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A stationary Kyle setup: microfounding propagator models. (English) Zbl 1504.91307

Summary: We provide an economically sound micro-foundation to linear price impact models, by deriving them as the equilibrium of a suitable agent-based system. In particular, we retrieve the so-called propagator model as the high-frequency limit of a generalized Kyle model, in which the assumption of a terminal time at which fundamental information is revealed is dropped. This allows to describe a stationary market populated by asymmetrically-informed rational agents. We investigate the stationary equilibrium of the model, and show that the setup is compatible with universal price diffusion at small times, and non-universal mean-reversion at time scales at which fluctuations in fundamentals decay. Our model suggests that at high frequency one should observe a quasi-permanent impact component, driven by slow fluctuations of fundamentals, and a faster transient one, whose timescale should be set by the persistence of the order flow.

MSC:

91G15 Financial markets

Software:

PMTK

References:

[1] Malkiel B G 2003 The efficient market hypothesis and its critics J. Econ. Perspect.17 59-82 · doi:10.1257/089533003321164958
[2] O’Hara M 1998 Market Microstructure Theory (Oxford: Blackwell)
[3] Shiller R 1981 Do stock prices move too much to be justified by subsequent changes in dividends? Am. Econ. Rev.71 421-36
[4] Bouchaud J-P 2008 Economics need a scientific revolution Nature455 11 · doi:10.1038/4551181a
[5] Bouchaud J-P, Gefen Y, Potters M and Wyart M 2004 Fluctuations and response in financial markets: the subtle nature of ‘random’ price changes Quant. Finance4 176-90 · Zbl 1405.91730 · doi:10.1080/14697680400000022
[6] Taranto D E, Bormetti G, Bouchaud J-P, Lillo F and Tóth B 2018 Linear models for the impact of order flow on prices. I. History dependent impact models Quant. Finance18 903-15 · Zbl 1400.91564 · doi:10.1080/14697688.2017.1395903
[7] Benzaquen M, Mastromatteo I, Eisler Z and Bouchaud J-P 2017 Dissecting cross-impact on stock markets: an empirical analysis J. Stat. Mech. 023406 · doi:10.1088/1742-5468/aa53f7
[8] Joulin A, Lefevre A, Grunberg D and Bouchaud J-P 2008 Stock price jumps: news and volume play a minor role Wilmott Mag.
[9] Kyle A S 1985 Continuous auctions and insider trading Econometrica53 1315-35 · Zbl 0571.90010 · doi:10.2307/1913210
[10] Bernhardt D, Seiler P and Taub B 2010 Speculative dynamics Econ. Theor.44 1-52 · Zbl 1231.91495 · doi:10.1007/s00199-009-0456-y
[11] Hewing L, Wabersich K P, Menner M and Zeilinger M N 2020 Learning-based model predictive control: toward safe learning in control Annu. Rev. Control Robot. Auton. Syst.3 269-96 · doi:10.1146/annurev-control-090419-075625
[12] Bernhardt D and Miao J 2004 Informed trading when information becomes stale J. Finance59 339-90 · doi:10.1111/j.1540-6261.2004.00635.x
[13] Murphy K P 2012 Machine Learning(A Probabilistic Perspective) (Cambridge, MA: MIT Press) · Zbl 1295.68003
[14] Benhamou E 2018 Kalman filter demystified: from intuition to probabilistic graphical model to real case in financial markets SSRN Electronic J.
[15] Çetin U and Danilova A 2016 Markovian Nash equilibrium in financial markets with asymmetric information and related forward-backward systems Ann. Appl. Probab.26 1996-2029 · Zbl 1353.91050 · doi:10.1214/15-aap1138
[16] Cho K-H 2003 Continuous auctions and insider trading: uniqueness and risk aversion Finance Stochast.7 47-71 · Zbl 1066.91057 · doi:10.1007/s007800200078
[17] Tóth B, Palit I, Lillo F and Farmer J D 2015 Why is equity order flow so persistent? J. Econ. Dyn. Control51 218-39 · Zbl 1402.91179 · doi:10.1016/j.jedc.2014.10.007
[18] Çetin U 2018 Financial equilibrium with asymmetric information and random horizon Finance Stochast.22 97-126 · Zbl 1422.91799 · doi:10.1007/s00780-017-0348-0
[19] Li C and Xing H 2013 Asymptotic Glosten-Milgrom equilibrium SSRN Electronic J.6 1-35 · doi:10.2139/ssrn.2342136
[20] Donier J, Bonart J, Mastromatteo I and Bouchaud J-P 2014 A fully consistent, minimal model for non-linear market impact Quant. Finance15 1109-21 · Zbl 1398.91274 · doi:10.1080/14697688.2015.1040056
[21] Boulatov A and Livdan D 2006 Strategic trading with market closures Society for Economic Dynamics, 2006 Meeting Papers
[22] Allan T 1996 Excess volatility and predictability of stock prices in autoregressive dividend models with learning Rev. Econ. Stud.63 523-57 · Zbl 0864.90010 · doi:10.2307/2297792
[23] Hommes C H and Zhu M 2012 Behavioral learning equilibria 150 · doi:10.2139/ssrn.2200399
[24] Tan L S L 2019 Explicit inverse of tridiagonal matrix with applications in autoregressive modelling IMA J. Appl. Math.84 679-95 · Zbl 1469.65079 · doi:10.1093/imamat/hxz010
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