Forecasting long-horizon volatility for strategic asset allocation

Cardinale, M, Naik, N and Sharma, V (2021) Forecasting long-horizon volatility for strategic asset allocation. Journal of Portfolio Management, 47 (4). pp. 83-98. ISSN 0095-4918

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.

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Item Type: Article
Subject Areas: Finance
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© 2021 Pageant Media Ltd

Multi-Asset Special Issue 2021

Date Deposited: 07 Apr 2021 11:22
Subjects: P > Portfolio investment
S > Statistical evaluation
Last Modified: 15 Jun 2021 13:09
URI: https://lbsresearch.london.edu/id/eprint/1747
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