def main():
initial_risk = 0.03
start_date = str_to_date('2010-01-01')
end_date = str_to_date('2011-12-31')
# Use the preset daily data provider
data_provider = daily_data_provider
# ----- build trading session ----- #
session_builder = container.resolve(BacktestTradingSessionBuilder) # type: BacktestTradingSessionBuilder
session_builder.set_backtest_name('Moving Average Alpha Model Backtest')
session_builder.set_position_sizer(InitialRiskPositionSizer, initial_risk=initial_risk)
session_builder.set_contract_ticker_mapper(DummyTickerMapper())
session_builder.set_commission_model(IBCommissionModel)
session_builder.set_data_provider(data_provider)
session_builder.set_frequency(Frequency.DAILY)
ts = session_builder.build(start_date, end_date)
# ----- build models ----- #
model = MovingAverageAlphaModel(fast_time_period=5, slow_time_period=20, risk_estimation_factor=1.25,
data_handler=ts.data_handler)
model_tickers = [DummyTicker('AAA'), DummyTicker('BBB'), DummyTicker('CCC'),
DummyTicker('DDD'), DummyTicker('EEE'), DummyTicker('FFF')]
model_tickers_dict = {model: model_tickers}
# ----- preload price data ----- #
ts.use_data_preloading(model_tickers)
# Verify the checksum of preloaded data with the precomputed value
ts.verify_preloaded_data("e73eed1f125ff6afa2cdc95957a703a999f41d34")
# ----- start trading ----- #
AlphaModelStrategy(ts, model_tickers_dict, use_stop_losses=True)
ts.start_trading()
def setUpClass(cls):
cls.initial_cash = 1000000 # 1M
cls.contract = Contract('AAPL US Equity',
security_type='STK',
exchange='NYSE')
cls.contract_size = 75
cls.fut_contract = Contract('CTZ9 Comdty',
security_type='FUT',
exchange='CME',
contract_size=cls.contract_size)
tickers = [
DummyTicker(cls.contract.symbol),
DummyTicker(cls.fut_contract.symbol)
]
cls.prices_series = QFSeries(data=[120, 250], index=tickers)
cls.prices_up = QFSeries(data=[130, 270], index=tickers)
cls.prices_down = QFSeries(data=[100, 210], index=tickers)
cls.start_time = str_to_date('2017-01-01')
cls.random_time = str_to_date('2017-02-02')
cls.end_time = str_to_date('2018-02-03')
cls.trades_generator = TradesGenerator()
def get_portfolio_and_data_handler(self):
data_handler = Mock(spec=DataHandler)
data_handler.get_last_available_price.side_effect = lambda tickers: self.data_handler_prices[tickers] \
if tickers else None
contract_mapper = Mock(spec=ContractTickerMapper)
contract_mapper.contract_to_ticker.side_effect = lambda contract: DummyTicker(
contract.symbol)
timer = SettableTimer()
timer.set_current_time(self.start_time)
portfolio = Portfolio(data_handler, self.initial_cash, timer,
contract_mapper)
return portfolio, data_handler, timer
def main():
# settings
backtest_name = 'Simple MA Strategy Demo'
start_date = str_to_date("2010-01-01")
end_date = str_to_date("2015-03-01")
ticker = DummyTicker("AAA")
# configuration
session_builder = container.resolve(BacktestTradingSessionBuilder) # type: BacktestTradingSessionBuilder
session_builder.set_frequency(Frequency.DAILY)
session_builder.set_backtest_name(backtest_name)
session_builder.set_data_provider(daily_data_provider)
ts = session_builder.build(start_date, end_date)
OnBeforeMarketOpenSignalGeneration(SimpleMAStrategy(ts, ticker))
ts.start_trading()
def main():
initial_risk = 0.03
start_date = str_to_date('2010-01-01')
end_date = str_to_date('2011-12-31')
# Use the preset daily data provider
data_provider = daily_data_provider
# ----- build trading session ----- #
session_builder = container.resolve(
BacktestTradingSessionBuilder) # type: BacktestTradingSessionBuilder
session_builder.set_backtest_name('Moving Average Alpha Model Backtest')
session_builder.set_position_sizer(InitialRiskPositionSizer,
initial_risk=initial_risk)
session_builder.set_commission_model(IBCommissionModel)
session_builder.set_data_provider(data_provider)
session_builder.set_frequency(Frequency.DAILY)
ts = session_builder.build(start_date, end_date)
# ----- build models ----- #
model = MovingAverageAlphaModel(fast_time_period=5,
slow_time_period=20,
risk_estimation_factor=1.25,
data_provider=ts.data_handler)
model_tickers = [
DummyTicker('AAA'),
DummyTicker('BBB'),
DummyTicker('CCC'),
DummyTicker('DDD'),
DummyTicker('EEE'),
DummyTicker('FFF')
]
model_tickers_dict = {model: model_tickers}
# ----- preload price data ----- #
ts.use_data_preloading(model_tickers)
# Verify the checksum of preloaded data with the precomputed value
ts.verify_preloaded_data("778bbaac65cb0a5a848167999b88cf29a1cd8467")
# ----- start trading ----- #
strategy = AlphaModelStrategy(ts, model_tickers_dict, use_stop_losses=True)
# Set the signal generation and orders placement to be performed at the OnBeforeMarketOpen event
OnBeforeMarketOpenSignalGeneration(strategy)
ts.start_trading()
def main():
# settings
backtest_name = 'Intraday MA Strategy Demo'
start_date = str_to_date("2019-07-01")
end_date = str_to_date("2019-10-01")
ticker = DummyTicker("AAA")
setup_logging(logging.INFO, console_logging=True)
OnNewBarEvent.set_frequency(Frequency.MIN_15)
OnNewBarEvent.set_start_and_end_time({"hour": 10, "minute": 0, "second": 0, "microsecond": 0},
{"hour": 13, "minute": 0, "second": 0, "microsecond": 0})
# configuration
session_builder = container.resolve(BacktestTradingSessionBuilder) # type: BacktestTradingSessionBuilder
session_builder.set_frequency(Frequency.MIN_1)
session_builder.set_backtest_name(backtest_name)
session_builder.set_data_provider(intraday_data_provider)
ts = session_builder.build(start_date, end_date)
OnNewBarSignalGeneration(IntradayMAStrategy(ts, ticker))
ts.start_trading()
def _acquire_data(input_file: str):
data_frame = read_csv(input_file, parse_dates=['dates'])
# The data_frame contains following headers: dates, open, high, low, close, volume, ticker.
dates = data_frame['dates'].drop_duplicates()
tickers = [DummyTicker(t) for t in data_frame['tickers'].unique()]
# The columns in the csv file are in the exactly same order as the corresponding fields in the list below
fields = PriceField.ohlcv()
# Create a data array
data_array = data_frame.set_index(['dates', 'tickers']).stack().to_xarray()
# Construct a QFDataArray based on the data_array and sort it by the 'dates' coordinate
data = QFDataArray.create(dates=dates,
tickers=tickers,
fields=fields,
data=data_array).sortby('dates')
start_date = dates.iloc[0]
end_date = dates.iloc[-1]
return data, start_date, end_date
def contract_to_ticker(self,
contract: Contract,
strictly_to_specific_ticker=True) -> Ticker:
return DummyTicker(ticker=contract.symbol)