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.

More Details

Item Type: Article
Subject Areas: Finance
Additional Information:

© 2021 Pageant Media Ltd

Multi-Asset Special Issue 2021

Date Deposited: 07 Apr 2021 11:22
Subjects: Portfolio investment
Statistical evaluation
Last Modified: 12 Aug 2024 00:46
URI: https://lbsresearch.london.edu/id/eprint/1747
More

Export and Share


Download

Full text not available from this repository.

Statistics

Altmetrics
View details on Dimensions' website

Downloads from LBS Research Online

View details

Actions (login required)

Edit Item Edit Item