Optimal portfolio and consumption policies subject to Rishel's important jump events model: computational methods

At important events or announcements, there can be large changes in the value of financial portfolios. Events and their corresponding jumps can occur at random or scheduled times. However, the amplitude of the response in either case can be unpredictable or random. While the volatility of portfolios is often modeled by continuous Brownian motion processes, discontinuous jump processes are more appropriate for modeling the response to important external events that significantly affect the prices of financial assets. Discontinuous jump processes are modeled by compound Poisson processes for random events or by quasi-deterministic jump processes for scheduled events. In both cases, the responses are randomly distributed and are modeled in a stochastic differential equation formulation. The objective is the maximal, expected total discounted utility of terminal wealth and instantaneous consumption. This paper was motivated by a paper by Rishel (1999) concerning portfolio optimization when prices are dependent on external events. However, the model has been significantly generalized for more realistic computational considerations with constraints and parameter values. The problem is illustrated for a canonical risk-adverse power utility model. However, the usual explicit canonical solution is not strictly valid. Fortunately, iterations about the canonical solution result in computationally feasible approximations.

[1]  H. Tuckwell,et al.  Population growth with randomly distributed jumps , 1997 .

[2]  Raymond Rishel Modeling and portfolio optimization for stock prices dependent on external events , 1999, Proceedings of the 38th IEEE Conference on Decision and Control (Cat. No.99CH36304).

[3]  R. C. Merton,et al.  Option pricing when underlying stock returns are discontinuous , 1976 .

[4]  E. Renshaw,et al.  STOCHASTIC DIFFERENTIAL EQUATIONS , 1974 .

[5]  F. Black,et al.  The Pricing of Options and Corporate Liabilities , 1973, Journal of Political Economy.

[6]  R. C. Merton,et al.  Optimum consumption and portfolio rules in a continuous - time model Journal of Economic Theory 3 , 1971 .

[7]  Floyd B. Hanson,et al.  Techniques in Computational Stochastic Dynamic Programming , 1996 .

[8]  S. Sethi,et al.  A Note on Merton's 'Optimum Consumption and Portfolio Rules in a Continuous-Time Model' , 1988 .

[9]  R. C. Merton,et al.  Lifetime Portfolio Selection under Uncertainty: The Continuous-Time Case , 1969 .

[10]  R. C. Merton,et al.  Optimum Consumption and Portfolio Rules in a Continuous-Time Model* , 1975 .

[11]  S. Shreve,et al.  Stochastic differential equations , 1955, Mathematical Proceedings of the Cambridge Philosophical Society.

[12]  J. J. Westman,et al.  The LQGP problem: a manufacturing application , 1997, Proceedings of the 1997 American Control Conference (Cat. No.97CH36041).

[13]  J. J. Westman,et al.  State dependent jump models in optimal control , 1999, Proceedings of the 38th IEEE Conference on Decision and Control (Cat. No.99CH36304).

[14]  R. C. Merton,et al.  Continuous-Time Finance , 1990 .

[15]  Suresh P. Sethi,et al.  Explicit Solution of a General Consumption/Investment Problem , 1986, Math. Oper. Res..

[16]  F. Hanson,et al.  Optimal harvesting with both population and price dynamics. , 1998, Mathematical biosciences.

[17]  I. Gihman,et al.  Controlled Stochastic Processes , 1979 .

[18]  J. J. Westman,et al.  Non-linear state dynamics: Computational methods and manufacturing application , 2000 .