Deep Learning for Dynamic Portfolio Optimization

Deep Learning for Dynamic Portfolio Optimization

This thesis considers a deep learning approach to a dynamic portfolio optimization problem. A proposed deep learning algorithm is tested on a simplified version of the problem with promising results, which suggest continued testing of the algorithm, on a larger scale for the original problem. First...

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Bibliographic Details
Main Author: Molnö, Victor
Format: Others
Language:English
Published: KTH, Matematisk statistik 2021
Subjects:
Dynamic portfolio optimization
No-trade-region
Deep learning
Policy iteration
Dynamisk portföljoptimering
Handelsstoppregion
Djupinlärning
Policyiterering
Probability Theory and Statistics
Sannolikhetsteori och statistik
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-304667

Internet

http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-304667

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