Download or read book Disentangling Volatility from Jumps written by Yacine Ait-Sahalia and published by . This book was released on 2010 with total page 45 pages. Available in PDF, EPUB and Kindle. Book excerpt: Realistic models for financial asset prices used in portfolio choice, option pricing or risk management include both a continuous Brownian and a jump components. This paper studies our ability to distinguish one from the other. I find that, surprisingly, it is possible to perfectly disentangle Brownian noise from jumps. This is true even if, unlike the usual Poisson jumps, the jump process exhibits an infinite number of small jumps in any finite time interval, which ought to be harder to distinguish from Brownian noise, itself made up of many small moves.

Download or read book Disentangling Continuous Volatility from Jumps in Long run Risk return Relationships written by Éric Jacquier 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 Disentangling Volatility from Jumps written by Yacine Aït-Sahalia and published by . This book was released on 2003 with total page 43 pages. Available in PDF, EPUB and Kindle. Book excerpt: Realistic models for financial asset prices used in portfolio choice, option pricing or risk management include both a continuous Brownian and a jump components. This paper studies our ability to distinguish one from the other. I find that, surprisingly, it is possible to perfectly disentangle Brownian noise from jumps. This is true even if, unlike the usual Poisson jumps, the jump process exhibits an infinite number of small jumps in any finite time interval, which ought to be harder to distinguish from Brownian noise, itself made up of many small moves

Download or read book Disentangling Continuous Volatility from Jumps in Long run Risk return Relationships written by Éric Jacquier and published by . This book was released on 2013 with total page 47 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Impact of Jumps in Volatility and Returns written by Michael S. Johannes and published by . This book was released on 2011 with total page 47 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper examines a class of continuous-time models that incorporate jumps in returns and volatility, in addition to diffusive stochastic volatility. We develop a likelihood-based estimation strategy and provide estimates of model parameters, spot volatility, jump times and jump sizes using both Samp;P 500 and Nasdaq 100 index returns. Estimates of jumps times, jump sizes and volatility are particularly useful for disentangling the dynamic effects of these factors during periods of market stress, such as those in 1987, 1997 and 1998. Using both formal and informal diagnostics, we find strong evidence for jumps in volatility, even after accounting for jumps in returns. We use implied volatility curves computed from option prices to judge the economic differences between the models. Finally, we evaluate the impact of estimation risk on option prices and find that the uncertainty in estimating the parameters and the spot volatility has important, though very different, effects on option prices.

Download or read book Inside Volatility Arbitrage written by Alireza Javaheri and published by John Wiley & Sons. This book was released on 2011-08-24 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Today?s traders want to know when volatility is a sign that the sky is falling (and they should stay out of the market), and when it is a sign of a possible trading opportunity. Inside Volatility Arbitrage can help them do this. Author and financial expert Alireza Javaheri uses the classic approach to evaluating volatility -- time series and financial econometrics -- in a way that he believes is superior to methods presently used by market participants. He also suggests that there may be "skewness" trading opportunities that can be used to trade the markets more profitably. Filled with in-depth insight and expert advice, Inside Volatility Arbitrage will help traders discover when "skewness" may present valuable trading opportunities as well as why it can be so profitable.

Download or read book Inside Volatility Filtering written by Alireza Javaheri and published by John Wiley & Sons. This book was released on 2015-08-24 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: A new, more accurate take on the classical approach to volatility evaluation Inside Volatility Filtering presents a new approach to volatility estimation, using financial econometrics based on a more accurate estimation of the hidden state. Based on the idea of "filtering", this book lays out a two-step framework involving a Chapman-Kolmogorov prior distribution followed by Bayesian posterior distribution to develop a robust estimation based on all available information. This new second edition includes guidance toward basing estimations on historic option prices instead of stocks, as well as Wiener Chaos Expansions and other spectral approaches. The author's statistical trading strategy has been expanded with more in-depth discussion, and the companion website offers new topical insight, additional models, and extra charts that delve into the profitability of applied model calibration. You'll find a more precise approach to the classical time series and financial econometrics evaluation, with expert advice on turning data into profit. Financial markets do not always behave according to a normal bell curve. Skewness creates uncertainty and surprises, and tarnishes trading performance, but it's not going away. This book shows traders how to work with skewness: how to predict it, estimate its impact, and determine whether the data is presenting a warning to stay away or an opportunity for profit. Base volatility estimations on more accurate data Integrate past observation with Bayesian probability Exploit posterior distribution of the hidden state for optimal estimation Boost trade profitability by utilizing "skewness" opportunities Wall Street is constantly searching for volatility assessment methods that will make their models more accurate, but precise handling of skewness is the key to true accuracy. Inside Volatility Filtering shows you a better way to approach non-normal distributions for more accurate volatility estimation.

Download or read book Handbook of Financial Econometrics written by Yacine Ait-Sahalia and published by Elsevier. This book was released on 2009-10-19 with total page 809 pages. Available in PDF, EPUB and Kindle. Book excerpt: This collection of original articles—8 years in the making—shines a bright light on recent advances in financial econometrics. From a survey of mathematical and statistical tools for understanding nonlinear Markov processes to an exploration of the time-series evolution of the risk-return tradeoff for stock market investment, noted scholars Yacine Aït-Sahalia and Lars Peter Hansen benchmark the current state of knowledge while contributors build a framework for its growth. Whether in the presence of statistical uncertainty or the proven advantages and limitations of value at risk models, readers will discover that they can set few constraints on the value of this long-awaited volume. Presents a broad survey of current research—from local characterizations of the Markov process dynamics to financial market trading activity Contributors include Nobel Laureate Robert Engle and leading econometricians Offers a clarity of method and explanation unavailable in other financial econometrics collections

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 2012-04-17 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 Missing Data Methods written by David M. Drukker and published by Emerald Group Publishing. This book was released on 2011-11-30 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: Part of the "Advances in Econometrics" series, this title contains chapters covering topics such as: Missing-Data Imputation in Nonstationary Panel Data Models; Markov Switching Models in Empirical Finance; Bayesian Analysis of Multivariate Sample Selection Models Using Gaussian Copulas; and, Consistent Estimation and Orthogonality.

Download or read book Non Parametric Estimation of Intraday Spot Volatility written by Thibault Vatter and published by . This book was released on 2016 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: We provide a new framework for modeling trends and periodic patterns in high-frequency financial data. Seeking adaptivity to ever-changing market conditions, we enlarge the Fourier flexible form into a richer functional class: both our smooth trend and the seasonality are non-parametrically time-varying and evolve in real time. We provide the associated estimators and use simulations to show that they behave adequately in the presence of jumps and heteroskedastic and heavy-tailed noise. A study of exchange rate returns sampled from 2010 to 2013 suggests that failing to factor in the seasonality's dynamic properties may lead to misestimation of the intraday spot volatility.

Download or read book Exploiting high frequency data for volatility forecasting and portfolio selection kumulative Dissertation written by Yujia Hu and published by . This book was released on 2012 with total page 123 pages. Available in PDF, EPUB and Kindle. Book excerpt: An instant may matter for the course of an entire life. It is with this idea that the present research had its inception. High frequency financial data are becoming increasingly available and this has triggered research in financial econometrics where information at high frequency can be exploited for different purposes. The most prominent example of this is the estimation and forecast of financial volatility. The research, chapter by chapter is summarized below. Chapter 1 provides empirical evidence on univariate realized volatility forecasting in relation to asymmetries present in the dynamics of both return and volatility processes. It examines leverage and volatility feedback effects among continuous and jump components of the S&P500 price and volatility dynamics, using recently developed methodologies to detect jumps and to disentangle their size from the continuous return and the continuous volatility. The research finds that jumps in return can improve forecasts of volatility, while jumps in volatility improve volatility forecasts to a lesser extent. Moreover, disentangling jump and continuous variations into signed semivariances further improves the out-of-sample performance of volatility forecasting models, with negative jump semivariance being highly more informative than positive jump semivariance. A simple autoregressive model is proposed and this is able to capture many empirical stylized facts while still remaining parsimonious in terms of number of parameters to be estimated. Chapter 2 investigates the out-of-sample performance and the economic value of multivariate forecasting models for volatility of exchange rate returns. It finds that, when the realized covariance matrix approximates the true latent covariance, a model that uses high frequency information for the correlation is more appropriate compared to alternative models that uses only low-frequency data. However multivariate FX returns standardized by the.

Download or read book Explaining Credit Default Swap Spreads with Equity Volatility and Jump Risks of Individual Firms written by Yibin Zhang and published by . This book was released on 2005 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Applied And Industrial Mathematics In Italy Ii Selected Contributions From The 8th Simai Conference written by Vincenzo Cutello and published by World Scientific. This book was released on 2007-08-17 with total page 642 pages. Available in PDF, EPUB and Kindle. Book excerpt: Industrial mathematics is evolving into an important branch of mathematics. Mathematicians, in particular in Italy, are becoming increasingly aware of this new trend and are engaged in bridging the gap between highly specialized mathematical research and the emerging demand for innovation from industry. The contributions in this volume provide both R&D workers in industry with a general view of existing skills, and academics with state-of-the-art applications of mathematics to real-world problems, which may also be incorporated in advanced courses.

Download or read book Financial Macro and Micro Econometrics Using R written by and published by Elsevier. This book was released on 2020-01-25 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Financial, Macro and Micro Econometrics Using R, Volume 42, provides state-of-the-art information on important topics in econometrics, including multivariate GARCH, stochastic frontiers, fractional responses, specification testing and model selection, exogeneity testing, causal analysis and forecasting, GMM models, asset bubbles and crises, corporate investments, classification, forecasting, nonstandard problems, cointegration, financial market jumps and co-jumps, among other topics. Presents chapters authored by distinguished, honored researchers who have received awards from the Journal of Econometrics or the Econometric Society Includes descriptions and links to resources and free open source R Gives readers what they need to jumpstart their understanding on the state-of-the-art

Download or read book Exploiting High Frequency Data for Volatility Forecasting and Portfolio Selection written by Yujia Hu and published by . This book was released on 2012 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: An instant may matter for the course of an entire life. It is with this idea that the present research had its inception. High frequency financial data are becoming increasingly available and this has triggered research in financial econometrics where information at high frequency can be exploited for different purposes. The most prominent example of this is the estimation and forecast of financial volatility. The research, chapter by chapter is summarized below. Chapter 1 provides empirical evidence on univariate realized volatility forecasting in relation to asymmetries present in the dynamics of both return and volatility processes. It examines leverage and volatility feedback effects among continuous and jump components of the S & P500 price and volatility dynamics, using recently developed methodologies to detect jumps and to disentangle their size from the continuous return and the continuous volatility. The research finds that jumps in return can improve forecasts of volatility, while jumps in volatility improve volatility forecasts to a lesser extent. Moreover, disentangling jump and continuous variations into signed semivariances further improves the out-of-sample performance of volatility forecasting models, with negative jump semivariance being highly more informative than positive jump semivariance. A simple autoregressive model is proposed and this is able to capture many empirical stylized facts while still remaining parsimonious in terms of number of parameters to be estimated. Chapter 2 investigates the out-of-sample performance and the economic value of multivariate forecasting models for volatility of exchange rate returns. It finds that, when the realized covariance matrix approximates the true latent covariance, a model that uses high frequency information for the correlation is more appropriate compared to alternative models that uses only low-frequency data. However multivariate FX returns standardized by the.

Download or read book The Economics of Commodity Markets written by Julien Chevallier and published by John Wiley & Sons. This book was released on 2013-06-19 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: As commodity markets have continued their expansion an extensive and complex financial industry has developed to service them. This industry includes hundreds of participating firms, including asset managers, brokers, consultants, verification agencies and a myriad of other institutions. Universities and other training institutions have responded to this rapid expansion of commodity markets as well as their substantial future growth potential by launching specialized courses on the subject. The Economics of Commodity Markets attempts to bridge the gap between academics and working professionals by way of a textbook that is both theoretically informative and practical. Based in part on the authors’ teaching experience of commodity finance at the University Paris Dauphine, the book covers all important commodity markets topics and includes coverage of recent topics such as financial applications and intuitive economic reasoning. The book is composed of three parts that cover: commodity market dynamics, commodities and the business cycle, and commodities and fundamental value. The key original approach to the subject matter lies in a shift away from the descriptive to the econometric analysis of commodity markets. Information on market trends of commodities is presented in the first part, with a strong emphasis on the quantitative treatment of that information in the remaining two parts of the book. Readers are provided with a clear and succinct exposition of up-to-date financial economic and econometric methods as these apply to commodity markets. In addition a number of useful empirical applications are introduced and discussed. This book is a self-contained offering, discussing all key methods and insights without descending into superfluous technicalities. All explanations are structured in an accessible manner, permitting any reader with a basic understanding of mathematics and finance to work their way through all parts of the book without having to resort to external sources.