Parameter Estimation in Stochastic Volatility Models is popular PDF and ePub book, written by Jaya P. N. Bishwal in 2022-08-06, it is a fantastic choice for those who relish reading online the Mathematics genre. Let's immerse ourselves in this engaging Mathematics book by exploring the summary and details provided below. Remember, Parameter Estimation in Stochastic Volatility Models can be Read Online from any device for your convenience.
Parameter Estimation in Stochastic Volatility Models Book PDF Summary
This book develops alternative methods to estimate the unknown parameters in stochastic volatility models, offering a new approach to test model accuracy. While there is ample research to document stochastic differential equation models driven by Brownian motion based on discrete observations of the underlying diffusion process, these traditional methods often fail to estimate the unknown parameters in the unobserved volatility processes. This text studies the second order rate of weak convergence to normality to obtain refined inference results like confidence interval, as well as nontraditional continuous time stochastic volatility models driven by fractional Levy processes. By incorporating jumps and long memory into the volatility process, these new methods will help better predict option pricing and stock market crash risk. Some simulation algorithms for numerical experiments are provided.
Detail Book of Parameter Estimation in Stochastic Volatility Models PDF
- Author : Jaya P. N. Bishwal
- Release : 06 August 2022
- Publisher : Springer Nature
- ISBN : 9783031038617
- Genre : Mathematics
- Total Page : 634 pages
- Language : English
- PDF File Size : 10,9 Mb
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