Areix-IO 0.1.1

Areix IO Backtesting Framework

Areix IO (Alpha Test)

Installation

Create a virtual environment

virtualenv venv --python=python3

Activate the virtual environment

# Macbook / Linus
source venv/bin/activate 

# Windows
venv/Scripts/activate

Deactivate

deactivate

Install Areix-IO package

pip install Areix-IO

Usage

import areix_io as aio
from areix_io.utils import create_report_folder, SideType

class MyStrategy(aio.Strategy):
    def initialize(self):
        self.info('initialize')
        for k,df in self.ctx.feed.items():
            df['ma5'] = df.close.rolling(5).mean()
            df['ma10'] = df.close.rolling(10).mean()
            df['ma20'] = df.close.rolling(20).mean()
    
    def before_trade(self, order):
        return True

    def on_order_ok(self, order):
        # self.info(f'submit order successfully: {order}')
        pass

    def on_market_start(self):
        # self.info('on_market_start')
        pass

    def on_market_close(self):
        # self.info('on_market_close')
        pass

    def on_order_timeout(self, order):
        # self.info(f'on_order_timeout. Order: {order}')
        pass

    def finish(self):
        self.info('finish')

    def on_bar(self, tick):
        bar_data = self.ctx.bar_data # The bar data at the tick
        hist_data = self.ctx.hist_data # The historical bar data until the tick

        for code, hist in bar_data.items():

            if hist['ma5'] > 1.03 * hist['ma20']:
                self.order_lotsize(code, lots=1, side=SideType.BUY, ioc=True)
                self.info(f"BUY created {bar_data[code]['lot_size']} {code} @ {bar_data[code]['close']} at {tick}")

            if hist['ma5'] < 0.98 * hist['ma20'] and code in self.ctx.position:
                self.order_lotsize(code, lots=1, side=SideType.SELL, ioc=True)
                self.info(f"SELL created {bar_data[code]['lot_size']} {code} @ {bar_data[code]['close']} at {tick}")

Run your strategy:

aio.set_token('xxxxxx') # Only need to run once
base = create_report_folder()
start_date = '2019-10-13'
end_date = '2021-02-03'

sdf = aio.StockDataFeed(
    symbols=['0700.HK', '0005.HK', '^HSI'], 
    start_date=start_date, 
    end_date=end_date,  
    # period= '1y', 
    interval='1d', 
    order_ascending=True, 
    store_path=base,
)
feed, idx = sdf.fetch_data()
benchmark = feed.pop('^HSI')

mytest = aio.BackTest(
    feed, 
    MyStrategy, 
    commission_rate=0.0017, 
    min_commission=40, 
    trade_at='close', 
    benchmark=benchmark, 
    cash=1000000, 
    tradedays=idx, 
    store_path=base,
    slippage=0.0,
    allow_ss=False
)

mytest.start()

Retrieve statistic results:

prefix = ''

mytest.export_json(f'{prefix}trade_records.json', mytest.ctx.trade_records)
mytest.export_csv(f'{prefix}trade_records.csv', mytest.ctx.trade_records)
mytest.export_csv(f'{prefix}order_records.csv', mytest.ctx.order_records)
mytest.export_csv(f'{prefix}closed_trade_records.csv', mytest.ctx.closed_trade_records)
mytest.export_json(f'{prefix}pnls.json', mytest.ctx.pnls)
mytest.export_csv(f'{prefix}pnls.csv', mytest.ctx.pnls)

print('-----------'*10)
stats = mytest.ctx.statistic.stats(pprint=True, annualization=252, risk_free=0.0442)
print(stats)
mytest.export_csv(f'{prefix}result.csv', stats, index=True)

df= mytest.ctx.statistic.df
mytest.export_csv(f'{prefix}statistic.csv', df, index=True)

mytest.plot(f'{base}/{prefix}report.png', interactive=False)
mytest.plot(f'{base}/{prefix}report.html', interactive=True)

start                                               2019-10-14 00:00:00
end                                                 2021-02-03 00:00:00
duration                                              478 days 00:00:00
beginning_balance                                               1000000
ending_balance                                           1634230.874058
total_net_profit                                          634230.874058
gross_profit                                             3046941.081667
gross_loss                                              -2412710.207609
profit_factor                                                  1.262871
return_on_initial_capital                                      0.634231
annualized_return                                              0.463524
total_return                                                   0.634231
max_return                                                     0.701701
min_return                                                    -0.116135
number_trades                                                        99
number_winning_trades                                                21
number_losing_trades                                                 17
win_ratio                                                      0.212121
loss_ratio                                                     0.171717
avg_profit_per_trade                                        3032.923087
trading_period                                 1 years 3 months 20 days
avg_daily_pnl                                               1957.502698
avg_daily_pnl(%)                                               0.001729
avg_weekly_pnl                                              9326.924619
avg_weekly_pnl(%)                                              0.007731
avg_monthly_pnl                                            39639.429629
avg_monthly_pnl(%)                                             0.033727
avg_quarterly_pnl                                         126993.756593
avg_quarterly_pnl(%)                                           0.111005
avg_annualy_pnl                                           317484.391481
avg_annualy_pnl(%)                                             0.279107
sharpe_ratio                                                   1.197033
sortino_ratio                                                  2.014487
annualized_volatility                                          0.327517
information_ratio                                              0.077989
omega_ratio                                                    0.009424
downside_risk                                                  0.216255
beta                                                           0.852260
alpha                                                         -0.727623
calmar_ratio                                                   2.754151
tail_ratio                                                     1.144190
stability_of_timeseries                                        0.781261
max_drawdown                                                   0.168300
max_drawdown_period          (2020-11-05 00:00:00, 2020-12-28 00:00:00)
max_drawdown_duration                                  53 days 00:00:00