Fokker-Planck equation of distributions of financial returns and power laws

Our purpose is to relate the Fokker–Planck formalism proposed by [Friedrich et al., Phys. Rev. Lett. 84 (2000) 5224] for the distribution of stock market returns to the empirically well-established power-law distribution with an exponent in the range 3–5. We show how to use Friedrich et al.'s formalism to predict that the distribution of returns is indeed asymptotically a power law with an exponent μ that can be determined from the Kramers–Moyal coefficients determined by Friedrich et al. However, with their values determined for the U.S. dollar–German mark exchange rates, the exponent μ predicted from their theory is found to be around 12, in disagreement with the often-quoted value between 3 and 5. This could be explained by the fact that the large asymptotic value of 12 does not apply to real data that lie still far from the stationary state of the Fokker–Planck description. Another possibility is that power laws are inadequate. The mechanism for the power law is based on the presence of multiplicative noise across time-scales, which is different from the multiplicative noise at fixed time-scales implicit in the ARCH models developed in the Finance literature.

[1]  Misako Takayasu,et al.  STABLE INFINITE VARIANCE FLUCTUATIONS IN RANDOMLY AMPLIFIED LANGEVIN SYSTEMS , 1997 .

[2]  D. Sornette Critical Phenomena in Natural Sciences: Chaos, Fractals, Selforganization and Disorder: Concepts and Tools , 2000 .

[3]  Adrian Pagan,et al.  The econometrics of financial markets , 1996 .

[4]  Rama Cont,et al.  Comment on "Turbulent cascades in foreign exchange markets" , 1996, cond-mat/9607120.

[5]  D. Sornette Multiplicative processes and power laws , 1997, cond-mat/9708231.

[6]  M. Dacorogna,et al.  Modelling Short-Term Volatility with GARCH and Harch Models , 1997 .

[7]  D. Sornette,et al.  Stretched exponential distributions in nature and economy: “fat tails” with characteristic scales , 1998, cond-mat/9801293.

[8]  C. Klüppelberg,et al.  Modelling Extremal Events , 1997 .

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

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

[11]  H. Kesten Random difference equations and Renewal theory for products of random matrices , 1973 .

[12]  Joachim Peinke,et al.  FOKKER-PLANCK EQUATION FOR THE ENERGY CASCADE IN TURBULENCE , 1997 .

[13]  Friedrich,et al.  How to quantify deterministic and random influences on the statistics of the foreign exchange market , 1999, Physical review letters.

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

[15]  C. Dunis,et al.  Nonlinear modelling of high frequency financial time series , 1998 .

[16]  R. Chou,et al.  ARCH modeling in finance: A review of the theory and empirical evidence , 1992 .

[17]  Sidney I. Resnick,et al.  Extremal behaviour of solutions to a stochastic difference equation with applications to arch processes , 1989 .

[18]  J. Peinke,et al.  Turbulent cascades in foreign exchange markets , 1996, Nature.

[19]  M. Dacorogna,et al.  Volatilities of different time resolutions — Analyzing the dynamics of market components , 1997 .

[20]  Olivier V. Pictet,et al.  From the bird's eye to the microscope: A survey of new stylized facts of the intra-daily foreign exchange markets , 1997, Finance Stochastics.

[21]  J. Peinke,et al.  Description of a Turbulent Cascade by a Fokker-Planck Equation , 1997 .

[22]  D. Sornette Critical Phenomena in Natural Sciences: Chaos, Fractals, Selforganization and Disorder: Concepts and Tools , 2000 .

[23]  J. M. Luck,et al.  On the distribution of a random variable occurring in 1D disordered systems , 1985 .

[24]  Casper G. de Vries,et al.  Stylized Facts of Nominal Exchange Rate Returns , 1994 .

[25]  M. Rockinger,et al.  The Tail Behavior of Stock Returns: Emerging Versus Mature Markets , 1999 .

[26]  R. Mantegna,et al.  Scaling behaviour in the dynamics of an economic index , 1995, Nature.

[27]  Stanley,et al.  Statistical properties of share volume traded in financial markets , 2000, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[28]  D. Sornette,et al.  Extreme Deviations and Applications , 1997, cond-mat/9705132.

[29]  H. Takayasu,et al.  Fractal Properties in Economics , 2000 .

[30]  D. Sornette,et al.  Convergent Multiplicative Processes Repelled from Zero: Power Laws and Truncated Power Laws , 1996, cond-mat/9609074.

[31]  D. Sornette Linear stochastic dynamics with nonlinear fractal properties , 1998 .

[32]  D. Sornette,et al.  ”Direct” causal cascade in the stock market , 1998 .

[33]  D. Sornette,et al.  Multifractal returns and hierarchical portfolio theory , 2000, cond-mat/0008069.

[34]  D. Sornette,et al.  Causal cascade in the stock market from the ``infrared'' to the ``ultraviolet'' , 1997, cond-mat/9708012.