Monte Carlo Strategies in Option Pricing for SABR Model Public Deposited

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  • March 21, 2019
  • Yin, Leicheng
    • Affiliation: College of Arts and Sciences, Department of Statistics and Operations Research
  • Option pricing problems have always been a hot topic in mathematical finance. The SABR model is a stochastic volatility model, which attempts to capture the volatility smile in derivatives markets. To price options under SABR model, there are analytical and probability approaches. The probability approach i.e. the Monte Carlo method suffers from computation inefficiency due to high dimensional state spaces. In this work, we adopt the probability approach for pricing options under the SABR model. The novelty of our contribution lies in reducing the dimensionality of Monte Carlo simulation from the high dimensional state space (time series of the underlying asset) to the 2-D or 3-D random vectors (certain summary statistics of the volatility path).
Date of publication
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Rights statement
  • In Copyright
  • Ji, Chuanshu
  • Zhang, Kai
  • Ziya, Serhan
  • Kulkarni, Vidyadhar
  • Argon, Nilay
  • Doctor of Philosophy
Degree granting institution
  • University of North Carolina at Chapel Hill Graduate School
Graduation year
  • 2016

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