gs_quant.timeseries.technicals.smoothed_moving_average

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

Smoothed 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

A modified moving average (MMA), running moving average (RMA), or smoothed moving average (SMMA) is defined as:

\(P_{MM,today} = \frac{(N-1)P_{MM,yesterday} + P_today}{N}\)

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

See Modified moving average for more information

Examples

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

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

See also

mean() :func:’moving_average’