The Stock-Bond Correlation

Autor: Mark Kritzman, David Turkington, Megan Czasonis
Rok vydání: 2020
Předmět:
Zdroj: The Journal of Portfolio Management. 47:67-76
ISSN: 2168-8656
0095-4918
DOI: 10.3905/jpm.2020.1.195
Popis: 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.
Databáze: OpenAIRE
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