Download or read book Volatility Modeling and Analysis Via Coupled Wishart Process written by Zhong She and published by . This book was released on 2013 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Multivariate Stochastic Volatility Via Wishart Random Processes written by Alexander Philipov and published by . This book was released on 2004 with total page 57 pages. Available in PDF, EPUB and Kindle. Book excerpt: Financial models for asset and derivatives pricing, risk management, portfolio optimization, and asset allocation rely on volatility forecasts. Time-varying volatility models, such as GARCH and Stochastic Volatility (SVOL), have been successful in improving forecasts over constant volatility models. We develop a new multivariate SVOL framework for modeling financial data that assumes covariance matrices stochastically varying through a Wishart process. In our formulation, scalar variances naturally extend to covariance matrices rather than vectors of variances as in traditional SVOL models. Model fitting is performed using Markov chain Monte Carlo simulation from the posterior distribution. Due to the complexity of the model, an efficiently designed Gibbs sampler is described that produces inferences with a manageable amount of computation. Our approach is illustrated on a multivariate time series of monthly industry portfolio returns. In a test of the economic value of our model, minimum-variance portfolios based on our SVOL covariance forecasts outperform out-of-sample portfolios based on alternative covariance models such as Dynamic Conditional Correlations and factor-based covariances.

Download or read book Essays on Multivariate Stochastic Volatility Models Using Wishart Processes written by Yu-Cheng Ku and published by . This book was released on 2010 with total page 87 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Handbook of Volatility Models and Their Applications written by Luc Bauwens and published by John Wiley & Sons. This book was released on 2012-03-22 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: A complete guide to the theory and practice of volatility models in financial engineering Volatility has become a hot topic in this era of instant communications, spawning a great deal of research in empirical finance and time series econometrics. Providing an overview of the most recent advances, Handbook of Volatility Models and Their Applications explores key concepts and topics essential for modeling the volatility of financial time series, both univariate and multivariate, parametric and non-parametric, high-frequency and low-frequency. Featuring contributions from international experts in the field, the book features numerous examples and applications from real-world projects and cutting-edge research, showing step by step how to use various methods accurately and efficiently when assessing volatility rates. Following a comprehensive introduction to the topic, readers are provided with three distinct sections that unify the statistical and practical aspects of volatility: Autoregressive Conditional Heteroskedasticity and Stochastic Volatility presents ARCH and stochastic volatility models, with a focus on recent research topics including mean, volatility, and skewness spillovers in equity markets Other Models and Methods presents alternative approaches, such as multiplicative error models, nonparametric and semi-parametric models, and copula-based models of (co)volatilities Realized Volatility explores issues of the measurement of volatility by realized variances and covariances, guiding readers on how to successfully model and forecast these measures Handbook of Volatility Models and Their Applications is an essential reference for academics and practitioners in finance, business, and econometrics who work with volatility models in their everyday work. The book also serves as a supplement for courses on risk management and volatility at the upper-undergraduate and graduate levels.

Download or read book Multivariate stochastic volatility via Wishart processes a continuation written by Wolfgang Rinnergschwentner and published by . This book was released on 2011 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Exact Simulation of the Wishart Stochastic Volatility Model written by Marco Huerner and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis deals with the simulation of the Wishart stochastic volatility model (WSVM) which is a matrix generalization of the famous Heston model. Lately, an exact sampling scheme has been introduced. Its theoretical foundations are given in two papers. First, Ahdida and Alfonsi [2] find a methodology to simulate exactly the Wishart process for a general parameter space. Second, Kang and Kang [22] complete the scheme by proposing an expression for the conditional Laplace transform of the risky asset given the final state of the variance process. The thesis has two principle goals. First, we merge the theoretical foundations necessary to understand the exact sampling methodology and collect the corresponding proofs. Thereby, we build the basics for consecutive theoretical work, especially with respect to a necessary discussion of the numerical properties of the model. Second, we provide a prototype computational implementation. This implementation intends to be a first Monte Carlo framework for numerical experiments, testing purposes and further algorithmic improvements. It provides the tool to address future computation related research tasks. The current version is written in the MATLAB language m, and C.

Download or read book Bayesian Theory and Applications written by Paul Damien and published by Oxford University Press. This book was released on 2013-01-24 with total page 717 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume guides the reader along a statistical journey that begins with the basic structure of Bayesian theory, and then provides details on most of the past and present advances in this field.

Download or read book Multivariate Wishart Stochastic Volatility Models written by Bastian Gribisch and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Multiple Time Scales Stochastic Volatility Modeling Method in Stochastic Local Volatility Model Calibration written by Fan Wang and published by . This book was released on 2013 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis we study carefully the stochastic local volatility (SLV) model for pricing barrier options in foreign exchange or equity market. We first discuss the advantage and disadvantage of popular models such as stochastic volatility and local volatility that have been used for pricing the same products, then introduce the necessities to build a hybrid SLV model. We classified the calibration process of SLV model into two major parts according to parameters' different nature, and point out the slowness of the calibration procedure is mainly caused by solving the lever-age surface from Kolmogorov forward equation via the iteration method. Our major contribution is to apply the fast mean reversion volatility modeling technique and singular/regular perturbation analysis developed by Fouque, Papanicolaou, Sircar and Sølna in [24, 27, 26] to the forward equation, which gives a starting point which is proved to be close to the true solution, so that the iteration time is significantly reduced. Besides, we developed target functions specifically designed for processing exotic option quotes and give suitable numerical methods for each step of the calibration.

Download or read book Volatility Analysis with Unified Discrete and Continuous Time Models by Combining Low frequency High frequency and Option Data written by Xinyu Song and published by . This book was released on 2017 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this dissertation, we present the topic on volatility analysis with combined discrete-time and continuous-time models by employing low-frequency, high-frequency and option data. We first investigate the traditional low-frequency approach for volatility analysis that frequently adopts generalized autoregressive conditional heteroscedastic (GARCH) type models and modern high-frequency approach for volatility estimation that often employs realized volatility type estimators, examples include multi-scale realized volatility estimators, pre-averaging realized volatility estimators and kernel realized volatility estimators. We introduce a new model for volatility analysis by combining low-frequency and high-frequency approaches. The proposed model is an Ito diffusion process where the instantaneous volatility depends on integrated volatility and squared log return. When the model is restricted to integer times, conditional volatility of the process adopts an analogous structure with the one seen in a standard GARCH model and includes one additional innovation: the integrated volatility. The proposed model is named as generalized unified GARCH-Ito model. Parameter estimation is built on the marriage of a quasi-likelihood function obtained based on conditional volatility structure from the proposed model and common realized volatility estimators obtained based on high-frequency financial data. To improve the performance of proposed estimators, we also provide the option of incorporating option data by adopting a joint quasi-likelihood function. We study the asymptotic behaviors of proposed estimators and conduct a simulation study that confirms proposed estimators have good finite sample statistical performance. An empirical study has been carried out to demonstrate the ease of implementation of the proposed model in daily volatility estimation.

Download or read book Multivariate Volatility Modeling and Forecasting with Stable GARCH and Wishart Autoregressive Models written by Matteo Bonato and published by . This book was released on 2009 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Volatility Estimation with Financial Data written by and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modeling and estimating volatility plays a crucial role in financial practice. Devoted efforts are made to investigate this topic using both low-frequency and high-frequency financial data. Traditionally, volatility modeling and analysis are based on either historical price data or option data. Finance theory shows that option prices heavily depend on the underlying stocks' prices, and thus the two kinds of data are related. This thesis explores the approach that combines both stock price data and option data to perform the statistical analysis of volatility. We investigate the Black-Scholes model and an exponential GARCH model and derive the relationship among the Fisher information for volatility estimation based on stock price data alone or option data alone as well as joint volatility estimation for combining stock price data and option data. Under the Block-Scholes model, asymptotic theory for the joint estimation is established, and a simulation study was conducted to check finite sample performances of the proposed joint estimator. Being more accessible than ever, high-frequency data have provided researchers and practitioners with incredible tools to investigate assets pricing and market dynamics. Non-synchronous observations, microstructure noise, and complex pricing models are challenges coming along with high-frequency data. Moreover, large volatility matrix estimation is involved in many finance practices and encounters "curse of dimensionality". Although it is widely used in large covariance estimation, imposing sparsity assumption on the entire volatility matrix is not reasonable in financial practice. In fact, due to the existence of common factors, assets are widely correlated with each other and their volatility matrix is not sparse. In this thesis, we focus on incorporating the factor influence in asset price modeling and volatility matrix estimation. We propose to model asset price using a factor-based diffusion process. The idea is that assets' prices are governed by a common factor, and that assets with similar characteristics share the same association with the factor. Under the proposed factor-based model, we developed an estimation scheme called "Blocking and Regularizing", which deals with all of the four changeless. The asymptotic properties of the proposed estimator are studied, while its finite sample performance is tested via extensive numerical studies to support theoretical results

Download or read book On Moment Non Explosions for Wishart Based Stochastic Volatility Models written by José Da Fonseca and published by . This book was released on 2018 with total page 15 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper provides a result on moment non-explosions for a stock following a Wishart multidimensional stochastic volatility dynamic or a Wishart affine stochastic correlation dynamic when the parameter values satisfy certain constraints. By reformulating the stock dynamic in terms of the volatility path along with standard results on matrix Lyapunov and Riccati equations, a non-explosion result of the moment of order greater than one can be obtained. It extends to these frameworks a property well known for the Heston model.

Download or read book The Volatility Process written by Alireza Javaheri and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Parameter estimation for a stochastic volatility model with coupled additive and multiplicative noise written by Ibukun O.O. Amusan and published by . This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Topics in Nonparametric Statistics written by Michael G. Akritas and published by Springer. This book was released on 2014-12-02 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is composed of peer-reviewed papers that have developed from the First Conference of the International Society for Non Parametric Statistics (ISNPS). This inaugural conference took place in Chalkidiki, Greece, June 15-19, 2012. It was organized with the co-sponsorship of the IMS, the ISI and other organizations. M.G. Akritas, S.N. Lahiri and D.N. Politis are the first executive committee members of ISNPS and the editors of this volume. ISNPS has a distinguished Advisory Committee that includes Professors R.Beran, P.Bickel, R. Carroll, D. Cook, P. Hall, R. Johnson, B. Lindsay, E. Parzen, P. Robinson, M. Rosenblatt, G. Roussas, T. SubbaRao and G. Wahba. The Charting Committee of ISNPS consists of more than 50 prominent researchers from all over the world. The chapters in this volume bring forth recent advances and trends in several areas of nonparametric statistics. In this way, the volume facilitates the exchange of research ideas, promotes collaboration among researchers from all over the world and contributes to the further development of the field. The conference program included over 250 talks, including special invited talks, plenary talks and contributed talks on all areas of nonparametric statistics. Out of these talks, some of the most pertinent ones have been refereed and developed into chapters that share both research and developments in the field.

Download or read book Advanced Multivariate Statistics with Matrices written by Tõnu Kollo and published by Springer Science & Business Media. This book was released on 2006-03-30 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents important tools and techniques for treating problems in m- ern multivariate statistics in a systematic way. The ambition is to indicate new directions as well as to present the classical part of multivariate statistical analysis in this framework. The book has been written for graduate students and statis- cians who are not afraid of matrix formalism. The goal is to provide them with a powerful toolkit for their research and to give necessary background and deeper knowledge for further studies in di?erent areas of multivariate statistics. It can also be useful for researchers in applied mathematics and for people working on data analysis and data mining who can ?nd useful methods and ideas for solving their problems. Ithasbeendesignedasatextbookforatwosemestergraduatecourseonmultiva- ate statistics. Such a course has been held at the Swedish Agricultural University in 2001/02. On the other hand, it can be used as material for series of shorter courses. In fact, Chapters 1 and 2 have been used for a graduate course ”Matrices in Statistics” at University of Tartu for the last few years, and Chapters 2 and 3 formed the material for the graduate course ”Multivariate Asymptotic Statistics” in spring 2002. An advanced course ”Multivariate Linear Models” may be based on Chapter 4. A lot of literature is available on multivariate statistical analysis written for di?- ent purposes and for people with di?erent interests, background and knowledge.