A volatility estimate that gives more weight to recent observations, with weights decaying geometrically. A single decay factor controls how quickly old data fade.
Where you will meet it
EWMA comes up in 5 learning outcome notes across the FRM syllabus.
A few of them:
Measuring and Monitoring Volatility FRM Part I · Valuation and risk models
“EWMA weights decline geometrically by a decay factor λ, so recent data count most and shocks fade smoothly, but there is no long-run level to revert to.”
Validating Bank Holding Companies’ Value-at-Risk Models for Market Risk FRM Part II · Market risk measurement and management
“Examples are the confidence level, the holding period, the data window, the EWMA decay factor, the correlation matrix and the volatility estimate.”
Measuring and Monitoring Volatility FRM Part I · Valuation and risk models
“The EWMA model updates variance in one step.”
Measuring and Monitoring Volatility FRM Part I · Valuation and risk models
“EWMA is the special case in which ω is zero and α + β is 1, so it has no long-run level.”
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