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Abstract
Many traditional approaches to forecasting volatility have shortcomings related to sampling error and other limitations. Jose Menchero , CEO of Menchero Portfolio Analytics Consulting , and Andrei Morozov, Executive Director at MSCI in Berkeley, California, offer a new approach that uses cross-sectional observations to produce more timely and accurate forecasts. This report discusses statistical measures for risk forecasting.
“Volatility forecasting is a challenging task,” Menchero says. “For instance, risk models tend to under-forecast volatility during times of financial crisis, while they over-forecast volatility after the crisis subsides. Our cross-sectional technique mitigates these biases by assigning more weight to recent observations without incurring a high penalty in sampling error.”
TOPICS: Analysis of individual factors/risk premia, portfolio management/multi-asset allocation
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Don’t have access? Click here to request a demo
Alternatively, Call a member of the team to discuss membership options
US and Overseas: +1 646-931-9045
UK: 0207 139 1600