Multi-period stochastic optimization models for dynamic asset allocation

Research output: Contribution to journalArticle

33 Citations (Scopus)

Abstract

Institutional investors manage their strategic asset mix over time to achieve favorable returns subject to various uncertainties, policy and legal constraints, and other requirements. One may use a multi-period portfolio optimization model in order to determine an optimal asset mix. The concept of scenarios is typically employed for modeling random parameters in a multi-period stochastic programming model, and scenarios are constructed via a tree structure. Recently, an alternative stochastic programming model with simulated paths was proposed by Hibiki [Hibiki, N., 2001b. A hybrid simulation/tree multi-period stochastic programming model for optimal asset allocation. In: Takahashi, H. (Ed.), The Japanese Association of Financial Econometrics and Engineering. JAFEE Journal 89-119 (in Japanese); Hibiki, N., 2003. A hybrid simulation/tree stochastic optimization model for dynamic asset allocation. In: Scherer, B. (Ed.), Asset and Liability Management Tools: A Handbook for Best Practice, Risk Books, pp. 269-294], and it is called a hybrid model. The advantage of the simulated path structure compared to the tree structure is to give a better accuracy to describe uncertainties of asset returns. In this paper, we compare the two types of multi-period stochastic optimization models, and clarify that the hybrid model can evaluate and control risk better than the scenario tree model using some numerical tests. According to the numerical results, an efficient frontier of the hybrid model with the fixed-proportion strategy dominates that of the scenario tree model when we evaluate them on simulated paths. Moreover, optimal solutions of the hybrid model are more appropriate than those of the scenario tree model.

Original languageEnglish
Pages (from-to)365-390
Number of pages26
JournalJournal of Banking and Finance
Volume30
Issue number2
DOIs
Publication statusPublished - 2006 Feb

Fingerprint

Stochastic optimization
Optimization model
Dynamic asset allocation
Scenarios
Hybrid model
Stochastic programming
Simulation
Optimal asset allocation
Financial engineering
Institutional investors
Assets
Asset returns
Control risk
Asset and liability management
Strategic assets
Proportion
Management tools
Policy uncertainty
Uncertainty
Financial econometrics

Keywords

  • Asset allocation
  • Hybrid model
  • Multi-period model
  • Portfolio optimization
  • Simulation

ASJC Scopus subject areas

  • Economics and Econometrics
  • Finance

Cite this

Multi-period stochastic optimization models for dynamic asset allocation. / Hibiki, Norio.

In: Journal of Banking and Finance, Vol. 30, No. 2, 02.2006, p. 365-390.

Research output: Contribution to journalArticle

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