Bi-objective reliability based optimization: an application to investment analysis

Portfolio optimization problems are easy to address if single linear objective functions are considered, with the assumption of normality of asset returns distributions, subject to different risks, returns, and investment constraints. Higher complexities arise if combinations of multi-objective form...

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Vydáno v:Annals of operations research Ročník 333; číslo 1; s. 47 - 78
Hlavní autoři: Sengupta, Raghu Nandan, Gupta, Aditya, Mukherjee, Subhankar, Weiss, Gregor
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.02.2024
Springer
Springer Nature B.V
Témata:
Autoregressive processes
Business and Management
Combinatorics
Estimates
Extreme values
Financial markets
Investment analysis
Mathematical optimization
Methods
Multiple objective analysis
Operations Research/Decision Theory
Optimization
Optimization models
Original - OR Modeling/Case Study
Parameter estimation
Parameter uncertainty
Pareto optimum
Portfolio management
Reliability
Securities analysis
Theory of Computation
India
Portfolio optimization
Investment analysis
Risk analysis
Multiple objective programming
ISSN:0254-5330, 1572-9338
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Shrnutí:Portfolio optimization problems are easy to address if single linear objective functions are considered, with the assumption of normality of asset returns distributions, subject to different risks, returns, and investment constraints. Higher complexities arise if combinations of multi-objective formulations, non-linear assets, non-normal asset return distributions, and uncertainty in parameter estimates are studied. In this paper, we solve two interesting variants of multi-objective investment analysis problems considering both non-normal asset return distributions and uncertainty in parameter estimates . Data used for the optimization models are pre-processed using ARCH/GARCH combined with extreme value asset returns distribution (EVD). The efficacy of our proposed multi-objective reliability-based portfolio optimization (MORBPO) problems is validated using Indian financial market data (Details of plan of codes, pseudo-codes and other set of detailed runs results (not discussed in this paper) are given in the open access link, https://github.com/RNSengupta/Bi-Objective_RBDO_Paper ). We present the optimal values of investment weights, portfolio returns, portfolio risks (variance, CVaR, EVaR), reliability indices ( β ) as well as Pareto optimal frontiers and analyze the outputs in the context of their practical implications. The run results highlight the fact that investors’ uncertainty levels (i.e., β ) play a crucial role in deciding the investment outcomes and thus facilitates him/her in choosing the optimal risk-return combinations of the portfolios.
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ISSN:0254-5330
1572-9338
DOI:10.1007/s10479-023-05645-3