The Divergence of High- and Low-Frequency Estimation

Causes and Consequences

November 2014

Financial analysts typically estimate volatilities and correlations from monthly or higher-frequency returns when determining the optimal composition of a portfolio. Although it is widely acknowledged that these measures are not necessarily stationary across samples, most analysts assume implicitly that, within sample, volatilities scale with the square root of time and correlations estimated from high-frequency returns are similar to correlations estimated from low-frequency returns.

Evidence does not support this view. Instead, evidence shows that relative asset values often evolve through time in ways that are highly inconsistent with their high-frequency volatilities and correlations. As a consequence, portfolios that are optimal based on high-frequency returns often lead to significantly suboptimal results for investors with long horizons. The causes and consequences of this discrepancy are analyzed by the article’s authors, as well as presenting a framework for constructing portfolios that balance short-horizon and long-horizon optimality.

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Evidence shows that relative asset values often evolve through time in ways that are highly inconsistent with their high-frequency volatilities and correlations.

William Kinlaw, CFA

Senior Managing Director,
Head of State Street Associates