Limit theorems for nearly unstable Hawkes processes

Because of their tractability and their natural interpretations in term of market quantities, Hawkes processes are nowadays widely used in high-frequency finance. However, in practice, the statistical estimation results seem to show that very often, only nearly unstable Hawkes processes are able to fit the data properly. By nearly unstable, we mean that the $L^1$ norm of their kernel is close to unity. We study in this work such processes for which the stability condition is almost violated. Our main result states that after suitable rescaling, they asymptotically behave like integrated Cox-Ingersoll-Ross models. Thus, modeling financial order flows as nearly unstable Hawkes processes may be a good way to reproduce both their high and low frequency stylized facts. We then extend this result to the Hawkes-based price model introduced by Bacry et al. [Quant. Finance 13 (2013) 65-77]. We show that under a similar criticality condition, this process converges to a Heston model. Again, we recover well-known stylized facts of prices, both at the microstructure level and at the macroscopic scale.

[1]  M. Rosenbaum,et al.  Limit theorems for nearly unstable Hawkes processes: Version with technical appendix , 2014 .

[2]  Gyula Pap,et al.  Asymptotic behavior of unstable INAR(p) processes , 2009, 0908.4560.

[3]  F. Lillo,et al.  The Long Memory of the Efficient Market , 2003, cond-mat/0311053.

[4]  A. C. Davison,et al.  Estimating value-at-risk: a point process approach , 2005 .

[5]  Stephen J. Hardiman,et al.  Critical reflexivity in financial markets: a Hawkes process analysis , 2013, 1302.1405.

[6]  Jeremy H. Large Measuring the resiliency of an electronic limit order book , 2007 .

[7]  Y. Ogata The asymptotic behaviour of maximum likelihood estimators for stationary point processes , 1978 .

[8]  J. Mémin,et al.  Convergence en loi des suites d'intégrales stochastiques sur l'espace $$\mathbb{D}$$ 1 de Skorokhod , 1989 .

[9]  Kay Giesecke,et al.  Affine Point Processes and Portfolio Credit Risk , 2010, SIAM J. Financial Math..

[10]  Luc Bauwens,et al.  Dynamic Latent Factor Models for Intensity Processes , 2004 .

[11]  J. Doob Stochastic processes , 1953 .

[12]  A. Hawkes Point Spectra of Some Mutually Exciting Point Processes , 1971 .

[13]  Patrick Hewlett Clustering of order arrivals , price impact and trade path optimisation , 2006 .

[14]  P. Embrechts,et al.  Multivariate Hawkes processes: an application to financial data , 2011, Journal of Applied Probability.

[15]  A. Hawkes Spectra of some self-exciting and mutually exciting point processes , 1971 .

[16]  Jean-Philippe Bouchaud,et al.  Relation between bid–ask spread, impact and volatility in order-driven markets , 2006, physics/0603084.

[17]  T. Alderweireld,et al.  A Theory for the Term Structure of Interest Rates , 2004, cond-mat/0405293.

[18]  Ulrike Goldschmidt,et al.  An Introduction To The Theory Of Point Processes , 2016 .

[19]  Emmanuel Bacry,et al.  Hawkes model for price and trades high-frequency dynamics , 2013, 1301.1135.

[20]  D. Sornette,et al.  Quantifying reflexivity in financial markets: towards a prediction of flash crashes , 2012, 1201.3572.

[21]  Financial Valuation and Risk Management Working Paper No . 134 A point process approach to Value-at-Risk estimation , 2003 .

[22]  S. Heston A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options , 1993 .

[23]  Results on Generalized Mittag-Leffler Function via Laplace Transform , 2013 .

[24]  D. Sornette,et al.  Quantifying Reflexivity in Financial Markets: Towards a Prediction of Flash Crashes , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.

[25]  Clive G. Bowsher Modelling Security Market Events in Continuous Time: Intensity Based, Multivariate Point Process Models , 2003 .

[26]  L. Adamopoulos Cluster models for earthquakes: Regional comparisons , 1976 .

[27]  V. Kalashnikov,et al.  Geometric Sums: Bounds for Rare Events with Applications: Risk Analysis, Reliability, Queueing , 1997 .

[28]  A. Shiryayev On Sums of Independent Random Variables , 1992 .

[29]  A. Hawkes,et al.  A cluster process representation of a self-exciting process , 1974, Journal of Applied Probability.

[30]  Yacine Ait-Sahalia,et al.  Modeling Financial Contagion Using Mutually Exciting Jump Processes , 2010 .

[31]  Emmanuel Bacry,et al.  Modelling microstructure noise with mutually exciting point processes , 2011, 1101.3422.

[32]  P. Protter,et al.  Weak Limit Theorems for Stochastic Integrals and Stochastic Differential Equations , 1991 .

[33]  J. Jacod Multivariate point processes: predictable projection, Radon-Nikodym derivatives, representation of martingales , 1975 .

[34]  P. Reynaud-Bouret,et al.  Adaptive estimation for Hawkes processes; application to genome analysis , 2009, 0903.2919.

[35]  J. Bouchaud,et al.  Fluctuations and Response in Financial Markets: The Subtle Nature of 'Random' Price Changes , 2003, cond-mat/0307332.

[36]  Thibault Jaisson,et al.  Market impact as anticipation of the order flow imbalance , 2014, 1402.1288.

[37]  A. Shiryaev,et al.  Limit Theorems for Stochastic Processes , 1987 .

[38]  Lingjiong Zhu Central Limit Theorem for Nonlinear Hawkes Processes , 2013, Journal of Applied Probability.

[39]  Laurent Massoulié,et al.  Hawkes branching point processes without ancestors , 2001, Journal of Applied Probability.

[40]  E. Bacry,et al.  Non-parametric kernel estimation for symmetric Hawkes processes. Application to high frequency financial data , 2011, 1112.1838.

[41]  R. Cowan An introduction to the theory of point processes , 1978 .

[42]  Didier Sornette,et al.  Apparent criticality and calibration issues in the Hawkes self-excited point process model: application to high-frequency financial data , 2013, 1308.6756.

[43]  M. B. Alaya,et al.  Parameter Estimation for the Square-Root Diffusions: Ergodic and Nonergodic Cases , 2012 .

[44]  Emmanuel Bacry,et al.  Scaling limits for Hawkes processes and application to financial statistics , 2012, 1202.0842.

[45]  P. Billingsley,et al.  Convergence of Probability Measures , 1970, The Mathematical Gazette.