Maximum Likelihood Estimation in Nonlinear Fractional Stochastic Volatility Model
Journal Title: Asian Research Journal of Mathematics - Year 2017, Vol 6, Issue 2
Abstract
We study the strong consistency and asymptotic normality of the maximum likelihood estimator (MLE) of a drift parameter in a stochastic volatility model when both the asset price process and the stochastic volatility are driven by independent fractional Brownian motions. Long memory in volatility is a stylized fact. We compute the nonlinear filter in the MLE using Kitagawa algorithm.
Authors and Affiliations
Jaya P. N. Bishwal
Keywords
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- EP ID EP338489
- DOI 10.9734/ARJOM/2017/35933
- Views 114
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