Springer
Parameter Estimation in Stochastic Volatility Models
Lowest observed price
Prices at stores
1 offerPrices are the most recently observed prices. Check the current price, availability and delivery costs at the store.
Price history
1 price observationThe chart shows the lowest recorded product price on each observation day. Prices between observations have not been verified.
- Lowest observed
- €128.39
- Highest observed
- €128.39
- Latest history observation
Show price observation
| Price observed (Finnish time) | Price |
|---|---|
| €128.39 |
Product details
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.
- Brand
- Springer
- EAN / GTIN
- 9783031038617