Belief rule-based system for portfolio optimisation with nonlinear cash-flows and constraints

被引：18

作者：

Chen, Yu-Wang ^{[1
]}

Poon, Ser-Huang ^{[1
]}

Yang, Jian-Bo ^{[1
]}

Xu, Dong-Ling ^{[1
]}

Zhang, Dongxu ^{[1
]}

Acomb, Simon ^{[1
]}

机构：

[1] Univ Manchester, Manchester Business Sch, Manchester M15 6PB, Lancs, England

来源：

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH | 2012年 / 223卷 / 03期

基金：

英国工程与自然科学研究理事会;

关键词：

Portfolio optimisation; Efficient frontier; Belief rule base; Evidential reasoning; EVIDENTIAL REASONING APPROACH; INFERENCE; METHODOLOGY; ALGORITHM;

D O I：

10.1016/j.ejor.2012.07.008

中图分类号：

C93 [管理学];

学科分类号：

12 ; 1201 ; 1202 ; 120202 ;

摘要：

A belief rule-based (BRB) system is a generic nonlinear modelling and inference scheme. It is based on the concept of belief structures and evidential reasoning (ER), and has been shown to be capable of capturing complicated nonlinear causal relationships between antecedent attributes and consequents. The aim of this paper is to develop a BRB system that complements the RiskMetrics WealthBench system for portfolio optimisation with nonlinear cash-flows and constraints. Two optimisation methods are presented to locate efficient portfolios under different constraints specified by the investors. Numerical studies demonstrate the effectiveness and efficiency of the proposed methodology. (C) 2012 Elsevier B.V. All rights reserved.

引用

页码：775 / 784

页数：10

共 40 条

[1]

Angelelli E, 2009, FINANCIAL HEDGING, P119

[2]

[Anonymous], HDB COMPUTATIONAL EC

[3]

[Anonymous], 1993, J. Financ

[4]

Black F., 1992, Financial Analysts Journal, V48, P28, DOI DOI 10.2469/FAJ.V48.N5.28

[5] A simulation approach to dynamic portfolio choice with an application to learning about return predictability [J].

Brandt, MW ;

Goyal, A ;

Santa-Clara, P ;

Stroud, JR .

REVIEW OF FINANCIAL STUDIES, 2005, 18 (03) :831-873

[6]

Campbell J. Y., 2002, STRATEGIC ASSET ALLO

[7] Multiperiod portfolio optimization models in stochastic markets using the mean-variance approach [J].

Celikyurt, U. ;

Ozekici, S. .

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2007, 179 (01) :186-202

[8] Inference analysis and adaptive training for belief rule based systems [J].

Chen, Yu-Wang ;

Yang, Jian-Bo ;

Xu, Dong-Ling ;

Zhou, Zhi-Jie ;

Tanga, Da-Wei .

EXPERT SYSTEMS WITH APPLICATIONS, 2011, 38 (10) :12845-12860

[9]

Coleman T., 1999, OPTIMIZATION TOOLBOX, Vthird

[10] Optimal Versus Naive Diversification: How Inefficient is the 1/N Portfolio Strategy? [J].

DeMiguel, Victor ;

Garlappi, Lorenzo ;

Uppal, Raman .

REVIEW OF FINANCIAL STUDIES, 2009, 22 (05) :1915-1953

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