Sensitivity of cautious-relaxed investment policies to target variation
This study builds on recent findings that target-based utility measures, used in the dynamic portfolio optimisation, deliver investment policies that can generate leftskewed payoff distributions. These policies can lead to small probabilities of low payoffs. This is in contrast to the classical portfolio optimisation strategies that commonly deliver right-skewed payoff distributions, which imply a high probability of losses. The left-skewed payoff distributions can be obtained when a “cautious-relaxed” investment policy is applied in portfolio management. Such a policy will be adopted by investors who are both cautious in seeking a payoff meeting a certain target, but relaxed toward the possibility of exceeding it. We use computational methods to analyse the effects of varying the target on the payoff distribution and also examine how the fund manager’s explicit preferences, when they differ from the investor’s, can impact the distribution. We found that increasing the target causes the distribution to become less left skewed. Lowering the target slightly, keeps the left-skewed payoff distribution albeit the mode diminishes. Decreasing the target substantially so it is below the safe investment payoff, changes the skew. Investor’s payoff will not suffer even if the actual fund manager allows for their own utility in the optimisation problem.
|Date of creation:||2013|
|Contact details of provider:|| Postal: Alice Fong, Administrator, School of Economics and Finance, Victoria Business School, Victoria University of Wellington, PO Box 600 Wellington, New Zealand|
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Web page: http://www.victoria.ac.nz/sef
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- Xue Dong He & Xun Yu Zhou, 2011. "Portfolio Choice Under Cumulative Prospect Theory: An Analytical Treatment," Management Science, INFORMS, vol. 57(2), pages 315-331, February.
- Azzato, Jeffrey D. & Krawczyk, Jacek B., 2008. "A parallel Matlab package for approximating the solution to a continuous-time stochastic optimal control problem," MPRA Paper 9993, University Library of Munich, Germany.
- Arjan B. Berkelaar & Roy Kouwenberg & Thierry Post, 2004.
"Optimal Portfolio Choice under Loss Aversion,"
The Review of Economics and Statistics,
MIT Press, vol. 86(4), pages 973-987, November.
- Azzato, Jeffrey & Krawczyk, Jacek B & Sissons, Christopher, 2011. "On loss-avoiding lump-sum pension optimization with contingent targets," Working Paper Series 1532, Victoria University of Wellington, School of Economics and Finance.
- Samuelson, Paul A, 1969.
"Lifetime Portfolio Selection by Dynamic Stochastic Programming,"
The Review of Economics and Statistics,
MIT Press, vol. 51(3), pages 239-46, August.
- Paul A. Samuelson, 2011. "Lifetime Portfolio Selection by Dynamic Stochastic Programming," World Scientific Book Chapters, in: THE KELLY CAPITAL GROWTH INVESTMENT CRITERION THEORY and PRACTICE, chapter 31, pages 465-472 World Scientific Publishing Co. Pte. Ltd..
- Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
- Patrick L. Brockett & Yehuda Kahane, 1992. "Risk, Return, Skewness and Preference," Management Science, INFORMS, vol. 38(6), pages 851-866, June.
- Cairns, Andrew, 2000. "Some Notes on the Dynamics and Optimal Control of Stochastic Pension Fund Models in Continuous Time," ASTIN Bulletin: The Journal of the International Actuarial Association, Cambridge University Press, vol. 30(01), pages 19-55, May.
- Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, 03.
- Alistair Windsor & Jacek B. Krawczyk, 1997. "A Matlab Package for Approximating the Solution to a Continuous- Time Stochastic Optimal Control Problem," Computational Economics 9710002, EconWPA.
- R. C. Merton, 1970.
"Optimum Consumption and Portfolio Rules in a Continuous-time Model,"
58, Massachusetts Institute of Technology (MIT), Department of Economics.
- Merton, Robert C., 1971. "Optimum consumption and portfolio rules in a continuous-time model," Journal of Economic Theory, Elsevier, vol. 3(4), pages 373-413, December.
- Dierkes, Maik & Erner, Carsten & Zeisberger, Stefan, 2010. "Investment horizon and the attractiveness of investment strategies: A behavioral approach," Journal of Banking & Finance, Elsevier, vol. 34(5), pages 1032-1046, May.
- Jacek B. Krawczyk, 2000. "A Markovian Approximated Solution To A Portfolio Management Problem," Computing in Economics and Finance 2000 233, Society for Computational Economics.
- Azzato, Jeffrey & Krawczyk, Jacek, 2006. "SOCSol4L An improved MATLAB package for approximating the solution to a continuous-time stochastic optimal control problem," MPRA Paper 1179, University Library of Munich, Germany.
- Yiu, K. F. C., 2004. "Optimal portfolios under a value-at-risk constraint," Journal of Economic Dynamics and Control, Elsevier, vol. 28(7), pages 1317-1334, April.
- Bali, Turan G. & Cakici, Nusret & Whitelaw, Robert F., 2011. "Maxing out: Stocks as lotteries and the cross-section of expected returns," Journal of Financial Economics, Elsevier, vol. 99(2), pages 427-446, February.
- Hanqing Jin & Xun Yu Zhou, 2008. "Behavioral Portfolio Selection In Continuous Time," Mathematical Finance, Wiley Blackwell, vol. 18(3), pages 385-426.
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