Book Details
Format
Hardback or Cased Book
ISBN-10
3031038606
ISBN-13
9783031038600
Edition
2022 ed.
Publisher
Springer International Publishing AG
Imprint
Springer International Publishing AG
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Aug 7th, 2022
Print length
613 Pages
Weight
1,116 grams
Dimensions
24.10 x 16.60 x 4.20 cms
Product Classification:
Probability & statisticsProbability and statisticsApplied mathematics
Ksh 23,400.00
Werezi Extended Catalogue
0 in stock
Delivery Location
Delivery fee: Select location
Secure
Quality
Fast
This book develops alternative methods to estimate the unknown parameters in stochastic volatility models, offering a new approach to test model accuracy.
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.
Get Parameter Estimation in Stochastic Volatility Models by at the best price and quality guaranteed only at Werezi Africa's largest book ecommerce store. The book was published by Springer International Publishing AG and it has pages.
