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The Divergence of High- and Low-Frequency Estimation: Causes and Consequences

机译:高频和低频估计的差异:成因和后果

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摘要

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.
机译:财务分析师通常会在确定投资组合的最佳构成时,根据月度或更高频率的回报来估计波动率和相关性。尽管人们普遍认为这些措施不一定在样本之间是固定的,但大多数分析家都隐含地认为,样本中的波动率与时间的平方根成比例,并且从高频收益估计的相关性类似于从低频收益估计的相关性。证据不支持这种观点。取而代之的是,证据表明,相对资产价值经常以与高频波动率和相关性高度不一致的方式随时间演变。结果,基于高频回报的最佳投资组合通常会导致远景投资人获得明显次优的结果。本文作者分析了这种差异的原因和后果,并提出了构建平衡短期投资和长期投资的最优投资组合的框架。

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