The roles of mean residence time on herd behavior in a financial market

We investigate the herd behavior of stock prices in a finance system with the Heston model. Based on parameter estimation of the Heston model obtained by minimizing the mean square deviation between the theoretical and empirical return distributions, we simulate mean residence time of positive return (MRTPR). Plots of MRTPR against the amplitude or mean reversion of volatility demonstrate a phenomenon of herd behavior for a positive cross correlation between noise sources of the Heston model. Also, for a negative cross correlation, a phenomenon of herd behavior is observed in plots of MRTPR against the long-run variance by increasing amplitude or mean reversion of volatility.

[1]  J. Sear,et al.  Real time monitoring of propofol blood concentration in ponies anaesthetized with propofol and ketamine. , 2013, Journal of veterinary pharmacology and therapeutics.

[2]  J. Hull Options, futures & other derivatives , 2003 .

[3]  P. Cizeau,et al.  Statistical properties of the volatility of price fluctuations. , 1999, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[4]  Mantegna,et al.  Variety and volatility in financial markets , 2000, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[5]  Yu Cao,et al.  Pharmacokinetic study of cinnamaldehyde in rats by GC-MS after oral and intravenous administration. , 2014, Journal of pharmaceutical and biomedical analysis.

[6]  Rosario N. Mantegna,et al.  Book Review: An Introduction to Econophysics, Correlations, and Complexity in Finance, N. Rosario, H. Mantegna, and H. E. Stanley, Cambridge University Press, Cambridge, 2000. , 2000 .

[7]  Lewis Stiller,et al.  Computation of the mean residence time of water in the hydration shells of biomolecules , 1993, J. Comput. Chem..

[8]  Q. Hua,et al.  Mean Residence Time of Soil Organic Carbon in Aggregates Under Contrasting Land Uses Based on Radiocarbon Measurements , 2013, Radiocarbon.

[9]  T. Chiang,et al.  An empirical analysis of herd behavior in global stock markets , 2010 .

[10]  G. Bonanno,et al.  Mean escape time in a system with stochastic volatility. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

[11]  V. Yakovenko,et al.  Probability distribution of returns in the Heston model with stochastic volatility , 2002, cond-mat/0203046.

[12]  D. Brockmeier,et al.  Mean residence time. , 1986, Methods and findings in experimental and clinical pharmacology.

[13]  Jeffrey J. McDonnell,et al.  On the relationships between catchment scale and streamwater mean residence time , 2003 .

[14]  Yi Liu,et al.  Buyers’ purchasing time and herd behavior on deal-of-the-day group-buying websites , 2012, Electron. Mark..

[15]  Tao Yang,et al.  Impact of time delays on stochastic resonance in an ecological system describing vegetation , 2014 .

[16]  C. Zeng,et al.  Impact of correlated noise in an energy depot model , 2016, Scientific Reports.

[17]  M. Cipriani,et al.  Estimating a Structural Model of Herd Behavior in Financial Markets , 2010, SSRN Electronic Journal.

[18]  Tao Yang,et al.  Delay-enhanced stability and stochastic resonance in perception bistability under non-Gaussian noise , 2015 .

[19]  D. Mei,et al.  The influences of delay time on the stability of a market model with stochastic volatility , 2013 .

[20]  Josep Perelló,et al.  The Escape Problem Under Stochastic Volatility: The Heston Model , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.

[21]  Victor M. Yakovenko,et al.  Exponential distribution of financial returns at mesoscopic time lags: a new stylized fact , 2004 .

[22]  Chunhua Zeng,et al.  Noise and large time delay: Accelerated catastrophic regime shifts in ecosystems , 2012 .

[23]  Bernardo Spagnolo,et al.  Volatility Effects on the Escape Time in Financial Market Models , 2008, Int. J. Bifurc. Chaos.

[24]  J. Masoliver,et al.  First-passage and risk evaluation under stochastic volatility. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.

[25]  Underlying dynamics of typical fluctuations of an emerging market price index: The Heston model from minutes to months , 2005, physics/0506101.

[26]  Jiang-Cheng Li,et al.  The risks and returns of stock investment in a financial market , 2013 .

[27]  T. Bollerslev,et al.  Generalized autoregressive conditional heteroskedasticity , 1986 .

[28]  J. Bouchaud,et al.  Herd Behavior and Aggregate Fluctuations in Financial Markets , 1997 .

[29]  Giovanni Bonanno,et al.  Hitting time distributions in financial markets , 2007 .

[30]  P. Cizeau,et al.  Volatility distribution in the S&P500 stock index , 1997, cond-mat/9708143.

[31]  F. Long,et al.  Noises-induced regime shifts and -enhanced stability under a model of lake approaching eutrophication , 2015 .

[32]  L. Summers,et al.  The Noise Trader Approach to Finance , 1990 .

[33]  V. Eguíluz,et al.  Transmission of information and herd Behavior: an application to financial markets. , 1999, Physical review letters.

[34]  C. Zeng,et al.  Noise-enhanced stability and double stochastic resonance of active Brownian motion , 2015 .

[35]  H. Eugene Stanley,et al.  Inverse Cubic Law for the Probability Distribution of Stock Price Variations , 1998 .

[36]  Tao Yang,et al.  Delay and noise induced regime shift and enhanced stability in gene expression dynamics , 2014 .

[37]  Tao Yang,et al.  Stochastic delayed monomer-dimer surface reaction model with various dimer adsorption , 2014 .

[38]  Jiang-Cheng Li,et al.  Reverse resonance in stock prices of financial system with periodic information. , 2013, Physical review. E, Statistical, nonlinear, and soft matter physics.

[39]  Fitting the Heston Stochastic Volatility Model to Chinese Stocks , 2014 .

[40]  L. Summers,et al.  Noise Trader Risk in Financial Markets , 1990, Journal of Political Economy.

[41]  R. Mahnke,et al.  Application of Heston model and its solution to German DAX data , 2004 .

[42]  Tao Yang,et al.  Delays-based protein switches in a stochastic single-gene network , 2015 .

[43]  W. Arthur,et al.  The Economy as an Evolving Complex System II , 1988 .

[44]  Makoto Nirei Self-organized criticality in a herd behavior model of financial markets , 2008 .

[45]  P. Gopikrishnan,et al.  Inverse cubic law for the distribution of stock price variations , 1998, cond-mat/9803374.

[46]  S. Ross,et al.  A theory of the term structure of interest rates'', Econometrica 53, 385-407 , 1985 .

[47]  Enhancement of stability in randomly switching potential with metastable state , 2004, cond-mat/0407312.

[48]  Ji-Ping Huang,et al.  Experimental econophysics: Complexity, self-organization, and emergent properties , 2015 .

[49]  R. Gencay,et al.  An Introduc-tion to High-Frequency Finance , 2001 .

[50]  Rosario N. Mantegna,et al.  Probability Distribution of the Residence Times in Periodically Fluctuating Metastable Systems , 1998 .

[51]  Zhigang Zheng,et al.  Effect of coupling displacement on thermal current of Frenkel-Kontorova lattices , 2014 .

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

[53]  C. Granger,et al.  A long memory property of stock market returns and a new model , 1993 .

[54]  Honggang Li,et al.  Market dynamics and stock price volatility , 2004 .

[55]  Bernardo Spagnolo,et al.  Noise-enhanced stability in fluctuating metastable states. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[56]  A. Banerjee,et al.  A Simple Model of Herd Behavior , 1992 .

[57]  D. Hirshleifer,et al.  Herd Behaviour and Cascading in Capital Markets: A Review and Synthesis , 2003 .

[58]  Victor M. Yakovenko,et al.  Comparison between the probability distribution of returns in the Heston model and empirical data for stock indexes , 2003 .

[59]  Hirotada Ohashi,et al.  Herd behavior in a complex adaptive system , 2011, Proceedings of the National Academy of Sciences.

[60]  Giovanni Bonanno,et al.  Role of noise in a market model with stochastic volatility , 2006 .

[61]  H. Gintis,et al.  Price dynamics, financial fragility and aggregate volatility , 2015 .

[62]  Giovanni Bonanno,et al.  ESCAPE TIMES IN STOCK MARKETS , 2005 .

[63]  B. Baaquie,et al.  A path integral approach to option pricing with stochastic volatility : Some exact results , 1997, cond-mat/9708178.

[64]  Fernando Estrada,et al.  Theory of financial risk , 2011 .

[65]  R. Engle Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation , 1982 .