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Combinatorial Nonlinear Goal Programming for ESG Portfolio Optimization and Dynamic Hedge Management

In: Mathematical and Statistical Methods for Actuarial Sciences and Finance

Author

Listed:
  • Gordon H. Dash Jr.

    (University of Rhode Island, Finance and Decision Sciences Area, College of Business Administration)

  • Nina Kajiji

    (University of Rhode Island, Department of Computer Science and Statistics
    The NKD-Group, Inc.)

Abstract

Compared to their fundamentally weighted counterparts naively diversified investment portfolios that embrace environmental, sustainability and governance (ESG) factors are known to experience enhanced long-term investment performance. This paper introduces a combinatorial nonlinear multiple objective optimization model to diversify the short-term ESG portfolio. The expectation of long-term wealth creation from an ESG portfolio is also examined. This latter investment objective is explored by implementing a discrete period ESG portfolio re-balancing with attached dynamic hedging. Post simulation, we report comparatively higher Sharpe ratios and lower VaR metrics for the multiobjective and dynamically hedged ESG portfolio investment style.

Suggested Citation

  • Gordon H. Dash Jr. & Nina Kajiji, 2014. "Combinatorial Nonlinear Goal Programming for ESG Portfolio Optimization and Dynamic Hedge Management," Springer Books, in: Cira Perna & Marilena Sibillo (ed.), Mathematical and Statistical Methods for Actuarial Sciences and Finance, edition 127, pages 77-80, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-05014-0_18
    DOI: 10.1007/978-3-319-05014-0_18
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