Computational Economics

, Volume 28, Issue 2, pp 113–137 | Cite as

The Impact of Short-Sale Constraints on Asset Allocation Strategies via the Backward Markov Chain Approximation Method

  • Carl Chiarella
  • Chih-Ying Hsiao


This paper considers an asset allocation strategy over a finite period under investment uncertainty and short-sale constraints as a continuous-time stochastic control problem. Investment uncertainty is characterised by a stochastic interest rate and inflation risk. If there are no short-sale constraints, the optimal asset allocation strategy can be obtained analytically. We consider several kinds of short-sale constraints and employ the backward Markov chain approximation method to explore the impact of short-sale constraints on asset allocation decisions. Our results show that the short-sale constraints do indeed have a significant impact on these decisions.


asset allocation stochastic optimal control short sale constraints inflation risk Markov chain approximation 


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  1. Brennan, M.J. and Xia, Y. (2002). Dynamic asset allocation under inflation, The Journal of Financ, 57(3), 1201–1238.CrossRefGoogle Scholar
  2. Camilli, F. and Falcone, M. (1995). An approximation scheme for the optimal control of diffusion processes. Mathematical Modelling and Numerical Analysis, 25(1), 97–122.Google Scholar
  3. Cox, J.C. and Huang, C–F. (1989). Optimal consumption and portfolio policies when asset prices follow a diffusion process. Journal of Economic Theory, 49, 33–83.CrossRefGoogle Scholar
  4. Duffie, D. and Kan, R. (1996). A yield-factor model of interest rates. Mathematical Finance, 6(4), 397–406.CrossRefGoogle Scholar
  5. Gruene, L. Numerik Optimaler Steuerung, Internet,
  6. Hsiao, C.-Y., Chiarella, C. and Semmler, W. (2005). Strategic Asset Allocation with Investment in Inflation-Indexed Bonds, Working Paper, University of Bielefeld.Google Scholar
  7. Jarrow, R. and Yildirim, Y. (2003), Pricing treasury inflation protected securities and related derivatives using an HJM model. Journal of Financial and Quantitative Analysis, 38(2), 337–358.CrossRefGoogle Scholar
  8. Kamien, M.I. and Schwartz, N.L. (1991), Dynamic Optimization, North-Holland.Google Scholar
  9. Kloeden, P.E. and Platen, E. (1992). Numerical Solution of Stochastic Differential Equations, Springer.Google Scholar
  10. Kushner, H.J. (1977). Probability methods for approximations in stochastic control and for ellipic equations, Academic Press, New York.Google Scholar
  11. Liu, J. (2005). Portfolio Selection in Stochastic Environments, Stanford GSB Working Papers.Google Scholar
  12. Merton, R.C. (1971). Optimum consumption and portfolio rules in a continuous time model, Journal of Economic Theory, 3, 373–413.CrossRefGoogle Scholar
  13. Merton, R.C. (1973). An intertemporal capital asset pricing model. Econometrica, 41(5), 867–887.CrossRefGoogle Scholar
  14. Oksendal, B. (2000). Stochastic Differential Equations, 6th. ed., Springer.Google Scholar
  15. Tapiero, C.S and Sulem, A. (1994). Computational aspects in applied stochastic control. Computational Economics, 7, 109–146.CrossRefGoogle Scholar
  16. Wachter, J.A. (2002). Portfolio and consumption decisions under mean-reverting returns: An exact solution for complete market. Journal of Financial and Quantitative Analysis, 37(1), 63–91.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, Inc. 2006

Authors and Affiliations

  • Carl Chiarella
    • 1
  • Chih-Ying Hsiao
    • 1
    • 2
  1. 1.School of Finance and EconomicsUniversity of TechnologySydneyAustralia
  2. 2.University of BielefeldBielefeldGermany

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