基于效用增强加权的指数跟踪

Index tracking with utility enhanced weighting

Quantitative Finance · 2019
被引 2
ABS 3

中文导读

提出一种基于累积效用面积比和层次分析法的新技术,用于构建增强型指数组合,在道琼斯和标普500指数上验证了其计算简便、调仓频率低且能持续获得更高的样本外效用和税后收益。

Abstract

Passive index investing involves investing in a fund that replicates a market index. Enhanced indexation uses the returns of an index as a reference point and aims at outperforming this index. The motivation behind enhanced indexing is that the indices and portfolios available to academics and practitioners for asset pricing and benchmarking are generally inefficient and, thus, susceptible to enhancement. In this paper we propose a novel technique based on the concept of cumulative utility area ratios and the Analytic Hierarchy Process (AHP) to construct enhanced indices from the DJIA and S&P500. Four main conclusions are forthcoming. First, the technique, called the utility enhanced tracking technique (UETT), is computationally parsimonious and applicable for all return distributions. Second, if desired, cardinality constraints are simple and computationally parsimonious. Third, the technique requires only infrequent rebalancing, monthly at the most. Finally, the UETT portfolios generate consistently higher out-of-sample utility profiles and after-cost returns for the fully enhanced portfolios as well as for the enhanced portfolios adjusted for cardinality constraints. These results are robust to varying market conditions and a range of utility functions.

被动投资指数增强投资组合优化效用理论