015-10  -0.022087    -0.074071        NaN           NaN
 2015-11   0.049262     0.006454  -0.080214           NaN
 2015-12  -0.014183     0.011534  -0.133851           NaN,
 'algorithm_volatility':          one_month  three_month  six_month  twelve_month
 2015-06   0.251622          NaN        NaN           NaN
 2015-07   0.342315          NaN        NaN           NaN
 2015-08   0.136963     0.260242        NaN           NaN
 2015-09   0.344152     0.288331        NaN           NaN
 2015-10   0.169573     0.232747        NaN           NaN
 2015-11   0.247332     0.264006   0.261217           NaN
 2015-12   0.146573     0.191906   0.246264           NaN,
 'alpha':          one_month  three_month  six_month  twelve_month
 2015-06   0.735366          NaN        NaN           NaN
 2015-07  -0.475093          NaN        NaN           NaN
 2015-08  -0.364626    -0.227756        NaN           NaN
 2015-09  -0.105391    -0.363256        NaN           NaN
 2015-10  -1.751701    -0.283988        NaN           NaN
 2015-11   0.708999    -0.089500  -0.110792           NaN
 2015-12  -0.445724    -0.297888  -0.223360           NaN,
 'benchmark_return':          one_month  three_month  six_month  twelve_month
 2015-06  -0.075985          NaN        NaN           NaN
 2015-07  -0.146725          NaN        NaN           NaN
 2015-08  -0.117946    -0.304554        NaN           NaN
 2015-09  -0.048592    -0.283937        NaN           NaN
 2015-10   0.103383    -0.074048        NaN           NaN
 2015-11   0.009149     0.059371  -0.263264           NaN
 2015-12   0.055732     0.175534  -0.158244           NaN,
 'benchmark_volatility':          one_month  three_month  six_month  twelve_month
 2015-06   0.553131          NaN        NaN           NaN
 2015-07   0.605976          NaN        NaN           NaN
 2015-08   0.602886     0.579502        NaN           NaN
 2015-09   0.341508     0.528661        NaN           NaN
 2015-10   0.254009     0.435778        NaN           NaN
 2015-11   0.303270     0.303330   0.470614           NaN
 2015-12   0.242035     0.265819   0.424935           NaN,
 'beta':          one_month  three_month  six_month  twelve_month
 2015-06   0.077529          NaN        NaN           NaN
 2015-07   0.266485          NaN        NaN           NaN
 2015-08   0.022695     0.132428        NaN           NaN
 2015-09   0.296257     0.170775        NaN           NaN
 2015-10   0.446108     0.118918        NaN           NaN
 2015-11   0.317140     0.320417   0.170118           NaN
 2015-12   0.315107     0.332873   0.204439           NaN,
 'information':          one_month  three_month  six_month  twelve_month
 2015-06   2.409919          NaN        NaN           NaN
 2015-07   0.941784          NaN        NaN           NaN
 2015-08   1.491993     1.626420        NaN           NaN
 2015-09   0.940981     1.156385        NaN           NaN
 2015-10  -9.504728    -0.151490        NaN           NaN
 2015-11   1.459239    -0.722447   0.805395           NaN
 2015-12  -3.836540    -2.618727  -0.007429           NaN,
 'max_drawdown':          one_month  three_month  six_month  twelve_month
 2015-06   0.037352          NaN        NaN           NaN
 2015-07   0.095654          NaN        NaN           NaN
 2015-08   0.060297     0.177451        NaN           NaN
 2015-09   0.082616     0.145535        NaN           NaN
 2015-10   0.063563     0.103676        NaN           NaN
 2015-11   0.057452     0.103676   0.194633           NaN
 2015-12   0.032795     0.085027   0.163384           NaN,
 'sharpe':          one_month  three_month  six_month  twelve_month
 2015-06   2.722326          NaN        NaN           NaN
 2015-07  -2.058756          NaN        NaN           NaN
 2015-08  -2.797356    -1.278522        NaN           NaN
 2015-09  -0.739650    -1.715168        NaN           NaN
 2015-10  -1.886834    -1.384793        NaN           NaN
 2015-11   2.962136    -0.045016  -0.751448           NaN
 2015-12  -1.295178     0.046603  -1.183779           NaN,
 'sortino':          one_month  three_month  six_month  twelve_month
 2015-06   5.663754          NaN        NaN           NaN
 2015-07  -4.056391          NaN        NaN           NaN
 2015-08  -3.296274    -1.742154        NaN           NaN
 2015-09  -0.346371    -1.393109        NaN           NaN
 2015-10  -3.025377    -1.032753        NaN           NaN
 2015-11   4.867143    -0.049848  -0.845587           NaN
 2015-12  -1.578239     0.076382  -1.182389           NaN}
gt.get_period_risks()['alpha'] # 获取分月计算的风险指标中的alpha
.dataframe thead tr:only-child th { text-align: right; } .dataframe thead th { text-align: left; } .dataframe tbody tr th { vertical-align: top; }
one_month three_month six_month twelve_month
2015-06 0.735366 NaN NaN NaN
2015-07 -0.475093 NaN NaN NaN
2015-08 -0.364626 -0.227756 NaN NaN
2015-09 -0.105391 -0.363256 NaN NaN
2015-10 -1.751701 -0.283988 NaN NaN
2015-11 0.708999 -0.089500 -0.110792 NaN
2015-12 -0.445724 -0.297888 -0.223360 NaN

如有任何疑问，请咨询聚宽官方人员。

聚宽(JoinQuant)因你而多彩, 感谢有你~~~

       

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