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Portfolio optimization with VaR approach: A comparative analysis for Japan, London, New York and India

Author

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  • Parul BHATIA

    (Apeejay School of Management, Dwarka, New Delhi)

  • Priya GUPTA

    (Lal Bahadur Shastri Institute of Management, Dwarka, New Delhi)

Abstract

Risk managers use various types of techniques to estimate different kinds of risk and ways to minimize its impact. VaR which stands for Value at Risk is one of those techniques. Various new methods for calculation of VaR have been developed. In this study, four techniques of VaR estimations have been employed: i) Historical Simulation; ii) Variance Covariance Approach; iii) Monte Carlo Simulation, and iv) AR-GARCH method. The purpose of this study is to compare the different VaR estimation methods and draw conclusions based on the Back- Testing methods. As per the analysis, historical method proved to be the best method for estimating value at risk. This method is widely preferred by risk managers and practitioners in the banking sector. Though the portfolios used in the study was diversified and contained stocks from different sectors, still the historical simulation method came out to be on the top as it was accepted for all the four portfolios. This method does have some limitations as the patterns generated from the past data may not hold true all the time.

Suggested Citation

  • Parul BHATIA & Priya GUPTA, 2020. "Portfolio optimization with VaR approach: A comparative analysis for Japan, London, New York and India," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(4(625), W), pages 245-262, Winter.
    • Handle: RePEc:agr:journl:v:4(625):y:2020:i:4(625):p:245-262
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    References listed on IDEAS

    as
    1. Adam Krzemienowski & Sylwia Szymczyk, 2016. "Portfolio optimization with a copula-based extension of conditional value-at-risk," Annals of Operations Research, Springer, vol. 237(1), pages 219-236, February.
    2. Adam Krzemienowski & Sylwia Szymczyk, 2016. "Portfolio optimization with a copula-based extension of conditional value-at-risk," Annals of Operations Research, Springer, vol. 237(1), pages 219-236, February.
    3. Geng Deng & Tim Dulaney & Craig McCann & Olivia Wang, 2013. "Robust portfolio optimization with Value-at-Risk-adjusted Sharpe ratios," Journal of Asset Management, Palgrave Macmillan, vol. 14(5), pages 293-305, October.
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