gs_quant.timeseries.statistics.zscores

zscores(x, w=<gs_quant.timeseries.helper.Window object>)

Rolling z-scores over a given window

Parameters:

• x (Series) – time series of prices

• w (Union[Window, int, str]) – Window or int: size of window and ramp up to use. e.g. Window(22, 10) where 22 is the window size and 10 the ramp up value. If w is a string, it should be a relative date like ‘1m’, ‘1d’, etc. Window size defaults to length of series.

Return type:

Series

Returns:

timeseries of z-scores

Usage

Calculate standard score of each value in series over given window. Standard deviation and sample mean are computed over the specified rolling window, then element is normalized to provide a rolling z-score:

\(R_t = \frac { X_t - \mu }{ \sigma }\)

Where \(\mu\) and \(\sigma\) are sample mean and standard deviation over the given window

If window is not provided, computes z-score relative to mean and standard deviation over the full series

Examples

Generate price series and compute z-score of returns over \(22\) observations

>>> prices = generate_series(100)
>>> zscores(returns(prices), 22)

See also

mean() std()