gs_quant.timeseries.technicals.moving_average

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

Moving average over specified 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:

date-based time series of return

Usage

Simple arithmetic moving average over the specified window (number of observations). Shorter windows will be more reactive to changes in the asset price, but more volatile. Larger windows will be smoother but less reactive to near term changes in asset prices.

\(R_t = \frac{\sum_{i=t-w+1}^{t} X_t}{N}\)

where N is the number of observations in each rolling window, \(w\). If window is not provided, computes rolling mean over the full series

Equivalent to mean

Examples

Generate price series with 100 observations starting from today’s date:

>>> prices = generate_series(100)
>>> moving_average(prices, 22)

See also

mean()