A stochastic programming model using an endogenously determined worst case risk measure for dynamic asset allocation

A stochastic programming model using an endogenously determined worst case risk measure for dynamic asset allocation

0.00 Avg rating0 Votes
Article ID: iaor20014195
Country: Germany
Volume: 89
Issue: 2
Start Page Number: 293
End Page Number: 309
Publication Date: Jan 2001
Journal: Mathematical Programming
Authors: ,
Abstract:

We present a new approach to asset allocation with transaction costs. A multiperiod stochastic linear programming model is developed where the risk is based on the worst case payoff that is endogenously determined by the model that balances expected return and risk. Utilizing portfolio protection and dynamic hedging, an investment portfolio similar to an option-like payoff structure on the initial investment portfolio is characterized. The relative changes in the expected terminal wealth, worst case payoff, and risk aversion, are studied theoretically and illustrated using a numerical example. This model dominates a static mean-variance model when the optimal portfolios are evaluated by the Sharpe ratio.

Reviews

Required fields are marked *. Your email address will not be published.