Friday, 16:15 - 16:40 h, Room: H 3021


Dirk Becherer
Optimal sparse portfolios in continuous time


We discuss sparse portfolio optimization in continuous time.
Optimization objective is to maximize the classical expected utility, that
is the expectation of a concave functional of portfolio gains.
Sparse optimization aims to find asset allocations that contain only few
assets or that deviate only in few coordinated from a reference benchmark
allocation. Results show that optimal sparse portfolios are less
sensitive to estimation errors and performance is superior to optimal
portfolio without sparsity constraints, when estimation of model parameters
is taken into account.


Talk 3 of the invited session Fri.3.H 3021
"Optimization in financial markets" [...]
Cluster 7
"Finance & economics" [...]


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