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Forecasting long-horizon volatility for strategic asset allocation

Journal

Journal of Portfolio Management

Subject

Finance

Publishing details

Journal of Portfolio Management 2021 Vol 47:4 p 83-98

Authors / Editors

Cardinale M;Naik N Y;Sharma V

Biographies

Narayan Naik

Publication Year

2021

Abstract

Long-term volatility is a key forecasting input for strategic asset allocation analysis, yet most studies on volatility models have focused on short horizons. The authors use a large sample of global equity and bond indexes since 1934 to test the predictive power of different long-horizon volatility models. Their findings suggest that the best approach to forecasting long-horizon volatility is to use a long historical window and capture both long-term mean reversion and short-term volatility clustering properties. The results show that the authors’ model specification does a better job of reducing forecasting errors than does a naïve model based on the simple extrapolation of historical volatility.

Keywords

Portfolio construction; Volatility measures; Quantitative methods; Statistical methods; Performance measurement

Available on ECCH

No


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