Parameter Estimation In Stochastic Volatility Models PDF Download
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| Author | : Jaya P. N. Bishwal |
| Publisher | : Springer Nature |
| Total Pages | : 634 |
| Release | : 2022-08-06 |
| Genre | : Mathematics |
| ISBN | : 3031038614 |
Download Parameter Estimation in Stochastic Volatility Models Book in PDF, ePub and Kindle
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.
| Author | : Ibukun O.O. Amusan |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2013 |
| Genre | : |
| ISBN | : |
Download Parameter estimation for a stochastic volatility model with coupled additive and multiplicative noise Book in PDF, ePub and Kindle
| Author | : Frederi G. Viens |
| Publisher | : John Wiley & Sons |
| Total Pages | : 468 |
| Release | : 2011-12-20 |
| Genre | : Business & Economics |
| ISBN | : 0470876883 |
Download Handbook of Modeling High-Frequency Data in Finance Book in PDF, ePub and Kindle
CUTTING-EDGE DEVELOPMENTS IN HIGH-FREQUENCY FINANCIAL ECONOMETRICS In recent years, the availability of high-frequency data and advances in computing have allowed financial practitioners to design systems that can handle and analyze this information. Handbook of Modeling High-Frequency Data in Finance addresses the many theoretical and practical questions raised by the nature and intrinsic properties of this data. A one-stop compilation of empirical and analytical research, this handbook explores data sampled with high-frequency finance in financial engineering, statistics, and the modern financial business arena. Every chapter uses real-world examples to present new, original, and relevant topics that relate to newly evolving discoveries in high-frequency finance, such as: Designing new methodology to discover elasticity and plasticity of price evolution Constructing microstructure simulation models Calculation of option prices in the presence of jumps and transaction costs Using boosting for financial analysis and trading The handbook motivates practitioners to apply high-frequency finance to real-world situations by including exclusive topics such as risk measurement and management, UHF data, microstructure, dynamic multi-period optimization, mortgage data models, hybrid Monte Carlo, retirement, trading systems and forecasting, pricing, and boosting. The diverse topics and viewpoints presented in each chapter ensure that readers are supplied with a wide treatment of practical methods. Handbook of Modeling High-Frequency Data in Finance is an essential reference for academics and practitioners in finance, business, and econometrics who work with high-frequency data in their everyday work. It also serves as a supplement for risk management and high-frequency finance courses at the upper-undergraduate and graduate levels.
| Author | : Makoto Takahashi |
| Publisher | : Springer Nature |
| Total Pages | : 120 |
| Release | : 2023-04-18 |
| Genre | : Business & Economics |
| ISBN | : 981990935X |
Download Stochastic Volatility and Realized Stochastic Volatility Models Book in PDF, ePub and Kindle
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.
| Author | : Jack C. Lee |
| Publisher | : Springer |
| Total Pages | : 0 |
| Release | : 2012-03-19 |
| Genre | : Mathematics |
| ISBN | : 9781461275299 |
Download Modelling and Prediction Honoring Seymour Geisser Book in PDF, ePub and Kindle
Modelling and Prediction Honoring Seymour Geisser contains the refereed proceedings of the Conference on Forecasting, Prediction, and Modelling held at National Chiao Tung University, Taiwan in 1994. The papers discuss general methodological issues; prediction; design of experiments and classification; prior distributions and estimation; posterior odds, testing, and model selection; modelling and prediction in finance; and time series modelling and applications. Specific topics include very interesting and topical statistical issues related to DNA fingerprinting and spatial image reconstruction, foundational issues for applied statistics and testing hypotheses, forecasting tax revenues and bond prices, and assessing oxone depletion.
| Author | : Sassan Alizadeh |
| Publisher | : |
| Total Pages | : 82 |
| Release | : 2001 |
| Genre | : Economics |
| ISBN | : |
Download High- and Low-frequency Exchange Rate Volatility Dynamics Book in PDF, ePub and Kindle
We propose using the price range in the estimation of stochastic volatility models. We show theoretically, numerically, and empirically that the range is not only a highly efficient volatility proxy, but also that it is approximately Gaussian and robust to microstructure noise. The good properties of the range imply that range-based Gaussian quasi-maximum likelihood estimation produces simple and highly efficient estimates of stochastic volatility models and extractions of latent volatility series. We use our method to examine the dynamics of daily exchange rate volatility and discover that traditional one-factor models are inadequate for describing simultaneously the high- and low-frequency dynamics of volatility. Instead, the evidence points strongly toward two-factor models with one highly persistent factor and one quickly mean-reverting factor.
| Author | : Mr.Noureddine Krichene |
| Publisher | : International Monetary Fund |
| Total Pages | : 30 |
| Release | : 2003-06-01 |
| Genre | : Business & Economics |
| ISBN | : 1451854846 |
Download Modeling Stochastic Volatility with Application to Stock Returns Book in PDF, ePub and Kindle
A stochastic volatility model where volatility was driven solely by a latent variable called news was estimated for three stock indices. A Markov chain Monte Carlo algorithm was used for estimating Bayesian parameters and filtering volatilities. Volatility persistence being close to one was consistent with both volatility clustering and mean reversion. Filtering showed highly volatile markets, reflecting frequent pertinent news. Diagnostics showed no model failure, although specification improvements were always possible. The model corroborated stylized findings in volatility modeling and has potential value for market participants in asset pricing and risk management, as well as for policymakers in the design of macroeconomic policies conducive to less volatile financial markets.
| Author | : Steven Cannon Hogan |
| Publisher | : |
| Total Pages | : 246 |
| Release | : 2000 |
| Genre | : |
| ISBN | : |
Download Nonparametric Estimation of Stochastic Volatility Models Book in PDF, ePub and Kindle
| Author | : Jaya P. N. Bishwal |
| Publisher | : Springer |
| Total Pages | : 268 |
| Release | : 2007-09-26 |
| Genre | : Mathematics |
| ISBN | : 3540744487 |
Download Parameter Estimation in Stochastic Differential Equations Book in PDF, ePub and Kindle
Parameter estimation in stochastic differential equations and stochastic partial differential equations is the science, art and technology of modeling complex phenomena. The subject has attracted researchers from several areas of mathematics. This volume presents the estimation of the unknown parameters in the corresponding continuous models based on continuous and discrete observations and examines extensively maximum likelihood, minimum contrast and Bayesian methods.
| Author | : Robert A. Meyers |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 919 |
| Release | : 2010-11-03 |
| Genre | : Business & Economics |
| ISBN | : 1441977007 |
Download Complex Systems in Finance and Econometrics Book in PDF, ePub and Kindle
Finance, Econometrics and System Dynamics presents an overview of the concepts and tools for analyzing complex systems in a wide range of fields. The text integrates complexity with deterministic equations and concepts from real world examples, and appeals to a broad audience.
