Doctoral thesis

A scenario generation algorithm for multistage stochastic programming : application for asset allocation models with derivatives


91 p

Thèse de doctorat: Università della Svizzera italiana, 2006 (jury note: magna cum laude)

English Modern financial portfolio management problems as well as asset/liability problems use stochastic optimization to allocate financial assets. To implement and solve such a stochastic optimization based portfolio allocation problem, we require scenario trees for the description of the future market evolutions of every random variable present in the model. This thesis proposes a general algorithm to construct scenario trees for underlying assets as well as options on these assets. The algorithm is based on the simulation of GARCH processes and on a Wasserstein distance minimization for the reduction of the number of scenarios. Several processes are analyzed, and empirical results on the DAX 100 and on European Put and Call options on this index are presented.
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