The First-passage Time of the Brownian Motion to a Curved Boundary: an Algorithmic Approach

Under some weak conditions, the first-passage time of the Brownian motion to a continuous curved boundary is an almost surely finite stopping time. Its probability density function (pdf) is explicitly known only in few particular cases. Several mathematical studies proposed to approximate the pdf in a quite general framework or even to simulate this hitting time using a discrete time approximation of the Brownian motion. The authors study a new algorithm which permits to simulate the first-passage time using an iterating procedure. The convergence rate presented in this paper suggests that the method is very efficient.

[1]  W. R. Schucany,et al.  Generating Random Variates Using Transformations with Multiple Roots , 1976 .

[2]  Owen D. Jones,et al.  Simulation of Brownian motion at first-passage times , 2008, Math. Comput. Simul..

[3]  Volker Strassen,et al.  Almost sure behavior of sums of independent random variables and martingales , 1967 .

[4]  G. O. Roberts,et al.  Pricing Barrier Options with Time-Dependent Coefficients , 1997 .

[5]  R. Capocelli,et al.  Diffusion approximation and first passage time problem for a model neuron , 1971, Biological cybernetics.

[6]  Nader Ebrahimi,et al.  System reliability based on diffusion models for fatigue crack growth , 2005 .

[7]  A. G. Nobile,et al.  A computational approach to first-passage-time problems for Gauss–Markov processes , 2001 .

[8]  Liqun Wang,et al.  Crossing Probabilities for Diffusion Processes with Piecewise Continuous Boundaries , 2006, math/0612337.

[9]  Ian F. Blake,et al.  Level-crossing problems for random processes , 1973, IEEE Trans. Inf. Theory.

[10]  C. Kardaras,et al.  EFFICIENT ESTIMATION OF ONE-DIMENSIONAL DIFFUSION FIRST PASSAGE TIME DENSITIES VIA MONTE CARLO SIMULATION , 2010, 1008.1326.

[11]  E. Gobet Weak approximation of killed diffusion using Euler schemes , 2000 .

[12]  H. E. Daniels,et al.  The maximum size of a closed epidemic , 1974, Advances in Applied Probability.

[13]  P. Glasserman,et al.  A Continuity Correction for Discrete Barrier Options , 1997 .

[14]  Wulfram Gerstner,et al.  Spiking Neuron Models , 2002 .

[15]  Ioannis Karatzas,et al.  Brownian Motion and Stochastic Calculus , 1987 .

[16]  Luc Devroye,et al.  Chapter 4 Nonuniform Random Variate Generation , 2006, Simulation.

[17]  Stochastic differential equations for compounded risk reserves , 1989 .

[18]  David Terman,et al.  Mathematical foundations of neuroscience , 2010 .

[19]  Alexander Novikov,et al.  EXPLICIT BOUNDS FOR APPROXIMATION RATES OF BOUNDARY CROSSING PROBABILITIES FOR THE WIENER PROCESS , 2005 .

[20]  H. R. Lerche Boundary Crossing of Brownian Motion , 1986 .

[21]  David Lindley,et al.  CBMS-NSF REGIONAL CONFERENCE SERIES IN APPLIED MATHEMATICS , 2010 .

[22]  Brooks Ferebee,et al.  An asymptotic expansion for one-sided Brownian exit densities , 1983 .

[23]  C. Zucca,et al.  A Monte Carlo Method for the Simulation of First Passage Times of Diffusion Processes , 2001 .

[24]  J. Durbin THE FIRST-PASSAGE DENSITY OF A CONTINUOUS GAUSSIAN PROCESS , 1985 .

[25]  E. Gobet,et al.  Stopped diffusion processes: Boundary corrections and overshoot , 2007, 0706.4042.

[26]  Henry C. Tuckwell,et al.  First passage time to detection in stochastic population dynamical models for HIV-1 , 2000, Appl. Math. Lett..

[27]  A. Longtin,et al.  Fokker–Planck and Fortet Equation-Based Parameter Estimation for a Leaky Integrate-and-Fire Model with Sinusoidal and Stochastic Forcing , 2014, The Journal of Mathematical Neuroscience.

[28]  Alexander Novikov,et al.  Time-Dependent Barrier Options and Boundary Crossing Probabilities , 2003 .

[29]  E. Gobet Euler schemes and half-space approximation for the simulation of diffusion in a domain , 2001 .

[30]  L. Sacerdote,et al.  On evaluations and asymptotic approximations of first-passage-time probabilities , 1996, Advances in Applied Probability.

[31]  Laura Sacerdote,et al.  On the comparison of Feller and Ornstein-Uhlenbeck models for neural activity , 1995, Biological Cybernetics.

[32]  A. G. Nobile,et al.  A new integral equation for the evaluation of first-passage-time probability densities , 1987, Advances in Applied Probability.

[33]  Anthony N. Burkitt,et al.  A Review of the Integrate-and-fire Neuron Model: I. Homogeneous Synaptic Input , 2006, Biological Cybernetics.

[34]  B. Pacchiarotti,et al.  Large Deviation Approaches for the Numerical Computation of the Hitting Probability for Gaussian Processes , 2015 .

[35]  Shunsuke Sato,et al.  On an integral equation for first-passage-time probability densities , 1984, Journal of Applied Probability.

[36]  Virginia Giorno,et al.  AN OUTLINE OF THEORETICAL AND ALGORITHMIC APPROACHES TO FIRST PASSAGE TIME PROBLEMS WITH APPLICATIONS TO BIOLOGICAL MODELING , 1999 .

[37]  M. E. Muller Some Continuous Monte Carlo Methods for the Dirichlet Problem , 1956 .

[38]  L. Sacerdote,et al.  An improved technique for the simulation of first passage times for diffusion processes , 1999 .

[39]  A. G. Nobile,et al.  On the evaluation of first-passage-time probability densities via non-singular integral equations , 1989, Advances in Applied Probability.

[40]  Brooks Ferebee,et al.  The tangent approximation to one-sided Brownian exit densities , 1982 .

[41]  Julia Abrahams,et al.  A Survey of Recent Progress on Level-Crossing Problems for Random Processes , 1986 .

[42]  J. Durbin,et al.  The first-passage density of the Brownian motion process to a curved boundary , 1992, Journal of Applied Probability.

[43]  P. Baldi,et al.  Asymptotics of hitting probabilities for general one-dimensional pinned diffusions , 2002 .