Optimal Limit Order Book Trading Strategies with Stochastic Volatility in the Underlying Asset

dc.authoridUğur, Ömür/0000-0001-9348-7775
dc.authorscopusid57190164851
dc.authorscopusid23994756900
dc.authorscopusid24402879000
dc.authorwosidUğur, Ömür/D-2361-2013
dc.contributor.authorAksoy, Ümit
dc.contributor.authorUgur, Omur
dc.contributor.authorAydoğan, Burcu
dc.contributor.otherMathematics
dc.date.accessioned2024-07-05T15:17:48Z
dc.date.available2024-07-05T15:17:48Z
dc.date.issued2023
dc.departmentAtılım Universityen_US
dc.department-temp[Aydogan, Burcu; Ugur, Omur] Middle East Tech Univ, Inst Appl Math, TR-06800 Ankara, Turkey; [Aydogan, Burcu; Aksoy, Umit] Atilim Univ, Dept Math, TR-06830 Ankara, Turkey; [Aydogan, Burcu] Rhein Westfal TH Aachen, Chair Math Uncertainty Quantificat, Pontdriesch 14-16, D-52062 Aachen, Germanyen_US
dc.descriptionUğur, Ömür/0000-0001-9348-7775en_US
dc.description.abstractIn quantitative finance, there have been numerous new aspects and developments related with the stochastic control and optimization problems which handle the controlled variables of performing the behavior of a dynamical system to achieve certain objectives. In this paper, we address the optimal trading strategies via price impact models using Heston stochastic volatility framework including jump processes either in price or in volatility of the price dynamics with the aim of maximizing expected return of the trader by controlling the inventories. Two types of utility functions are considered: quadratic and exponential. In both cases, the remaining inventories of the market maker are charged with a liquidation cost. In order to achieve the optimal quotes, we control the inventory risk and follow the influence of each parameter in the model to the best bid and ask prices. We show that the risk metrics including profit and loss distribution (PnL), standard deviation and Sharpe ratio play important roles for the trader to make decisions on the strategies. We apply finite differences and linear interpolation as well as extrapolation techniques to obtain a solution of the nonlinear Hamilton-Jacobi-Bellman (HJB) equation. Moreover, we consider different cases on the modeling to carry out the numerical simulations.en_US
dc.description.sponsorshipProjekt DEALen_US
dc.description.sponsorshipOpen Access funding enabled and organized by Projekt DEAL. The authors have not disclosed any funding.en_US
dc.identifier.citation0
dc.identifier.doi10.1007/s10614-022-10272-4
dc.identifier.endpage324en_US
dc.identifier.issn0927-7099
dc.identifier.issn1572-9974
dc.identifier.issue1en_US
dc.identifier.scopus2-s2.0-85134076058
dc.identifier.startpage289en_US
dc.identifier.urihttps://doi.org/10.1007/s10614-022-10272-4
dc.identifier.urihttps://hdl.handle.net/20.500.14411/1794
dc.identifier.volume62en_US
dc.identifier.wosWOS:000812450800001
dc.identifier.wosqualityQ2
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectMarket makingen_US
dc.subjectHigh-frequency tradingen_US
dc.subjectLimit order booken_US
dc.subjectStochastic controlen_US
dc.subjectHamilton-Jacobi-Bellman equationen_US
dc.titleOptimal Limit Order Book Trading Strategies with Stochastic Volatility in the Underlying Asseten_US
dc.typeArticleen_US
dspace.entity.typePublication
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