Basis Assets
Basis Assets
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基础资产
DOI：
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发表时间：
2003
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通讯作者：
Robert F. Dittmar
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文献类型：
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作者：
D. Ahn;Jennifer S. Conrad;Robert F. Dittmar
本文提出了一种新的方法来形成代表投资者机会集的基础资产，并评价资产定价模型的拟合优度。我们使用回报相关性来形成证券之间的距离度量，如Ormerod和Mounfield（2000）所示，并使用这种距离度量来将证券分类到投资组合中。我们将从这组基础资产中得出的推论与从文献中常用的其他基准投资组合中得出的推论进行比较，例如beta和规模排序投资组合以及Fama和French（1993）的规模和账面市值排序投资组合。具体来说，我们比较了跨越检验、资产定价模型检验和最优投资组合推论的结果。结果表明，在为投资者的机会集生成代理方面，由回报的历史相关性聚类形成的基础资产集至少与基于特征的投资组合一样好。所提出的投资组合似乎还能够产生风险-收益权衡的度量，其估计误差较低。最后，我们将聚类投资组合与从同一样本周期提取的主成分进行比较，发现聚类投资组合在平均收益上产生略高的样本外离散度，夏普比率略低，单个证券的权重更稳定。
This paper proposes a new method to form basis assets with which to represent investors' opportunity sets and evaluate the goodness-of-fit of asset pricing models. We use return correlations to form a measure of distance between securities, as in Ormerod and Mounfield (2000), and use this distance measure to sort securities into portfolios. We compare the inferences drawn from this set of basis assets with those drawn from other benchmark portfolios commonly used in the literature such as beta and size-sorted portfolios and the Fama and French (1993) size and book-to-market sorted portfolios. Specifically, we compare the results of spanning tests, tests of asset pricing models and inferences about optimal portfolios. The results suggest that the set of basis assets formed by clustering on historical correlations in returns does at least as well as characteristic-based portfolios at generating a proxy for an investor's opportunity set. The proposed set of portfolios also appears capable of generating measures of risk-return trade-off that are estimated with lower error. Finally, we compare the cluster portfolios to principal components extracted from the same sample period, and find that the cluster portfolios generate slightly higher out-of-sample dispersion in mean returns, a slightly lower Sharpe ratio and more stable weights on individual securities.