FRM Part I · FRM Exam Part I · Measuring and Monitoring Volatility
A risk manager builds an EWMA covariance matrix for many risk factors. Which design choice ensures the resulting matrix is positive semi-definite, so that portfolio variances can never be negative?
Use the same decay factor λ for all variances and covariances. A common λ makes the EWMA matrix a weighted sum of return outer products, which is positive semi-definite. Pair-specific decay factors or mismatched windows can break this and produce negative portfolio variances.
- AUse the same decay factor λ for every variance and covariance elementCorrect
- BChoose a separate λ for each pair to best fit that pair's history
- CUse a longer window for covariances than for variances
- DEstimate each correlation separately and then combine them with the volatilities
Explanation
With a single common λ, the matrix is a weighted sum of outer products of return vectors, which guarantees positive semi-definiteness. Pair-specific decay factors or mismatched windows can produce matrices with negative eigenvalues and hence possibly negative portfolio variances.
Did you get it right without looking?
One question tells you little. A timed set on Measuring and Monitoring Volatility shows your real accuracy, how long you take and where you lose marks.
More Measuring and Monitoring Volatility questions
- Over the past year, equity index options with a strike 10% below spot have had implied volatilities of 28%, while at-the-money options have …
- Daily returns have a standard deviation of 1.00% and a first-order autocorrelation of +0.25, with no higher-order autocorrelation. What is t…
- Which statement about implied volatility versus historical volatility is correct?
- Which statement about the parameters of a GARCH(1,1) model is correct?
- An analyst estimates daily volatility from five observed daily log returns: +1%, -2%, +3%, 0%, -2%. Assuming the true mean is zero, the anal…
- The daily log returns of a portfolio are assumed i.i.d. with a standard deviation of 1.2% per day. Using the square-root-of-time rule with 2…