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Abstract
Investors rely on the stock-bond correlation for a variety of tasks, such as forming optimal portfolios, designing hedging strategies, and assessing risk. Most investors estimate the stock–bond correlation simply by extrapolating the historical correlation of monthly returns; they assume that this correlation best characterizes the correlation of future annual or multiyear returns, but this approach is decidedly unreliable. The authors introduce four innovations for generating a reliable prediction of the stock-bond correlation. First, they show how to represent the correlation of single-period cumulative stock and bond returns in a way that captures how the returns drift during the period. Second, they identify fundamental predictors of the stock-bond correlation. Third, they model the stock–bond correlation as a function of the path of some fundamental predictors rather than single observations. Finally, they censor their sample to include only relevant observations, in which relevance has a precise mathematical definition.
TOPICS: Portfolio management/multi-asset allocation, risk management, statistical methods
Key Findings
▪ The stock-bond correlation is a critical component of many investment activities, such as forming optimal portfolios, designing hedging strategies, and assessing risk.
▪ Most investors estimate the correlation of longer-interval returns by extrapolating the correlation of past shorter-interval returns, but this approach is decidedly unreliable.
▪ By applying recent advances in quantitative methods, it is possible to generate reliable predictions of the correlation of longer-horizon stock and bond returns.
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US and Overseas: +1 646-931-9045
UK: 0207 139 1600