Modelling stock market volatility : bridging the gap to continuous time /
This essay collection focuses on the relationship between continuous time models and Autoregressive Conditionally Heteroskedastic (ARCH) models and applications. For the first time, Modelling Stock Market Volatility provides new insights about the links between these two models and new work on pract...
| Други автори: | Rossi, Peter E. 1955- |
|---|---|
| Формат: | Електронна книга |
| Език: | English |
| Публикувано: |
San Diego :
Academic Press,
℗♭1996.
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| Предмети: | |
| Онлайн достъп: |
http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=297148 |
| Подобни документи: |
Print version::
Modelling stock market volatility. |
Съдържание:
- Modelling Stock Market Volatility Changes
- Stationarity and Persistence in the GARCH(I, I) Model
- Conditional Heteroskedasticity in Asset Returns: A New Approach
- Good News, Bad News, Volatility, and Betas
- ARCH Models as Diffusion Approximations
- Filtering and Forecasting with Misspecified ARCH Models I: Getting the Right Variance with the Wrong Model
- Filtering and Forecasting with Misspecified ARCH Models II: Making the Right Forecast with the Wrong Model
- Asymptotic Filtering Theory for Univariate ARCH Models
- Asymptotic Filtering Theory for Multivariate ARCH Models
- Continuous Record Asymptotics for Rolling Sample Variance Estimators
- Estimating Diffusion Models of Stochastic Volatility
- Specification Analysis of Continuous Time Models in Finance
- Back to the Future: Generating Moment Implications for Continuous-Time Markov Processes
- Nonparametric Pricing of Interest Rate Derivative Securities
- Index.