• Title/Summary/Keyword: Malliavin derivative

Search Result 3, Processing Time 0.018 seconds

GENERALIZED BROWNIAN MOTIONS WITH APPLICATION TO FINANCE

  • Chung, Dong-Myung;Lee, Jeong-Hyun
    • Journal of the Korean Mathematical Society
    • /
    • v.43 no.2
    • /
    • pp.357-371
    • /
    • 2006
  • Let $X\;=\;(X_t,\;t{\in}[0, T])$ be a generalized Brownian motion(gBm) determined by mean function a(t) and variance function b(t). Let $L^2({\mu})$ denote the Hilbert space of square integrable functionals of $X\;=\;(X_t - a(t),\; t {in} [0, T])$. In this paper we consider a class of nonlinear functionals of X of the form F(. + a) with $F{in}L^2({\mu})$ and discuss their analysis. Firstly, it is shown that such functionals do not enjoy, in general, the square integrability and Malliavin differentiability. Secondly, we establish regularity conditions on F for which F(.+ a) is in $L^2({\mu})$ and has its Malliavin derivative. Finally we apply these results to compute the price and the hedging portfolio of a contingent claim in our financial market model based on a gBm X.

GENERATING SAMPLE PATHS AND THEIR CONVERGENCE OF THE GEOMETRIC FRACTIONAL BROWNIAN MOTION

  • Choe, Hi Jun;Chu, Jeong Ho;Kim, Jongeun
    • Bulletin of the Korean Mathematical Society
    • /
    • v.55 no.4
    • /
    • pp.1241-1261
    • /
    • 2018
  • We derive discrete time model of the geometric fractional Brownian motion. It provides numerical pricing scheme of financial derivatives when the market is driven by geometric fractional Brownian motion. With the convergence analysis, we guarantee the convergence of Monte Carlo simulations. The strong convergence rate of our scheme has order H which is Hurst parameter. To obtain our model we need to convert Wick product term of stochastic differential equation into Wick free discrete equation through Malliavin calculus but ours does not include Malliavin derivative term. Finally, we include several numerical experiments for the option pricing.