Abstract
In this work we investigate the portfolio selection problem (P1) and bi-directional trading (P2) when prices are interrelated. Zhang et al. (J. Comb. Optim. 23 (2012) 159–166) provided the algorithm UND which solves one variant of P2. We are interested in solutions which are optimal from a worst-case perspective. For P1, we prove the worst-case input sequence and derive the algorithm optimal portfolio for interrelated prices (OPIP). We then prove the competitive ratio and optimality. We use the idea of OPIP to solve P2 and derive the algorithm called optimal conversion for interrelated prices (OCIP). Using OCIP, we also design optimal online algorithms for bi-directional search (P3) called bi-directional UND (BUND) and optimal online search for unknown relative price bounds (RUN). We run numerical experiments and conclude that OPIP and OCIP perform well compared to other algorithms even if prices do not behave adverse.
Subject
Management Science and Operations Research,Computer Science Applications,Theoretical Computer Science
Reference19 articles.
1. Agarwal A., Hazan E., Kale S. and Schapire R.E., Algorithms for portfolio management based on the newton method. In: Proceedings of the 23rd International Conference on Machine Learning. ACM (2006) 9–16.
2. A survey on combinatorial optimization in dynamic environments
3. Borodin A., El-Yaniv R. and Gogan V., On the competitive theory and practice of portfolio selection (Extended Abstract). In: Proceedings of the 4th Latin American Symposium on Theoretical Informatics (2000) 173–196.
4. Optimal Buy-and-Hold Strategies for Financial Markets with Bounded Daily Returns
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