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Modeling Stock Return Volatility A Comparative Approach
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Book Synopsis Modeling Stock Return Volatility, a Comparative Approach by : Robert Krimetz
Download or read book Modeling Stock Return Volatility, a Comparative Approach written by Robert Krimetz and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The application of machine learning and probabilistic programming methods on stock return prediction has grown in tandem with the availability of high frequency stock data. With well recorded heteroskedasticity in historical stock returns, modeling attempts have evolved from making general assumptions about the underlying data generating distribution to predicting changes in the underlying distribution of returns. The increase in popularity of 'tradable volatility' through derivative contacts and VIX futures over the past three decades has motivated research efforts to model the variance of daily returns. Along this line of research, three schools of thought have emerged to model return volatility; Time Series Models, Stochastic Models, and Bayesian Models. Given that the preliminary assumptions underlying these models differ, the nature of their results and the varying metrics used to calculate their respective accuracy makes it difficult to directly compare them. Accordingly, the currently available pool of research has diverged along these three separate paths making it unclear the advantages of each. Notably, Bayesian models have largely been neglected in the current pool of research due to their computational intensity. In this paper I derive ten time series and Bayesian models then provide a comprehensive comparative study of the results on real stock data. I found that Bayesian models with intractable posterior distributions significantly outperform time series models at predicting directional change in future volatility, while the GARCH and FIGARCH time series models generate the most accurate point predictions for future volatility. I hope the results outlined in this paper better contextualize different volatility predictions and motivate the creation of more accurate tradeable volatility models.
Book Synopsis Modelling and forecasting stock return volatility and the term structure of interest rates by : Michiel de Pooter
Download or read book Modelling and forecasting stock return volatility and the term structure of interest rates written by Michiel de Pooter and published by Rozenberg Publishers. This book was released on 2007 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation consists of a collection of studies on two areas in quantitative finance: asset return volatility and the term structure of interest rates. The first part of this dissertation offers contributions to the literature on how to test for sudden changes in unconditional volatility, on modelling realized volatility and on the choice of optimal sampling frequencies for intraday returns. The emphasis in the second part of this dissertation is on the term structure of interest rates.
Book Synopsis A Practical Guide to Forecasting Financial Market Volatility by : Ser-Huang Poon
Download or read book A Practical Guide to Forecasting Financial Market Volatility written by Ser-Huang Poon and published by John Wiley & Sons. This book was released on 2005-08-19 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Financial market volatility forecasting is one of today's most important areas of expertise for professionals and academics in investment, option pricing, and financial market regulation. While many books address financial market modelling, no single book is devoted primarily to the exploration of volatility forecasting and the practical use of forecasting models. A Practical Guide to Forecasting Financial Market Volatility provides practical guidance on this vital topic through an in-depth examination of a range of popular forecasting models. Details are provided on proven techniques for building volatility models, with guide-lines for actually using them in forecasting applications.
Book Synopsis Stock Market Volatility by : Greg N. Gregoriou
Download or read book Stock Market Volatility written by Greg N. Gregoriou and published by CRC Press. This book was released on 2009-04-08 with total page 654 pages. Available in PDF, EPUB and Kindle. Book excerpt: Up-to-Date Research Sheds New Light on This Area Taking into account the ongoing worldwide financial crisis, Stock Market Volatility provides insight to better understand volatility in various stock markets. This timely volume is one of the first to draw on a range of international authorities who offer their expertise on market volatility in devel
Book Synopsis Modeling and Forecasting Stock Return Volatility by : Pia Grammig
Download or read book Modeling and Forecasting Stock Return Volatility written by Pia Grammig and published by . This book was released on 2013 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Modeling Stochastic Volatility with Application to Stock Returns by : Mr.Noureddine Krichene
Download or read book Modeling Stochastic Volatility with Application to Stock Returns written by Mr.Noureddine Krichene and published by International Monetary Fund. This book was released on 2003-06-01 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Handbook of Financial Econometrics and Statistics by : Cheng-Few Lee
Download or read book Handbook of Financial Econometrics and Statistics written by Cheng-Few Lee and published by Springer. This book was released on 2014-09-28 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Financial Econometrics and Statistics provides, in four volumes and over 100 chapters, a comprehensive overview of the primary methodologies in econometrics and statistics as applied to financial research. Including overviews of key concepts by the editors and in-depth contributions from leading scholars around the world, the Handbook is the definitive resource for both classic and cutting-edge theories, policies, and analytical techniques in the field. Volume 1 (Parts I and II) covers all of the essential theoretical and empirical approaches. Volumes 2, 3, and 4 feature contributed entries that showcase the application of financial econometrics and statistics to such topics as asset pricing, investment and portfolio research, option pricing, mutual funds, and financial accounting research. Throughout, the Handbook offers illustrative case examples and applications, worked equations, and extensive references, and includes both subject and author indices.
Book Synopsis Modeling and Forecasting Daily Stock Return Volatility with Intra-day Price Fluctuation Information by : Yansong Lu
Download or read book Modeling and Forecasting Daily Stock Return Volatility with Intra-day Price Fluctuation Information written by Yansong Lu and published by . This book was released on 2005 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Forecasting Volatility in the Financial Markets by : Stephen Satchell
Download or read book Forecasting Volatility in the Financial Markets written by Stephen Satchell and published by Elsevier. This book was released on 2011-02-24 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting Volatility in the Financial Markets, Third Edition assumes that the reader has a firm grounding in the key principles and methods of understanding volatility measurement and builds on that knowledge to detail cutting-edge modelling and forecasting techniques. It provides a survey of ways to measure risk and define the different models of volatility and return. Editors John Knight and Stephen Satchell have brought together an impressive array of contributors who present research from their area of specialization related to volatility forecasting. Readers with an understanding of volatility measures and risk management strategies will benefit from this collection of up-to-date chapters on the latest techniques in forecasting volatility. Chapters new to this third edition:* What good is a volatility model? Engle and Patton* Applications for portfolio variety Dan diBartolomeo* A comparison of the properties of realized variance for the FTSE 100 and FTSE 250 equity indices Rob Cornish* Volatility modeling and forecasting in finance Xiao and Aydemir* An investigation of the relative performance of GARCH models versus simple rules in forecasting volatility Thomas A. Silvey Leading thinkers present newest research on volatility forecasting International authors cover a broad array of subjects related to volatility forecasting Assumes basic knowledge of volatility, financial mathematics, and modelling
Book Synopsis Handbook of Volatility Models and Their Applications by : Luc Bauwens
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.
Book Synopsis Volatility Prediction by : Harry M. Kat
Download or read book Volatility Prediction written by Harry M. Kat and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Future volatility is a key input for pricing and hedging derivatives and for quantitative investment strategies in general. There are many different approaches. This article investigates whether random walk, GARCH (1,1), EGARCH (1,1) and stochastic volatility models of return volatility behavior differ in their ability to predict the volatility of stock index and currency returns over horizons ranging from 2 to 100 trading days. We use close-to-close return data for 7 indices and 5 currencies over the period 1980-1992. The results show that the forecast performance of the different models depends on the specific asset class in question. For stock indices the best volatility predictions are generated by the stochastic volatility model. For currencies on the other hand, the best forecasts come from the GARCH (1,1) model.
Book Synopsis Stock Market Risk and Return by : Robert Whitelaw
Download or read book Stock Market Risk and Return written by Robert Whitelaw and published by . This book was released on 2008 with total page 45 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent empirical evidence suggests that expected stock returns are weakly, or even negatively, related to the volatility of stock returns at the market level, and that this relation varies substantially over time. This evidence contradicts the apparently reliable intuition that risk and return are positively related and that stock market volatility is a good proxy for risk. This paper investigates the relation between volatility and expected returns in a general equilibrium, exchange economy. A relatively simple model, estimated using aggregate consumption data, is able to duplicate the salient features of the observed expected return/volatility relation. The key features of the model are the existence of two regimes with different consumption growth processes and time-varying correlations between stock returns and the marginal rate of substitution; thus inducing variability in the short-run relation between expected returns and volatility and a weakening of the long-run relation. These results highlight the perils of relying on intuition from static models. They also have important implications for the empirical modeling of returns.
Book Synopsis Stock Return Volatility: A Comparative Study of India and China by : Pankaj Chaudhary
Download or read book Stock Return Volatility: A Comparative Study of India and China written by Pankaj Chaudhary and published by . This book was released on 2016-09-03 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Empirical Studies on Volatility in International Stock Markets by : Eugenie M.J.H. Hol
Download or read book Empirical Studies on Volatility in International Stock Markets written by Eugenie M.J.H. Hol and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: Empirical Studies on Volatility in International Stock Markets describes the existing techniques for the measurement and estimation of volatility in international stock markets with emphasis on the SV model and its empirical application. Eugenie Hol develops various extensions of the SV model, which allow for additional variables in both the mean and the variance equation. In addition, the forecasting performance of SV models is compared not only to that of the well-established GARCH model but also to implied volatility and so-called realised volatility models which are based on intraday volatility measures. The intended readers are financial professionals who seek to obtain more accurate volatility forecasts and wish to gain insight about state-of-the-art volatility modelling techniques and their empirical value, and academic researchers and students who are interested in financial market volatility and want to obtain an updated overview of the various methods available in this area.
Book Synopsis A Permanent and Transitory Component Model of Stock Return Volatility by : Robert F. Engle
Download or read book A Permanent and Transitory Component Model of Stock Return Volatility written by Robert F. Engle and published by . This book was released on 1992 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis High-Low Range in GARCH Models of Stock Return Volatility by : Peter Molnár
Download or read book High-Low Range in GARCH Models of Stock Return Volatility written by Peter Molnár and published by . This book was released on 2016 with total page 29 pages. Available in PDF, EPUB and Kindle. Book excerpt: We suggest a simple and general way to improve the GARCH volatility models using the intraday range between the highest and the lowest price to proxy volatility. We illustrate the method by modifying a GARCH(1,1) model to a Range-GARCH(1,1) model. Our empirical analysis conducted on stocks, stock indices and simulated data shows that the Range-GARCH(1,1) model performs significantly better than the standard GARCH(1,1) model both in terms of in-sample fit and out-of-sample forecasting ability.
Book Synopsis Stock Market Risk and Return by : Robert F. Whitelaw
Download or read book Stock Market Risk and Return written by Robert F. Whitelaw and published by . This book was released on 1997 with total page 61 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent empirical evidence suggests that expected stock returns are weakly, or even negatively, related to the volatility of stock returns at the market level, and that this relation varies substantially over time. This evidence contradicts the apparently reliable intuition that risk and return axe positively related and that stock market volatility is a good proxy for risk. This paper investigates the relation between volatility and expected returns in a general equilibrium, exchange economy. A relatively simple model, estimated using aggregate consumption data, is able to duplicate the salient features of the observed expected return/volatility relation. The key features of the model are the existence of two regimes with different consumption growth processes and time-varying transition probabilities between regimes. This structure generates time-varying correlations between stock returns and the marginal rate of substitution; thus inducing variability in the short-run relation between expected returns and volatility and a weakening of the long-run relation. These results highlight the perils of relying on intuition from static models. They also have important implications for the empirical modeling of returns.
