Sammendrag
In this thesis we study stochastic optimal control problems for Volterra type dynamics. To this end, we consider two different approaches: maximum principle and dynamic programming. We use the maximum principle when working with time-changed Lévy noise drivers and obtain a sufficient and necessary optimal condition. We also discuss the two players game setting. We present the dynamic programming approach in the case of a simplified continuous Volterra forward equation, where the dependence from the past is obtained through a convolution kernel. In this case we also provide a numerical approach for the linear-quadratic case.
Artikkelliste
Paper I. G. Di Nunno, M. Giordano. Stochastic Volterra equations withtime-changed Lévy noise and maximum principles. Published in Annals of Operations Research. Ann Oper Res (2023). DOI: 10.1007/s10479-023-05303-8. The article is included in the thesis. Also available at: https://doi.org/10.1007/s10479-023-05303-8 |
Paper II. G. Di Nunno, M. Giordano. Maximum principles for stochastic time-changed Volterra games. Submitted for publication. Arxiv : 2012.06449. To be published. The paper is not available in DUO awaiting publishing. |
Paper III. G. Di Nunno, M. Giordano. Lifting of Volterra processes: optimal control and HJB equations. Submitted for publication. ArXiv : 2306.14175. To be published. The paper is not available in DUO awaiting publishing. |
Paper IV. M. Giordano, A. Yurchenko-Tytarenko. Optimal control in linear stochastic advertising models with memory. Published in Decisions Economics and Finance. Decisions Econ Finan (2023). DOI: 10.1007/s10203-023-00409-x. The article is included in the thesis. Also available at: https://doi.org/10.1007/s10203-023-00409-x |