Discretized reality and spurious profits in stochastic programming models for asset/liability management
AbstractIn the literature on stochastic programming models for practical portfolio investment problems, relatively little attention has been devoted to the question how the necessarily approximate description of the asset-price uncertainty in these models influences the optimal solution. In this paper we will show that it is important that asset prices in such a description are arbitrage-free. Descriptions which have been suggested in the literature are often inconsistent with observed market prices and/or use sampling to obtain a set of scenarios about the future. We will show that this effectively introduces arbitrage opportunities in the optimization model. For an investor who cannot exploit arbitrage opportunities directly because of market imperfections and trading restrictions, we will illustrate that the presence of such arbitrage opportunities may cause substantial biases in the optimal investment strategy.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics in its series Serie Research Memoranda with number 0011.
Date of creation: 1997
Date of revision:
Contact details of provider:
Web page: http://www.feweb.vu.nl
Find related papers by JEL classification:
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
- G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
This paper has been announced in the following NEP Reports:
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Harrison, J. Michael & Kreps, David M., 1979. "Martingales and arbitrage in multiperiod securities markets," Journal of Economic Theory, Elsevier, vol. 20(3), pages 381-408, June.
- Golub, Bennett & Holmer, Martin & McKendall, Raymond & Pohlman, Lawrence & Zenios, Stavros A., 1995. "A stochastic programming model for money management," European Journal of Operational Research, Elsevier, vol. 85(2), pages 282-296, September.
- Brennan, Michael J. & Schwartz, Eduardo S., 1982. "An Equilibrium Model of Bond Pricing and a Test of Market Efficiency," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 17(03), pages 301-329, September.
- Ho, Thomas S Y & Lee, Sang-bin, 1986. " Term Structure Movements and Pricing Interest Rate Contingent Claims," Journal of Finance, American Finance Association, vol. 41(5), pages 1011-29, December.
- Heath, David & Jarrow, Robert & Morton, Andrew, 1990. "Bond Pricing and the Term Structure of Interest Rates: A Discrete Time Approximation," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 25(04), pages 419-440, December.
- Hull, John & White, Alan, 1993. "One-Factor Interest-Rate Models and the Valuation of Interest-Rate Derivative Securities," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 28(02), pages 235-254, June.
- Randall S. Hiller & Jonathan Eckstein, 1993. "Stochastic Dedication: Designing Fixed Income Portfolios Using Massively Parallel Benders Decomposition," Management Science, INFORMS, vol. 39(11), pages 1422-1438, November.
- Hull, John & White, Alan, 1990. "Valuing Derivative Securities Using the Explicit Finite Difference Method," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 25(01), pages 87-100, March.
- John M. Mulvey & Hercules Vladimirou, 1992. "Stochastic Network Programming for Financial Planning Problems," Management Science, INFORMS, vol. 38(11), pages 1642-1664, November.
- Stephen P. Bradley & Dwight B. Crane, 1972. "A Dynamic Model for Bond Portfolio Management," Management Science, INFORMS, vol. 19(2), pages 139-151, October.
- Gondzio, Jacek & Kouwenberg, Roy & Vorst, Ton, 2003.
"Hedging options under transaction costs and stochastic volatility,"
Journal of Economic Dynamics and Control,
Elsevier, vol. 27(6), pages 1045-1068, April.
- Roy Kouwenberg & Jacek Gondzio & Ton Vorst, 1999. "Hedging Options under Transaction Costs and Stochastic Volatility," Computing in Economics and Finance 1999 911, Society for Computational Economics.
- Rocha, Paula & Kuhn, Daniel, 2012. "Multistage stochastic portfolio optimisation in deregulated electricity markets using linear decision rules," European Journal of Operational Research, Elsevier, vol. 216(2), pages 397-408.
- de Lange, Petter E. & Fleten, Stein-Erik & Gaivoronski, Alexei A., 2004. "Modeling financial reinsurance in the casualty insurance business via stochastic programming," Journal of Economic Dynamics and Control, Elsevier, vol. 28(5), pages 991-1012, February.
- Gulpinar, Nalan & Rustem, Berc & Settergren, Reuben, 2004. "Simulation and optimization approaches to scenario tree generation," Journal of Economic Dynamics and Control, Elsevier, vol. 28(7), pages 1291-1315, April.
- Sodhi, ManMohan S. & Tang, Christopher S., 2009. "Modeling supply-chain planning under demand uncertainty using stochastic programming: A survey motivated by asset-liability management," International Journal of Production Economics, Elsevier, vol. 121(2), pages 728-738, October.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (R. Dam).
If references are entirely missing, you can add them using this form.