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Article Dans Une Revue RAIRO - Operations Research Année : 2019

Optimal online algorithms for the portfolio selection problem, bi-directional trading and -search with interrelated prices

Résumé

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.
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Dates et versions

hal-02925350 , version 1 (29-08-2020)

Identifiants

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Pascal Schroeder, Imed Kacem, Günter Schmidt. Optimal online algorithms for the portfolio selection problem, bi-directional trading and -search with interrelated prices. RAIRO - Operations Research, 2019, 53 (2), pp.559-576. ⟨10.1051/ro/2018064⟩. ⟨hal-02925350⟩
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