Enhanced indexing using weighted conditional value at risk

Ruchika Sehgal () and Aparna Mehra ()
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Ruchika Sehgal: Indian Institute of Technology Delhi
Aparna Mehra: Indian Institute of Technology Delhi

Annals of Operations Research, 2019, vol. 280, issue 1, No 10, 240 pages

Abstract: Abstract We propose an enhanced indexing portfolio optimization model that not only seeks to maximize the excess returns over and above the benchmark index but simultaneously control the risk by introducing a constraint on the weighted conditional value at risk (WCVaR) of the portfolio. The constraint in the proposed model can be seen as hedging the risk described by WCVaR of the portfolio. To carry out a comparative analysis of the proposed model, we also suggest an enhanced indexing CVaR model. We analyze the performance of the proposed model at various risk levels on eight publicly available financial data sets from Beasley OR library, and S&P 500, S&P BSE 500, NASDAQ composite, FTSE 100 index, and their constituents, for average returns, Sharpe ratio, and upside potential ratio. Empirical analysis exhibits superior performance of the portfolios from the proposed WCVaR model over the respective benchmark indices and additionally the optimal portfolios obtained from various other enhanced indexing models that exist in the literature. Furthermore, we present evidence of better performance of WCVaR model over the CVaR model for long-term investment horizons.

Keywords: Enhanced indexing; Conditional value at risk; Weighted conditional value at risk; Gini mean difference; Sharpe ratio; Upside potential ratio (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s10479-019-03132-2

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