backtest

Available parameters

strategy : str or an instance of fastquant.strategies.base.BaseStrategy see list of accepted strategy keys below
data : pandas.DataFrame dataframe with at least close price indexed with time
commission : float commission per transaction [0, 1] (default 0.0075)
init_cash : float initial cash (currency implied from data) (default 100000)
plot : bool show plot backtrader (disabled if strategy=="multi")
verbose : int Verbose can take values: [0, 1, 2, 3], with increasing levels of verbosity (default=1).
sort_by : str sort result by given metric (default='rnorm')
sentiments : pandas.DataFrame df of sentiment [0, 1] indexed by time (applicable if strategy=='senti')
strats : dict dictionary of strategy parameters (applicable if strategy=='multi')
return_history : bool return history of transactions (i.e. buy and sell timestamps) (default=False)
return_plot: bool return the plot (if you want to save the plot) (default=False)
channel : str Channel to be used for notifications - e.g. "slack" (default=None)
symbol : str Symbol to be referenced in the channel notification if not None (default=None)
allow_short : bool Whether to allow short selling, with max set as short_max times the portfolio value (default=False)
short_max : float The maximum short position allowable as a ratio relative to the portfolio value at that time point (default=1.5)
figsize : tuple The size of the figure to be displayed at the end of the backtest (default=(30, 15))
data_class : bt.feed.DataBase Custom backtrader database to be used as a parent class instead bt.feed. (default=None)
data_kwargs : dict Datafeed keyword arguments (empty dict by default)

Strategies

List of accepted strategy keys are

Strategy	Alias	Parameters
Relative Strength Index (RSI)	rsi	`rsi_period`, `rsi_upper`, `rsi_lower`
Simple moving average crossover (SMAC)	smac	`fast_period`, `slow_period`
Exponential moving average crossover (EMAC)	emac	`fast_period`, `slow_period`
Moving Average Convergence Divergence (MACD)	macd	`fast_perod`, `slow_upper`, `signal_period`, `sma_period`, `sma_dir_period`
Bollinger Bands	bbands	`period`, `devfactor`
Buy and Hold	buynhold	`N/A`
Sentiment Strategy	sentiment	`keyword` , `page_nums`, `senti`
Custom Prediction Strategy	custom	`upper_limit`, `lower_limit`, `custom_column`
Custom Ternary Strategy	ternary	`buy_int`, `sell_int`, `custom_column`

Examples

Return history

from fastquant import backtest
res, hist = backtest(..., return_history=True)

Return plot

from fastquant import backtest
res, plot = backtest(..., return_plot=True)

# Save plot
plot.savefig('example.png')

Return history and plot

from fastquant import backtest
res, hist, plot = backtest(..., return_history=True, return_plot=True,

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

Uh oh!