Example #1
0
def MakeDataToCsv():
    '''
    生成沪深300的股票数据到指定的文件夹
    :return:
    '''
    stockList = mt_read_index_codes('000300.SH')
    stockList = list(map(lambda x: x.split(".")[0], stockList))
    stockList = list(map(mt_add_suffix_name, stockList))
    count = 0
    resultTemp = pd.DataFrame()
    for stock in stockList:
        df = QAStock2btData(stock, '2010-01-01', '2020-10-10')
        df = IndicateBias(df, 20, 60, 120)
        df = IndicatePctChange(df, 1)
        df = IndicatePctChange(df, 3)
        df = IndicatePctChange(df, 5)
        df = IndicatePctChange(df, 10)
        df = IndicatePctChange(df, 20)
        df = IndicatePctChange(df, 60)
        df = IndicatePctChange(df, 120)
        df = IndicatePctChange(df, 1, True)
        df = IndicatePctChange(df, 3, True)
        df = IndicatePctChange(df, 5, True)
        df = IndicatePctChange(df, 10, True)
        df = IndicatePctChange(df, 20, True)

        df = IndicateBias(df, 20, 60, 120)
        df.to_csv('./selectStock/' + stock + '.csv')
        count += 1
        print("current code is :%s" % stock)
        resultTemp = pd.concat([resultTemp, df])
        if count > 5000:
            break
Example #2
0
def runstrat():
    args = parse_args()

    cerebro = bt.Cerebro(cheat_on_open=True)
    cerebro.broker.setcommission(commission=0.0012, stocklike=True)
    # cerebro.broker.set_coo(True)

    # Data feed kwargs
    # '15min', '30min', '60min',
    # dataframe = read_dataframe(args.data, args.years, ['15min', '60min', 'd'])
    # dataframe = readFromDb(args.data, args.fq, args.years, ["5min", '15min', '60min', 'd'])
    # dataframe = readFromDb(args.data, args.fq, args.years, ['d'])
    # for i in range(len(dataframe)):
    #     cerebro.adddata(bt.feeds.PandasData(dataname=dataframe[i]))

    # for i in range(len(dataframe)):
    #     temp_df = macd_extend_data(dataframe[i])
    #     cerebro.adddata(pandas_divergence(dataname=temp_df,
    #                                       divergence_top=temp_df.columns.to_list().index('divergence_top'),
    #                                       divergence_bottom=temp_df.columns.to_list().index('divergence_bottom')))

    # dataframe = QAIndex2btData("159934", '2014-01-01', '2020-10-13')
    dataframe = QAStock2btData("000002", '2008-01-01', '2021-04-30')
    # dataframe = read_dataframe('000651.csv', '2014-2020', ['d'])[0]
    cerebro.adddata(bt.feeds.PandasData(dataname=dataframe))

    cerebro.addstrategy(lnkyzhangSt)
    # cerebro.addstrategy(MacdDivergenceSt)
    # cerebro.addstrategy(LeiGoneSt)

    cerebro.addanalyzer(bt.analyzers.DrawDown, _name='DrawDown')
    cerebro.addanalyzer(bt.analyzers.AnnualReturn, _name='AnnualReturn')

    cerebro.addanalyzer(bt.analyzers.PyFolio, _name='pyfolio')

    strat = cerebro.run(stdstats=True, runonce=False)

    drawDown = strat[0].analyzers.DrawDown.get_analysis()
    print("max drawdown: %f", drawDown.max.drawdown)
    annualReturn = strat[0].analyzers.AnnualReturn.get_analysis()
    print("annualReturn: %s", annualReturn)

    pyfoliozer = strat[0].analyzers.getbyname('pyfolio')
    returns, positions, transactions, gross_lev = pyfoliozer.get_pf_items()

    transactions.to_csv("transtion.csv")
    if args.plot:
        # cerebro.plot(style='line')
        cerebro.plot(style='candle', iplot=False)
def MakeDataToCsv():
    '''
    生成沪深300的股票数据到指定的文件夹
    :return:
    '''
    stockList = mt_read_index_codes('000300.SH')
    stockList = list(map(lambda x: x.split(".")[0], stockList))
    stockList = list(map(mt_add_suffix_name, stockList))
    count = 0
    resultTemp = pd.DataFrame()
    for stock in stockList:
        df = QAStock2btData(stock, '2010-01-01', '2020-10-10')
        df_indBias = IndicateBias(df, 20, 60, 120)
        df = stopPriceStatistic(df)
        df = df.merge(df_indBias[["s_bias", "m_bias", "l_bias"]],
                      left_on="startDate",
                      right_index=True)
        df.to_csv('./analysisData/' + stock + '.csv')
        count += 1
        print("current code is :%s" % stock)
        resultTemp = pd.concat([resultTemp, df])
        if count > 5000:
            break
Example #4
0
# # Create a calendar
# sse = mcal.get_calendar('SSE', open_time=time(9, 30), close_time=time(15, 00))
# print(sse.tz.zone)
# print('open, close: %s, %s' % (sse.open_time, sse.close_time))
# # Show available calendars
# # print(mcal.get_calendar_names())
# early = sse.schedule(start_date='2000-01-01', end_date='2000-04-10')
#
# print(early)
#
from BackTraderTest.BackTraderFunc.makeData import QAStock2btData
from matplotlib import pyplot as plt
import sympy

dataframe = QAStock2btData("000651", '2012-01-01', '2029-01-13')


# 测试natr
# a = ta.ATR(dataframe.high, dataframe.low, dataframe.close)
# ema20 = ta.EMA(dataframe.close)
#
# a = a / ema20

upperband, middleband, lowerband = ta.BBANDS(dataframe.close,timeperiod=20)
real = (upperband - lowerband) / middleband


fig, ax = plt.subplots(figsize=(10, 7))
ax.hist(real, bins=20, rwidth=0.5)
ax.set_title("Simple Histogram")