指数跟踪的平均风险优化

IF 1.3 Q2 STATISTICS & PROBABILITY

Statistics & Risk Modeling Pub Date : 2006-07-01 DOI:10.1524/stnd.2006.24.1.189

Yumiharu Nakano

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引用次数: 0

摘要

本文分析了以平均财富为多维绩效标准的多指标跟踪问题及其跟踪误差。我们通过凸锥定义的向量不等式来评估投资组合的绩效，这使我们能够描述投资者的各种偏好关系。在具有确定性系数的布朗市场模型中，我们完全确定了有效投资组合集和有效边界。作为我们分析的成果，我们展示了托宾共同基金定理的一个版本。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Mean-risk optimization for index tracking

SUMMARY This paper presents an analysis of the tracking problems of multiple indices with multidimensional performance criterion consisting of mean wealth and the tracking errors. We evaluate the performance of portfolios via the vector inequalities defined by convex cones, which enable us to describe various preference relations for investors. In Brownian market models with deterministic coefficients, we completely determine the set of efficient portfolios as well as the efficient frontier in our context. As a product of our analysis, we exhibit a version of Tobin's mutual fund theorem.

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来源期刊

Statistics & Risk Modeling STATISTICS & PROBABILITY-

CiteScore

1.80

自引率

6.70%

发文量

期刊介绍： Statistics & Risk Modeling (STRM) aims at covering modern methods of statistics and probabilistic modeling, and their applications to risk management in finance, insurance and related areas. The journal also welcomes articles related to nonparametric statistical methods and stochastic processes. Papers on innovative applications of statistical modeling and inference in risk management are also encouraged. Topics Statistical analysis for models in finance and insurance Credit-, market- and operational risk models Models for systemic risk Risk management Nonparametric statistical inference Statistical analysis of stochastic processes Stochastics in finance and insurance Decision making under uncertainty.