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Robust Portfolio Optimization: A Stochastic Evaluation of Worst-Case Scenarios

Author

Listed:
  • Paulo Rotella Junior

    (Department of Production Engineering, Federal University of Paraiba, Brazil & Department of Management, Federal Institute of Education, Science and Technology - North of Minas Gerais, Brazil & Faculty of Finance and Accounting, Prague University of Economics and Business, Czech Republic & Faculty of Social Sciences, Charles University, Czech Republic)

  • Luiz Celio Souza Rocha

    (Department of Management, Federal Institute of Education, Science and Technology - North of Minas Gerais, Brazil)

  • Rogerio Santana Peruchi

    (Department of Production Engineering, Federal University of Paraiba, Brazil)

  • Giancarlo Aquila

    (IEPG, Federal University of Itajuba, Brazil)

  • Karel Janda

    (Faculty of Finance and Accounting, Prague University of Economics and Business, Czech Republic & Faculty of Social Sciences, Charles University, Czech Republic)

  • Edson de Oliveira Pamplona

    (Institute of Production and Management Engineering, Federal University of Itajuba, Brazil)

Abstract

This article presents a new approach for building robust portfolios based on stochastic efficiency analysis and periods of market downturn. The empirical analysis is done on assets traded on the Brazil Stock Exchange, B3 (Brasil, Bolsa, Balcao). We start with information on the assets from periods of market downturn (worst-case) and we group them using hierarchical clustering. Then we do stochastic efficiency analysis on these data using the Chance Constrained Data Envelopment Analysis (CCDEA) model. Finally, we use a classical model of capital allocation to obtain the optimal share of each asset. Our model is able to accommodate investors who exhibit different risk behaviors (from conservatives to risky investors) by varying the level of probability in fulfilling the constraints (1-αi) of the CCDEA model. We show that the optimal portfolios constructed with the use of information from periods of market downturns perform better for the Sharpe ratio (SR) in the validation period. The combined use of these approaches, using also fundamentalist variables and information on market downturns, allows us to build robust portfolios, with higher cumulative returns in the validation period, and portfolios with lower beta values.

Suggested Citation

  • Paulo Rotella Junior & Luiz Celio Souza Rocha & Rogerio Santana Peruchi & Giancarlo Aquila & Karel Janda & Edson de Oliveira Pamplona, 2022. "Robust Portfolio Optimization: A Stochastic Evaluation of Worst-Case Scenarios," Working Papers IES 2022/03, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Mar 2022.
    • Handle: RePEc:fau:wpaper:wp2022_03
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    Keywords

    Robust optimization; Stochastic evaluation; Chance Constrained DEA; Worst-case markets; Portfolios;
    All these keywords.

    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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