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

Download or read book Forecasting Daily Stock Volatility written by Ana-Maria Fuertes and published by . This book was released on 2013 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt: Several recent studies advocate the use of nonparametric estimators of daily price variability that exploit intraday information. This paper compares four such estimators, realised volatility, realised range, realised power variation and realised bipower variation, by examining their in-sample distributional properties and out-of-sample forecast ranking when the object of interest is the conventional conditional variance. The analysis is based on a 7-year sample of transaction prices for 14 NYSE stocks. The forecast race is conducted in a GARCH framework and relies on several loss functions. The realized range fares relatively well in the in-sample fit analysis, for instance, regarding the extent to which it brings normality in returns. However, overall the realised power variation provides the most accurate 1-day-ahead forecasts. Forecast combination of all four intraday measures produces the smallest forecast errors in about half of the sampled stocks. A market conditions analysis reveals that the additional use of intraday data on day t-1 to forecast volatility on day t is most advantageous when day t is a low volume or an up-market day. The results have implications for value-at-risk analysis.

Download or read book Forecasting Stock Volatility written by Xingyi Li and published by . This book was released on 2018 with total page 33 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is evidence that volatility forecasting models that use intraday data provide better forecast accuracy as compared with that delivered by the models that use daily data. Exactly how much better is still unknown. The present paper fills this gap in the literature and extends previous studies on forecasting stock market volatility in several important directions. First, we employ an extensive set of intraday data on 31 individual stocks over a sample period of 19 years. Second, we use forecast horizons ranging from 1 day to 6 months. Third, we evaluate the precision of volatility forecast provided by various competing models. Fourth, we conduct several robustness checks to assess the sensitivity of our results to various alternative choices. The major finding of our empirical study is that the gains from using intraday data are rather significant and persist over longer forecast horizons. Depending on the forecast horizon, the improvement in forecast precision varies from 30 to 50 percent. We demonstrate that our main results on the forecast accuracy gains are robust to the choice of intraday data frequency and the choice of measure of realized daily volatility.

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.

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:

Download or read book Forecasting Volatility in the Financial Markets written by John L. Knight and published by Butterworth-Heinemann. This book was released on 2002 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text 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 modeling and forecasting techniques. It then uses a technical survey to explain the different ways to measure risk and define the different models of volatility and return.

Download or read book Empirical Modeling of Exchange Rate Dynamics written by Francis X. Diebold and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 153 pages. Available in PDF, EPUB and Kindle. Book excerpt: Structural exchange rate modeling has proven extremely difficult during the recent post-1973 float. The disappointment climaxed with the papers of Meese and Rogoff (1983a, 1983b), who showed that a "naive" random walk model distinctly dominated received theoretical models in terms of predictive performance for the major dollar spot rates. One purpose of this monograph is to seek the reasons for this failure by exploring the temporal behavior of seven major dollar exchange rates using nonstructural time-series methods. The Meese-Rogoff finding does not mean that exchange rates evolve as random walks; rather it simply means that the random walk is a better stochastic approximation than any of their other candidate models. In this monograph, we use optimal model specification techniques, including formal unit root tests which allow for trend, and find that all of the exchange rates studied do in fact evolve as random walks or random walks with drift (to a very close approximation). This result is consistent with efficient asset markets, and provides an explanation for the Meese-Rogoff results. Far more subtle forces are at work, however, which lead to interesting econometric problems and have implications for the measurement of exchange rate volatility and moment structure. It is shown that all exchange rates display substantial conditional heteroskedasticity. A particularly reasonable parameterization of this conditional heteroskedasticity, which captures the observed clustering of prediction error variances, is developed in Chapter 2.

Download or read book Forecasting the Volatility of Stock Market and Oil Futures Market written by Dexiang Mei and published by Scientific Research Publishing, Inc. USA. This book was released on 2020-12-17 with total page 139 pages. Available in PDF, EPUB and Kindle. Book excerpt: The volatility has been one of the cores of the financial theory research, in addition to the stock markets and the futures market are an important part of modern financial markets. Forecast volatility of the stock market and oil futures market is an important part of the theory of financial markets research.

Download or read book Forecasting Daily Variability of the S P 100 Stock Index Using Historical Realised and Implied Volatility Measurements written by Siem Jan Koopman and published by . This book was released on 2004 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt:

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.

Download or read book Forecasting Volatility written by Stephen Figlewski and published by . This book was released on 1997 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Forecasting Daily Stock Volatility Using GARCH Model written by Sasikanta Tripathy and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Modeling and forecasting the volatility of stock markets has been one of the major topics in financial econometrics in recent years. Based on the daily closing value of 23 years data, an average of 5,605 observations, for both Sensex and Shanghai Stock Exchange Composite Index, this paper makes an attempt to fit appropriate GARCH model to estimate the conditional market volatility for both Bombay Stock Exchange (BSE) and Shanghai Stock Exchange (SSE), respectively. The empirical results demonstrate that there are significant ARCH effects in both the stock markets, and it is appropriate to use the GARCH model to estimate the process.

Download or read book Forecasting Stock Price Volatility An Indian Perspective written by K. Prabhakaran and published by LAP Lambert Academic Publishing. This book was released on 2014-12 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book threw light on the growth and development of the stock market and observed that the development of the stock market highly depends on volatility and forecasting is an important area of research in financial market. The book measured the extent of stock price volatility in select companies of Automobile, Infrastructure, Manufacturing, Pharmaceutical and Services and identified suitable model for forecasting the volatility of the share prices in India. It evaluated the comparative ability of different statistical and econometric forecasting models in the context of Indian Stocks. Three different competing models were considered for the book and for forecasting performance of different models two forecasting error statistics viz., Root Mean Square Error (RMSE) and the Mean Absolute Error (MAE) were used and the best model was suggested for each sector. The EGARCH model provides the most accurate forecast compared to other competing models in the book. The book also made a few observations which may help the investors to understand better about the stock market.

Download or read book The Nature of Statistical Learning Theory written by Vladimir Vapnik and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. It considers learning as a general problem of function estimation based on empirical data. Omitting proofs and technical details, the author concentrates on discussing the main results of learning theory and their connections to fundamental problems in statistics. This second edition contains three new chapters devoted to further development of the learning theory and SVM techniques. Written in a readable and concise style, the book is intended for statisticians, mathematicians, physicists, and computer scientists.

Download or read book Does Stock Market Volatility Forecast Returns written by and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "We use daily price indices obtained from the Morgan Stanley Capital International to construct realized volatility for 18 individual stock markets, including the US, and the world stock market. In contrast with the CAPM, we find that volatility by itself does not forecast excess returns in most countries; however, it becomes a significant predictor when combined with the US consumption-wealth ratio, which, as argued by recent authors, is a proxy for the liquidity premium. The latter result mainly reflects the fact that volatility in international stock markets co-moves closely with the US stock volatility: The former loses its predictive power if we also include the latter in the forecasting equation. Moreover, the out-of-sample forecast of the US or the world stock market returns appears to be a good proxy for conditional returns of international stock markets. Our results thus indicate that (1) volatility is one of important determinants of the equity premium and (2) international stock markets are integrated"--Federal Reserve Bank of St. Louis web site.

Download or read book Financial Risk Forecasting written by Jon Danielsson and published by John Wiley & Sons. This book was released on 2011-04-20 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: Financial Risk Forecasting is a complete introduction to practical quantitative risk management, with a focus on market risk. Derived from the authors teaching notes and years spent training practitioners in risk management techniques, it brings together the three key disciplines of finance, statistics and modeling (programming), to provide a thorough grounding in risk management techniques. Written by renowned risk expert Jon Danielsson, the book begins with an introduction to financial markets and market prices, volatility clusters, fat tails and nonlinear dependence. It then goes on to present volatility forecasting with both univatiate and multivatiate methods, discussing the various methods used by industry, with a special focus on the GARCH family of models. The evaluation of the quality of forecasts is discussed in detail. Next, the main concepts in risk and models to forecast risk are discussed, especially volatility, value-at-risk and expected shortfall. The focus is both on risk in basic assets such as stocks and foreign exchange, but also calculations of risk in bonds and options, with analytical methods such as delta-normal VaR and duration-normal VaR and Monte Carlo simulation. The book then moves on to the evaluation of risk models with methods like backtesting, followed by a discussion on stress testing. The book concludes by focussing on the forecasting of risk in very large and uncommon events with extreme value theory and considering the underlying assumptions behind almost every risk model in practical use – that risk is exogenous – and what happens when those assumptions are violated. Every method presented brings together theoretical discussion and derivation of key equations and a discussion of issues in practical implementation. Each method is implemented in both MATLAB and R, two of the most commonly used mathematical programming languages for risk forecasting with which the reader can implement the models illustrated in the book. The book includes four appendices. The first introduces basic concepts in statistics and financial time series referred to throughout the book. The second and third introduce R and MATLAB, providing a discussion of the basic implementation of the software packages. And the final looks at the concept of maximum likelihood, especially issues in implementation and testing. The book is accompanied by a website - www.financialriskforecasting.com – which features downloadable code as used in the book.

Download or read book Volatility and Correlation written by Riccardo Rebonato and published by John Wiley & Sons. This book was released on 2005-07-08 with total page 864 pages. Available in PDF, EPUB and Kindle. Book excerpt: In Volatility and Correlation 2nd edition: The Perfect Hedger and the Fox, Rebonato looks at derivatives pricing from the angle of volatility and correlation. With both practical and theoretical applications, this is a thorough update of the highly successful Volatility & Correlation – with over 80% new or fully reworked material and is a must have both for practitioners and for students. The new and updated material includes a critical examination of the ‘perfect-replication’ approach to derivatives pricing, with special attention given to exotic options; a thorough analysis of the role of quadratic variation in derivatives pricing and hedging; a discussion of the informational efficiency of markets in commonly-used calibration and hedging practices. Treatment of new models including Variance Gamma, displaced diffusion, stochastic volatility for interest-rate smiles and equity/FX options. The book is split into four parts. Part I deals with a Black world without smiles, sets out the author’s ‘philosophical’ approach and covers deterministic volatility. Part II looks at smiles in equity and FX worlds. It begins with a review of relevant empirical information about smiles, and provides coverage of local-stochastic-volatility, general-stochastic-volatility, jump-diffusion and Variance-Gamma processes. Part II concludes with an important chapter that discusses if and to what extent one can dispense with an explicit specification of a model, and can directly prescribe the dynamics of the smile surface. Part III focusses on interest rates when the volatility is deterministic. Part IV extends this setting in order to account for smiles in a financially motivated and computationally tractable manner. In this final part the author deals with CEV processes, with diffusive stochastic volatility and with Markov-chain processes. Praise for the First Edition: “In this book, Dr Rebonato brings his penetrating eye to bear on option pricing and hedging.... The book is a must-read for those who already know the basics of options and are looking for an edge in applying the more sophisticated approaches that have recently been developed.” —Professor Ian Cooper, London Business School “Volatility and correlation are at the very core of all option pricing and hedging. In this book, Riccardo Rebonato presents the subject in his characteristically elegant and simple fashion...A rare combination of intellectual insight and practical common sense.” —Anthony Neuberger, London Business School