def get_pnl_trades(self):
"""Gets P&L of each individual trade per signal
Returns
-------
pandas.Dataframe
"""
if self._pnl_trades is None:
calculations = Calculations()
self._pnl_trades = calculations.calculate_individual_trade_gains(self._signal, self._pnl)
return self._pnl_trades
def get_pnl_trades(self):
"""
get_pnl_trades - Gets P&L of each individual trade per signal
Returns
-------
pandas.Dataframe
"""
if self._pnl_trades is None:
calculations = Calculations()
self._pnl_trades = calculations.calculate_individual_trade_gains(self._signal, self._pnl)
return self._pnl_trades
spot_df = asset_df
logger.info("Running backtest...")
# use technical indicator to create signals
# (we could obviously create whatever function we wanted for generating the signal dataframe)
tech_ind = TechIndicator()
tech_ind.create_tech_ind(spot_df, indicator, tech_params); signal_df = tech_ind.get_signal()
# use the same data for generating signals
backtest.calculate_trading_PnL(br, asset_df, signal_df)
port = backtest.get_cumportfolio()
port.columns = [indicator + ' = ' + str(tech_params.sma_period) + ' ' + str(backtest.get_portfolio_pnl_desc()[0])]
signals = backtest.get_porfolio_signal() # get final signals for each series
returns = backtest.get_pnl() # get P&L for each series
calculations = Calculations()
trade_returns = calculations.calculate_individual_trade_gains(signals, returns)
print(trade_returns)
# print the last positions (we could also save as CSV etc.)
print(signals.tail(1))
style = Style()
style.title = "EUR/USD trend model"
style.source = 'Quandl'
style.scale_factor = 1
style.file_output = 'eurusd-trend-example.png'
Chart(port, style = style).plot()
tech_ind = TechIndicator()
tech_ind.create_tech_ind(spot_df, indicator, tech_params)
signal_df = tech_ind.get_signal()
# use the same data for generating signals
backtest.calculate_trading_PnL(br, asset_df, signal_df)
port = backtest.portfolio_cum()
port.columns = [
indicator + ' = ' + str(tech_params.sma_period) + ' ' +
str(backtest.portfolio_pnl_desc()[0])
]
signals = backtest.portfolio_signal() # get final signals for each series
returns = backtest.pnl() # get P&L for each series
calculations = Calculations()
trade_returns = calculations.calculate_individual_trade_gains(
signals, returns)
print(trade_returns)
# print the last positions (we could also save as CSV etc.)
print(signals.tail(1))
style = Style()
style.title = "EUR/USD trend model"
style.source = 'Quandl'
style.scale_factor = 1
style.file_output = 'eurusd-trend-example.png'
Chart(port, style=style).plot()
