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An Algorithmic Approach to Optimal Asset Liquidation Problems

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  • Juri Hinz

    (University of Technology Sydney)

  • Jeremy Yee

    (University of Technology Sydney)

Abstract

This paper examines discrete-time optimal control problems arising in the context of optimal asset liquidation using recently published algorithms and code. We address these questions within a realistic framework, assuming that the order placement decisions must be adapted dynamically. Furthermore, we show how a duality-based technique can be used to assess the quality of our numerical solution.

Suggested Citation

  • Juri Hinz & Jeremy Yee, 2017. "An Algorithmic Approach to Optimal Asset Liquidation Problems," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 24(2), pages 109-129, June.
    • Handle: RePEc:kap:apfinm:v:24:y:2017:i:2:d:10.1007_s10690-017-9226-1
    DOI: 10.1007/s10690-017-9226-1
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    References listed on IDEAS

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    1. Christian Bender, 2011. "Dual pricing of multi-exercise options under volume constraints," Finance and Stochastics, Springer, vol. 15(1), pages 1-26, January.
    2. Juri Hinz & Nicholas Yap, 2015. "Algorithms for Optimal Control of Stochastic Switching Systems," Research Paper Series 352, Quantitative Finance Research Centre, University of Technology, Sydney.
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    Cited by:

    1. Juri Hinz & Tanya Tarnopolskaya & Jeremy Yee, 2020. "Efficient algorithms of pathwise dynamic programming for decision optimization in mining operations," Annals of Operations Research, Springer, vol. 286(1), pages 583-615, March.
    2. Ritesh Kumar Dubey & A. Sarath Babu & Rajneesh Ranjan Jha & Urvashi Varma, 2022. "Algorithmic Trading Efficiency and its Impact on Market-Quality," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 29(3), pages 381-409, September.

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