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Robust portfolio optimization: a stochastic evaluation of worst-case scenarios

Author

Listed:
  • Paulo Rotella Junior
  • Luiz Célio Souza Rocha
  • Rogério Santana Peruchi
  • Giancarlo Aquila
  • Edson de Oliveira Pamplona
  • Karel Janda
  • Arthur Leandro Guerra Pires

Abstract

This article presents a new approach for building robust portfolios based on stochastic efficiency analysis, by using the Chance Constrained Data Envelopment Analysis (CCDEA) model and periods of market downturn, i.e. worst-state market. The model is able to accommodate investors who exhibit different risk behaviors and the empirical analysis is done on assets traded on the Brazil Stock Exchange, B3 (Brasil, Bolsa, Balcão). The results confirm that the proposed model achieved portfolios that at the same time reduced systematic risk and maximized portfolio returns when working with worse market state data and higher levels of risk aversion. A higher level of risk aversion also led to better risk-return ratios, which can be seen in higher Sharpe ratio values.

Suggested Citation

  • Paulo Rotella Junior & Luiz Célio Souza Rocha & Rogério Santana Peruchi & Giancarlo Aquila & Edson de Oliveira Pamplona & Karel Janda & Arthur Leandro Guerra Pires, 2023. "Robust portfolio optimization: a stochastic evaluation of worst-case scenarios," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 36(3), pages 2165525-216, December.
    • Handle: RePEc:taf:reroxx:v:36:y:2023:i:3:p:2165525
    DOI: 10.1080/1331677X.2023.2165525
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    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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