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The Journal of Portfolio Management

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Improving Risk Forecasts Through Cross-Sectional Observations

Jose Menchero and Andrei Morozov
The Journal of Portfolio Management Spring 2015, 41 (3) 84-96; DOI: https://doi.org/10.3905/jpm.2015.41.3.084
Jose Menchero
is CEO of Menchero Portfolio Analytics Consulting in San Francisco, CA.
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  • For correspondence: jose@mencheropac.com
Andrei Morozov
is executive director at MSCI Barra in Berkeley, CA.
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  • For correspondence: andrei.morozov@mscibarra.com
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Abstract

Volatility forecasting requires a delicate balance between two opposing effects. On the one hand, we should give more weight to recent observations, because they contain the most relevant data. On the other hand, giving too much weight to recent observations leads to undesirable increases in sampling error. In this article, the authors study how to optimally balance these two effects. Central to this challenge is the identification of a reliable measure of risk forecasting accuracy. We The authors examine several widely used measures, highlighting serious shortcomings in some of the approaches as well as introduceing a new technique for volatility estimation that refines traditional volatility forecasts by incorporating cross-sectional observations. The authors show that our their technique improves the accuracy of risk forecasts. We They argue that our their cross-sectional technique permits placing more weight on recent observations while mitigating the detrimental effects of sampling error.

TOPICS: Analysis of individual factors/risk premia, portfolio management/multi-asset allocation

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The Journal of Portfolio Management: 41 (3)
The Journal of Portfolio Management
Vol. 41, Issue 3
Spring 2015
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Improving Risk Forecasts Through Cross-Sectional Observations
Jose Menchero, Andrei Morozov
The Journal of Portfolio Management Apr 2015, 41 (3) 84-96; DOI: 10.3905/jpm.2015.41.3.084

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Improving Risk Forecasts Through Cross-Sectional Observations
Jose Menchero, Andrei Morozov
The Journal of Portfolio Management Apr 2015, 41 (3) 84-96; DOI: 10.3905/jpm.2015.41.3.084
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  • Article
    • Abstract
    • EVALUATING THE ACCURACY OF RISK FORECASTS
    • EMPIRICAL DATA
    • EMPIRICAL COMPARISON
    • CONCLUSION
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