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Optimal liquidation under partial information with price impact

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  • Colaneri, Katia
  • Eksi, Zehra
  • Frey, Rüdiger
  • Szölgyenyi, Michaela

Abstract

We study the optimal liquidation problem in a market model where the bid price follows a geometric pure jump process whose local characteristics are driven by an unobservable finite-state Markov chain and by the liquidation rate. This model is consistent with stylized facts of high frequency data such as the discrete nature of tick data and the clustering in the order flow. We include both temporary and permanent effects into our analysis. We use stochastic filtering to reduce the optimal liquidation problem to an equivalent optimization problem under complete information. This leads to a stochastic control problem for piecewise deterministic Markov processes (PDMPs). We carry out a detailed mathematical analysis of this problem. In particular, we derive the optimality equation for the value function, we characterize the value function as continuous viscosity solution of the associated dynamic programming equation, and we prove a novel comparison result. The paper concludes with numerical results illustrating the impact of partial information and price impact on the value function and on the optimal liquidation rate.

Suggested Citation

  • Colaneri, Katia & Eksi, Zehra & Frey, Rüdiger & Szölgyenyi, Michaela, 2020. "Optimal liquidation under partial information with price impact," Stochastic Processes and their Applications, Elsevier, vol. 130(4), pages 1913-1946.
  • Handle: RePEc:eee:spapps:v:130:y:2020:i:4:p:1913-1946
    DOI: 10.1016/j.spa.2019.06.004
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    References listed on IDEAS

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    1. He, Hua & Mamaysky, Harry, 2005. "Dynamic trading policies with price impact," Journal of Economic Dynamics and Control, Elsevier, vol. 29(5), pages 891-930, May.
    2. Jim Gatheral & Alexander Schied, 2011. "Optimal Trade Execution Under Geometric Brownian Motion In The Almgren And Chriss Framework," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 14(03), pages 353-368.
    3. Alexander Schied, 2012. "Robust Strategies for Optimal Order Execution in the Almgren-Chriss Framework," Papers 1204.2717, arXiv.org, revised May 2013.
    4. Alexander Schied & Torsten Schöneborn, 2009. "Risk aversion and the dynamics of optimal liquidation strategies in illiquid markets," Finance and Stochastics, Springer, vol. 13(2), pages 181-204, April.
    5. Alexander Schied, 2013. "Robust Strategies for Optimal Order Execution in the Almgren--Chriss Framework," Applied Mathematical Finance, Taylor & Francis Journals, vol. 20(3), pages 264-286, July.
    6. Nicole Bäuerle & Ulrich Rieder, 2009. "MDP algorithms for portfolio optimization problems in pure jump markets," Finance and Stochastics, Springer, vol. 13(4), pages 591-611, September.
    7. Rüdiger Frey & Thorsten Schmidt, 2012. "Pricing and hedging of credit derivatives via the innovations approach to nonlinear filtering," Finance and Stochastics, Springer, vol. 16(1), pages 105-133, January.
    8. Charles-Albert Lehalle & Othmane Mounjid & Mathieu Rosenbaum, 2018. "Optimal liquidity-based trading tactics," Papers 1803.05690, arXiv.org.
    9. Philippe Casgrain & Sebastian Jaimungal, 2019. "Trading algorithms with learning in latent alpha models," Mathematical Finance, Wiley Blackwell, vol. 29(3), pages 735-772, July.
    10. Bertsimas, Dimitris & Lo, Andrew W., 1998. "Optimal control of execution costs," Journal of Financial Markets, Elsevier, vol. 1(1), pages 1-50, April.
    11. �lvaro Cartea & Sebastian Jaimungal, 2013. "Modelling Asset Prices for Algorithmic and High-Frequency Trading," Applied Mathematical Finance, Taylor & Francis Journals, vol. 20(6), pages 512-547, December.
    12. Andersen, Torben G, 1996. "Return Volatility and Trading Volume: An Information Flow Interpretation of Stochastic Volatility," Journal of Finance, American Finance Association, vol. 51(1), pages 169-204, March.
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    Citations

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    Cited by:

    1. Felix Dammann & Giorgio Ferrari, 2023. "Optimal execution with multiplicative price impact and incomplete information on the return," Finance and Stochastics, Springer, vol. 27(3), pages 713-768, July.
    2. Dammann, Felix & Ferrari, Giorgio, 2022. "Optimal Execution with Multiplicative Price Impact and Incomplete Information on the Return," Center for Mathematical Economics Working Papers 663, Center for Mathematical Economics, Bielefeld University.
    3. Felix Dammann & Giorgio Ferrari, 2022. "Optimal Execution with Multiplicative Price Impact and Incomplete Information on the Return," Papers 2202.10414, arXiv.org, revised Nov 2022.
    4. Colaneri, Katia & Frey, Rüdiger, 2021. "Classical solutions of the backward PIDE for Markov modulated marked point processes and applications to CAT bonds," Insurance: Mathematics and Economics, Elsevier, vol. 101(PB), pages 498-507.
    5. Bandini, Elena & Calvia, Alessandro & Colaneri, Katia, 2022. "Stochastic filtering of a pure jump process with predictable jumps and path-dependent local characteristics," Stochastic Processes and their Applications, Elsevier, vol. 151(C), pages 396-435.
    6. Giorgia Callegaro & Claudia Ceci & Giorgio Ferrari, 2020. "Optimal reduction of public debt under partial observation of the economic growth," Finance and Stochastics, Springer, vol. 24(4), pages 1083-1132, October.

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