Dynamic stochastic programming for asset-liability management
نویسندگان
چکیده
Multistage stochastic programming in contrast to stochastic control has found wide application in the formulation and solution of nancial problems characterized by a large number of state variables and a generally low n umber of possible decision stages. The literature on the use of multistage recourse modelling to formalize complex portfolio optimization problems dates back to the early seventies, when the technique was rst adopted to solve a xed interest security portfolio problem. We present here the CALM model which has been designed to deal with uncertainty aaecting both assets in either the portfolio or the market and liabilities in the form of scenario dependent p a yments or borrowing costs. We consider as an instance a pension fund problem in which portfolio rebalancing is allowed over a long-term horizon at discrete time points and where liabilities refer to ve diierent classes of pension contracts. The portfolio manager, given an initial wealth, seeks the maximization of terminal wealth at the horizon, with investment returns modelled as discrete state random vectors. Decision vectors represent possible investments in the market and holding or selling assets in the portfolio, as well as borrowing decisions from a credit line or deposits with a bank. Computational results are presented for a set of 10-stage portfolio problems using diierent solution methods and libraries OSL,CPLEX,OB1.The portfolio problem with an underlying vector data process which allows up to 2688 realizations at the 10 year horizon is solved on an IBM RS60000590 for a set of twenty four large scale test problems using the simplex and barrier methods provided by CPLEX the latter for either linear or quadratic objective, the predictorrcorrector interior point method provided in OB1, the simplex method of OSL, the MSLiP-OSL code instantiating nested Benders decomposition with subproblem solution using OSL simplex and the current v ersion of MSLiP.
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ورودعنوان ژورنال:
- Annals OR
دوره 81 شماره
صفحات -
تاریخ انتشار 1998