Share This Article:

Optimal Execution in Illiquid Market with the Absence of Price Manipulation

Abstract Full-Text HTML XML Download Download as PDF (Size:4755KB) PP. 1-14
DOI: 10.4236/jmf.2015.51001    3,134 Downloads   3,767 Views   Citations

ABSTRACT

This article shows the execution performance of the risk-averse institutional trader with constant absolute risk aversion (CARA) type utility by using the condition of no price manipulation defined in the risk neutral sense. From two linear price impact models both satisfying that condition, we have derived the unique explicit optimal execution strategy calculated backwardly with dynamic programming equations. And our study shows that the optimal execution strategy exists in the static class. The derived solution can be decomposed into mainly two components, each giving an explanation of the property of optimal execution volume. Moreover we propose two conditions in order to compare the performance of these two price models, and illustrate that the performances of the two models are surprisingly different under certain conditions.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

Kuno, S. and Ohnishi, M. (2015) Optimal Execution in Illiquid Market with the Absence of Price Manipulation. Journal of Mathematical Finance, 5, 1-14. doi: 10.4236/jmf.2015.51001.

References

[1] Alfonsi, A., Schied, A. and Slynko, A. (2012) Order Book Resilience, Price Manipulation, and the Positive Portfolio Problem. SIAM Journal on Financial Mathematics, 3, 511-533.
http://dx.doi.org/10.1137/110822098
[2] Almgren, R. and Chriss, N. (2000) Optimal Execution of Portfolio Transactions. Journal of Risk, 3, 5-39.
[3] Huberman, G. and Stanzl, W. (2005) Optimal Liquidity Trading. Review of Finance, 9, 165-200.
http://dx.doi.org/10.1007/s10679-005-7591-5
[4] Gatheral, J. (2010) No-Dynamic-Arbitrage and Market Impact. Quantitative Finance, 10,749-759.
http://dx.doi.org/10.1080/14697680903373692
[5] Obizhaeva, A. and Wang, J. (2013) Optimal Trading Strategy and Supply/Demand Dynamics. Journal of Financial Markets, 16, 1-32.
http://dx.doi.org/10.1016/j.finmar.2012.09.001
[6] Bouchaud, J.-P., Farmer, J.D. and Lillo, F. (2009) How Markets Slowly Digest Changes in Supply and Demand. Handbook of Financial Markets: Dynamics and Evolution, Elsevier, Berlin.
[7] Schied, A., Schöneborn, T. and Teharanci, M. (2010) Optimal Basket Liquidation for CARA Investors Is Deterministic. Applied Mathematical Finance, 17, 471-489.
http://dx.doi.org/10.1080/13504860903565050
[8] Bertsimas, D. and Lo, A. (1998) Optimal Control of Execution Costs. Journal of Financial Markets, 1, 1-50.
http://dx.doi.org/10.1137/S0363012995291609
[9] Huberman, G. and Stanzl, W. (2004) Price Manipulation and Quasi-Arbitrage. Econometrica, 74, 1247-1275.
http://dx.doi.org/10.1111/j.1468-0262.2004.00531.x
[10] Kunou, S. and Ohnishi, M. (2010) Optimal Execution Strategy with Price Impact. Research Institute for Mathematical Sciences (RIMS) Kokyuroku, 1645, 234-247.
[11] Lorenz, C. and Schied, A. (2013) Drift Dependence of Optimal Trade Execution Strategies under Transient Price Impact. Finance and Stochastics, 17, 743-770.
http://dx.doi.org/10.1007/s00780-013-0211-x
[12] Almgren, R., Thum, C., Hauptmann, E. and Li, H. (2005) Equity Market Impact. Risk, 18, 57-62.
[13] Bouchaud, J.-P., Mézard, M. and Potters, M. (2004) Statistical Properties of Stock Order Books: Empirical Results and Models. Quantitative Finance, 2, 251-256.
http://dx.doi.org/10.1088/1469-7688/2/4/301

  
comments powered by Disqus

Copyright © 2019 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.