margot.data.features.finance¶

class margot.data.features.finance.SimpleReturns(column: str, *args, **kwargs)¶

Simple returns are the percent change from yesterdays close to today’s close.

Internal implementation:

return series.pct_change().fillna(0)

class margot.data.features.finance.LogReturns(column: str, *args, **kwargs)¶

Log returns can be summed over time.

Internal implementation:

return np.log(1 + series.pct_change().fillna(0))

class margot.data.features.finance.RealisedVolatility(column: str, *args, **kwargs)¶

Realised volatility measures the variability of returns over a lookback window.

Internal implementation:

return series.rolling(window).std() * np.sqrt(252)

Parameters

Raises

AttributeError – A lookback window is required.

class margot.data.features.finance.SimpleMovingAverage(column: str, *args, **kwargs)¶

Simple moving average of lookback window.

Internal implementation:

return series.rolling(window).mean()

Parameters

get_label()¶

Return the label for this feature.

Override this to customise.

class margot.data.features.finance.UpperBollingerBand(column: str, *args, **kwargs)¶

Upper bollinger band with window and standard deviation.

Internal implementation:

return series.rolling(window).mean() +
        series.rolling(self.window).mean().std() *
            self.width

Parameters

class margot.data.features.finance.LowerBollingerBand(column: str, *args, **kwargs)¶

Lower bollinger band of window and standard deviation.

Internal implementation:

return series.rolling(window).mean() -
        series.rolling(self.window).mean().std() *
            self.width

Parameters