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Essays On Multivariate Stochastic Volatility Models
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Book Synopsis Essays on Multivariate Stochastic Volatility Models by : Sebastian Trojan
Download or read book Essays on Multivariate Stochastic Volatility Models written by Sebastian Trojan and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first essay describes a very general stochastic volatility (SV) model specification with leverage, heavy tails, skew and switching regimes, using realized volatility (RV) as an auxiliary time series to improve inference on latent volatility. The information content of the range and of implied volatility using the VIX index is also analyzed. Database is the S & P 500 index. Asymmetry in the observation error is modeled by the generalized hyperbolic skew Student-t distribution, whose heavy and light tail enable substantial skewness. Resulting number of regimes and dynamics differ dependent on the auxiliary volatility proxy and are investigated in-sample for the financial crash period 2008/09 in more detail. An out-of-sample study comparing predictive ability of various model variants for a calm and a volatile period yields insights about the gains on forecasting performance from different volatility proxies. Results indicate that including RV or the VIX pays off mostly in more volatile market conditions, whereas in calmer environments SV specifications using no auxiliary series outperform. The range as volatility proxy provides a superior in-sample fit, but its predictive performance is found to be weak. The second essay presents a high frequency stochastic volatility model. Price duration and associated absolute price change in event time are modeled contemporaneously to fully capture volatility on the tick level, combining the SV and stochastic conditional duration (SCD) model. Estimation is with IBM stock intraday data 2001/10 (decimalization completed), taking a minimum midprice threshold of a half tick. Persistent information flow is extracted, featuring a positively correlated innovation term and negative cross effects in the AR(1) persistence matrix. Additionally, regime switching in both duration and absolute price change is introduced to increase nonlinear capabilities of the model. Thereby, a separate price jump.
Book Synopsis Essays on Multivariate Stochastic Volatility Models Using Wishart Processes by : Yu-Cheng Ku
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:
Book Synopsis Essays on Stochastic Volatility Models with Jump Clustering by : Jian Chen
Download or read book Essays on Stochastic Volatility Models with Jump Clustering written by Jian Chen and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Three Essays on Continuous-time Stochastic Volatility Models by : Lu Feng
Download or read book Three Essays on Continuous-time Stochastic Volatility Models written by Lu Feng and published by . This book was released on 1996 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Essays on Stochastic Volatility and Jumps by : Diep Ngoc Duong
Download or read book Essays on Stochastic Volatility and Jumps written by Diep Ngoc Duong and published by . This book was released on 2013 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation comprises three essays on financial economics and econometrics. The first essay outlines and expands upon further testing results from Bhardwaj, Corradi and Swanson (BCS: 2008) and Corradi and Swanson (2011). In particular, specification tests in the spirit of the conditional Kolmogorov test of Andrews (1997) that rely on block bootstrap resampling methods are first discussed. We then broaden our discussion from single process specification testing to multiple process model selection by discussing how to construct predictive densities and how to compare the accuracy of predictive densities derived from alternative (possibly misspecified) diffusion models. In particular, we generalize simulation steps outlined in Cai and Swanson (2011) to multifactor models where the number of latent variables is larger than three. In the second essay, we begin by discussing important developments in volatility modeling, with a focus on time varying and stochastic volatility as well as the "model free" estimation of volatility via the use of so-called realized volatility, and variants thereof called realized measures. In an empirical investigation, we use realized measures to investigate the role of "small" and large" jumps in the realized variation of stock price returns and show that jumps do matter in the relative contribution to the total variation of the process, when examining individual stock returns, as well as market indices. The third essay examines the predictive content of a variety of realized measures of jump power variations, all formed on the basis of power transformations of instantaneous returns. Our prediction involves estimating members of the linear and nonlinear extended Heterogeneous Autoregressive of the Realized Volatility (HAR-RV) class of models, using S & P 500 futures data as well as stocks in the Dow 30, for the period 1993-2009. Our findings suggest that past "large" jump power variations help less in the prediction of future realized volatility, than past "small" jump power variations. Our empirical findings also suggest that past realized signed jump power variations, which have not previously been examined in this literature, are strongly correlated with future volatility.
Book Synopsis Essays on Multivariate Volatility Models by : Trung Thanh Le
Download or read book Essays on Multivariate Volatility Models written by Trung Thanh Le and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis is an empirical study of how multivariate models can be applied to analyze the dependence between emerging financial markets and the US financial market. This thesis comprises of 3 complete papers which will use this data set as follows. The first paper is an comparative research on estimations and evaluations of 54 individual volatility models which belong to 10 different model classes being the Riskmetrics models, the Constant model (CCC), the Orthogonal-GARCH model (O-GARCH), the Dynamic Conditional Correlation model (DCC), the Asymmetric DCC model (ADCC), the Consistent DCC model (CDCC) and the Student's t-DCC model (TDCC). All of these models were estimated and then ranked by using both in-sample and out of sample performances. This research is to emphasize the importance of model selection in modeling the volatility of financial time series from emerging financial markets. The second paper uses the TDCC model which performed relatively well among the 54 volatility of financial time series from emerging financial markets. The second paper uses the TDCC model which performed relatively well among the 54 volatility models to analyze the volatilities and correlations of the emerging markets. Specifically, the pair-wise conditional correlations between each of the emerging markets and the US market, generated by the TDCC model, were used to perform empirical tests for the contagion of the 3 recent financial crises which are the Dotcom crisis in 2000, the Sub-prime in 2007-2008 and the Global financial crisis in 2008-2009. The use of the TDCC model which assumes a Student's t-distribution is greatly meaningful for the empirical tests for contagion as it deals with the fat-tailed behaviours of the financial data. The third paper is the application of multivariate copula, which provides a connection between the univariate distributions and the multivariate distribution inside the DCC model, to analyze the emerging data. The flexibility of the copula model that separates the multivariate distribution assumption from those univariate series allows us to have an efficient examination of the dependence structure of emerging financial markets. Following success of the copula models in recent studies, our research, which is the first to use the copula model to analyze high-dimensional data, confirms a significant improvement of the copula from the standard DCC model.
Book Synopsis Essays on Stochastic Volatility and Jumps by : Ke Chen (Economist)
Download or read book Essays on Stochastic Volatility and Jumps written by Ke Chen (Economist) and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis studies a few different finance topics on the application and modelling of jump and stochastic volatility process. First, the thesis proposed a non-parametric method to estimate the impact of jump dependence, which is important for portfolio selection problem. Comparing with existing literature, the new approach requires much less restricted assumption on the jump process, and estimation results suggest that the economical significance of jumps is largely mis-estimated in portfolio optimization problem. Second, this thesis investigates the time varying variance risk premium, in a framework of stochastic volatility with stochastic jump intensity. The proposed model considers jump intensity as an extra factor which is driven by realized jumps, in addition to a stochastic volatility model. The results provide strong evidence of multiple factors in the market and show how they drive the variance risk premium. Thirdly, the thesis uses the proposed models to price options on equity and VIX consistently. Based on calibrated model parameters, the thesis shows how to calculate the unconditional correlation of VIX future between different maturities.
Book Synopsis Volatility and Time Series Econometrics:Essays in Honor of Robert Engle by : Tim Bollerslev
Download or read book Volatility and Time Series Econometrics:Essays in Honor of Robert Engle written by Tim Bollerslev and published by OUP Oxford. This book was released on 2010-02-11 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Robert Engle received the Nobel Prize for Economics in 2003 for his work in time series econometrics. This book contains 16 original research contributions by some the leading academic researchers in the fields of time series econometrics, forecasting, volatility modelling, financial econometrics and urban economics, along with historical perspectives related to field of time series econometrics more generally.Engle's Nobel Prize citation focuses on his path-breaking work on autoregressive conditional heteroskedasticity (ARCH) and the profound effect that this work has had on the field of financial econometrics. Several of the chapters focus on conditional heteroskedasticity, and develop the ideas of Engle's Nobel Prize winning work. Engle's work has had its most profound effect on the modelling of financial variables and several of the chapters use newly developed time series methods to study thebehavior of financial variables. Each of the 16 chapters may be read in isolation, but they all importantly build on and relate to the seminal work by Nobel Laureate Robert F. Engle.
Book Synopsis Essays on Stochastic Volatility and Random-field Models in Finance by :
Download or read book Essays on Stochastic Volatility and Random-field Models in Finance written by and published by . This book was released on 2006 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Essays on stochastic volatility and random-fiels models in finance by : Helen Tsoulouvi
Download or read book Essays on stochastic volatility and random-fiels models in finance written by Helen Tsoulouvi and published by . This book was released on 2006 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Essays on Stochastic Volatility by : Hyung-Jin Chung
Download or read book Essays on Stochastic Volatility written by Hyung-Jin Chung and published by . This book was released on 1997 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Essays on Multivariate Volatility and Dependence Models for Financial Time Series by : Diaa Noureldin
Download or read book Essays on Multivariate Volatility and Dependence Models for Financial Time Series written by Diaa Noureldin and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Two Essays on Multivariate Stochastic Processes and Applications to Credit Risk Modeling by : Luca Vidozzi
Download or read book Two Essays on Multivariate Stochastic Processes and Applications to Credit Risk Modeling written by Luca Vidozzi and published by . This book was released on 2009 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Essays in Honor of Cheng Hsiao by : Dek Terrell
Download or read book Essays in Honor of Cheng Hsiao written by Dek Terrell and published by Emerald Group Publishing. This book was released on 2020-04-15 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: Including contributions spanning a variety of theoretical and applied topics in econometrics, this volume of Advances in Econometrics is published in honour of Cheng Hsiao.
Book Synopsis Three Essays on Volatility Measurement and Modeling with Price Limits by : Rui Gao
Download or read book Three Essays on Volatility Measurement and Modeling with Price Limits written by Rui Gao and published by . This book was released on 2014 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation studies volatility measurement and modeling issues when asset prices are subject to price limits based on Bayesian approaches. Two types of estimators are developed to consistently estimate integrated volatility in the presence of price limits. One is a realized volatility type estimator, but using both realized asset prices and simulated asset prices. The other is a discrete sample analogue of integrated volatility using posterior samples of the latent volatility states. These two types of estimators are first constructed based on the simple log-stochastic volatility model in Chapter 2. The simple log-stochastic volatility framework is extended in Chapter 3 to incorporate correlated innovations and further extended in Chapter 4 to accommodate jumps and fat-tailed innovations. For each framework, a MCMC algorithm is designed to simulate the unobserved asset prices, model parameters and latent states. Performances of both type estimators are also examined using simulations under each framework. Applications to Chinese stock markets are also provided.
Book Synopsis Analysis of High Dimensional Multivariate Stochastic Volatility Models by : Siddhartha Chib
Download or read book Analysis of High Dimensional Multivariate Stochastic Volatility Models written by Siddhartha Chib and published by . This book was released on 2005 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper is concerned with the fitting and comparison of high dimensional multivariate time series models with time varying correlations. The models considered here combine features of the classical factor model with those of the univariate stochastic volatility model. Specifically, a set of unobserved time-dependent factors, along with an associated loading matrix, are used to model the contemporaneous correlation while, conditioned on the factors, the noise in each factor and each series is assumed to follow independent three-parameter univariate stochastic volatility processes. A complete analysis of these models, and its special cases, is developed that encompasses estimation, filtering and model choice. The centerpieces of our estimation algorithm (which relies on MCMC methods) is (1) a reduced blocking scheme for sampling the free elements of the loading matrix and the factors and (2) a special method for sampling the parameters of the univariate SV process. The sampling of the loading matrix (containing typically many hundreds of parameters) is done via a highly tuned Metropolis-Hastings step. The resulting algorithm is completely scalable in terms of series and factors and very simulation-efficient. We also provide methods for estimating the log-likelihood function and the filtered values of the time-varying volatilities and correlations. We pay special attention to the problem of comparing one version of the model with another and for determining the number of factors. For this purpose we use MCMC methods to find the marginal likelihood and associated Bayes factors of each fitted model. In sum, these procedures lead to the first unified and practical likelihood based analysis of truly high dimensional models of stochastic volatility. We apply our methods in detail to two datasets. The first is the return vector on 20 exchange rates against the US Dollar. The second is the return vector on 40 common stocks quoted on the New York Stock Exchange.
Book Synopsis Essays on Volatility Models Using EMM Estimation by : Ying Gu
Download or read book Essays on Volatility Models Using EMM Estimation written by Ying Gu and published by . This book was released on 2006 with total page 155 pages. Available in PDF, EPUB and Kindle. Book excerpt:
