Forecasting with Exponential Moving Averages

purpose

forecasting

smoothing

dataset

Mahanadi river flow

Buffalo snow

VIX

synthetic

α

0.5

optimum α for forecast

mse = 1.63210

For stationary or nearly stationary data, the exponential moving average is a simple method for time-series forecasting. Choose between forecasting and smoothing to see the difference between them;

α

is the smoothing parameter in the exponential moving average and

mse

is the mean square error between the forecast (red curve) and actual values of the data (blue curve). Larger values of

α

cause less smoothing.