Dipartimento di Scienze
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Research Series

Title:Utility Maximization under restricted information for jump market models
Author(s):Claudia Ceci
Files: [pdf] [bib]
Abstract:The contribution of this paper is twofold: we study by a BSDE approach power utility maximization problem in a partially observed financial market with jumps and we solve by the innovation method the arising filtering problem. We consider a market with the risky asset dynamics described by a pure jump process whose local characteristics are not observable by investors. We assume that agents' decisions are based on the knowledge of an information flow containing the asset price history. In the case where agents just observe asset prices the value process and the optimal investment strategy are represented in terms of solutions to a BSDE driven by the minimal compensated random measure associated to the stock price. A Markovian model where the stock price process dynamics depends by an unobservable stochastic factor is proposed. Next, for this model we extend the study to the case where agents observe the stock price and receive in addition noisy signals on the unobservable stochastic factor (it can be viewed as an abstract form of "insider information"). In this setup the value process is characterized as solution to a BSDE driven by the compensated random measure and the so-called innovation process. Computation of these quantities leads to a filtering problem with mixed type observation and whose solution is discussed via the innovation approach.

Title:Statistical Dominance Over Pareto Optimal Mean-variance Portfolios
Author(s):Giacomo di Tollo and Pamela Peretti and Mauro Birattari and Eliseo Ferrante and Thomas Stuetzle
Files: [pdf] [bib]
Abstract:Portfolios belonging to the Mean-Variance Efficient set are Pareto-Efficient. In this work we outline a procedure to understand if this assertion is always true in practical sense, or if some portfolios belonging to the frontier can be considered as dominated in a probabilistic way.