Trend-Following Filters – Part 5

By |February 15th, 2022|Research Insights, Trend Following, Trend-Following Course, Guest Posts|

There are two general types of Kalman filter models: steady-state and adaptive. A steady-state filter assumes that the statistics of the process under consideration are constant over time, resulting in fixed, time-invariant filter gains. The gains of an adaptive filter, on the other hand, are able to adjust to processes that have time-varying dynamics, such as financial time series which typically display volatility and non-stationarity.

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