Stochastic volatility and realized stochastic volatility models / Makoto Takahashi, Yasuhiro Omori, Toshiaki Watanabe.
Takahashi, Makoto, author.; Omori, Yasuhiro, author.; Watanabe, Toshiaki, author.
2023
HG4515.2 .T35 2023
Available Online

Linked e-resources

Linked Resource Online Access
Concurrent users Unlimited
Authorized users Authorized users
Document Delivery Supplied Can lend chapters, not whole ebooks

Details

Title Stochastic volatility and realized stochastic volatility models / Makoto Takahashi, Yasuhiro Omori, Toshiaki Watanabe.
Author Takahashi, Makoto, author.
ISBN 9789819909353 electronic book
981990935X electronic book
9789819909346
9819909341
DOI https://doi.org/10.1007/978-981-99-0935-3
Published Singapore : Springer, 2023.
Language English
Description 1 online resource (viii, 113 pages) : illustrations (some color).
Other Standard Identifiers 10.1007/978-981-99-0935-3 doi
Call Number HG4515.2 .T35 2023
Dewey Decimal Classification 332.632220151922
Summary This treatise delves into the latest advancements in stochastic volatility models, highlighting the utilization of Markov chain Monte Carlo simulations for estimating model parameters and forecasting the volatility and quantiles of financial asset returns. The modeling of financial time series volatility constitutes a crucial aspect of finance, as it plays a vital role in predicting return distributions and managing risks. Among the various econometric models available, the stochastic volatility model has been a popular choice, particularly in comparison to other models, such as GARCH models, as it has demonstrated superior performance in previous empirical studies in terms of fit, forecasting volatility, and evaluating tail risk measures such as Value-at-Risk and Expected Shortfall. The book also explores an extension of the basic stochastic volatility model, incorporating a skewed return error distribution and a realized volatility measurement equation. The concept of realized volatility, a newly established estimator of volatility using intraday returns data, is introduced, and a comprehensive description of the resulting realized stochastic volatility model is provided. The text contains a thorough explanation of several efficient sampling algorithms for latent log volatilities, as well as an illustration of parameter estimation and volatility prediction through empirical studies utilizing various asset return data, including the yen/US dollar exchange rate, the Dow Jones Industrial Average, and the Nikkei 225 stock index. This publication is highly recommended for readers with an interest in the latest developments in stochastic volatility models and realized stochastic volatility models, particularly in regards to financial risk management.
Bibliography, etc. Note Includes bibliographical references.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed April 25, 2023).
Added Author Omori, Yasuhiro, author.
Watanabe, Toshiaki, author.
Series SpringerBriefs in statistics. JSS research series in statistics. 2364-0065
Available in Other Form Print version: 9789819909346
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
All Resources
1 Introduction
2 Stochastic Volatility Model
3 Asymmetric Stochastic Volatility Model
4 Stochastic Volatility Model with Generalized Hyperbolic Skew Student's t Error
5 Realized Stochastic Volatility Model.

Browse Subjects

Show more subjects...

Statistics

from
to
Export