A robust portfolio optimization in Indian Stock market

M. Rajan, Nimit Rana
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引用次数: 1

Abstract

A good investment strategy requires a combination of mathematical modeling with deep understanding of the economics of the market. The basis of the portfolio optimization is the mean-variance optimization put forwarded by Markowitz in 1952. The optimization procedure depends on the input parameters, the covariance matrix and expected return which have to be estimated using the historical data. The portfolio selection hence depends on the reliability of these inputs and often lead to wrong results due to inaccurate estimation of covariance matrix and expected return. In this paper, we examine the performance of portfolio optimization in Indian Stock market using stable models for covariance estimation and come up with a portfolio of stocks that gives a meaningful return in reality.
在印度股票市场稳健的投资组合优化
一个好的投资策略需要将数学建模与对市场经济的深刻理解相结合。投资组合优化的基础是Markowitz在1952年提出的均值-方差优化。优化过程取决于输入参数,协方差矩阵和预期收益,这些都必须使用历史数据进行估计。因此,投资组合的选择取决于这些输入的可靠性,并且由于对协方差矩阵和预期收益的估计不准确而经常导致错误的结果。本文利用协方差估计的稳定模型,考察了印度股票市场的投资组合优化绩效,并提出了一个在现实中具有有意义回报的股票组合。
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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