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Discrete-time behavioral portfolio selection under cumulative prospect theory
Institution:1. School of Management, Shanghai University, China;2. School of Statistics and Management, Shanghai Key Laboratory of Financial Information Technology, Shanghai University of Finance and Economics, China;3. Department of Systems Engineering & Engineering Management, The Chinese University of Hong Kong, Hong Kong;1. University of Technology Sydney, UTS Business School, PO Box 123, Broadway, NSW 2007, Australia;2. Sun Yat-Sen University, Sun Yat-Sen Business School, No. 135, West Xingang Road, Guangzhou 510275, PR China;1. Department of Economics, Deakin University, 70 Elgar Road, Burwood VIC 3125, Australia;2. OECD Economics Department, 2, rue André Pascal, 75775 Paris Cedex 16, France;3. Department of Economics, Monash University, Clayton VIC 3800, Australia;1. Department of Finance, Accounting and Statistics and Vienna Graduate School of Finance, WU Vienna University of Economics and Business, Welthandelsplatz 1, 1020 Vienna, Austria;2. Department of Economics and Business, Aarhus University, Denmark;1. School of Applied Mathematics, Guangdong University of Technology, Guangzhou 510520, PR China;2. Department of Statistics and Probability, Michigan State University, East Lansing, MI 48824, USA;3. School of Finance, Guangdong University of Foreign Studies, Guangzhou 510006, China
Abstract:We formulate and study three multi-period behavioral portfolio selection models under cumulative prospect theory: (i) S-shaped utility maximization without probability weighting in a market with one risky asset; (ii) S-shaped utility maximization without probability weighting in a market with multiple risky assets which follow a joint elliptical distribution; and (iii) S-shaped utility maximization with inverse-S-shaped probability weighting in a market with one risky asset. For the first two time consistent models, we identify the well-posedness conditions and derive the semi-analytical optimal policies. For the third time inconsistent model, we assume that the investor is aware of the time inconsistency but is unable to commit to his initial plan of action. Then, we reformulate the model into an intrapersonal game model and derive the semi-analytical subgame perfect Nash equilibrium (time consistent) policy under well-posedness condition. All the three policies take a piecewise linear feedback form. Our analysis of the three models not only partially explains the well documented phenomena of non-participation puzzle and horizon effect, but also extends the two fund separation theorem into multi-period S-shaped utility setting and pushes forward the study on time inconsistency issue incurred by probability weighting.
Keywords:Multi-period portfolio selection  S-shaped utility  Probability weighting  Time consistent policy  Two-fund separation  Non-participation puzzle and horizon effect
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