Download or read book Trade Versus Time Series Based Volatility Forecasts written by Martin Scheicher and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper compares the quality of commonly used predictors for the volatility of stock returns. The techniques studied are moving averages of squared returns, GARCH and stochastic volatility models, and the implied volatility. We use a variety of econometric criteria to assess the forecasting performance. Among the models we estimate, no clear winner emerges. The implied volatility is found to contain information, which is absent in time series, based forecasts. Based on our findings we suggest practical consequences for the purpose of derivatives valuation and risk management.
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 Volatility Forecasts Trading Volume and the Arch Versus Option Implied Volatility Trade Off written by Glen Donaldson and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We investigate empirically the role of trading volume (1) in predicting the relative informativeness of volatility forecasts produced by autoregressive conditional heteroskedasticity (ARCH) models versus the volatility forecasts derived from option prices, and (2) in improving volatility forecasts produced by ARCH and option models and combinations of models. Daily and monthly data are explored. We find that if trading volume was low during period t-1 relative to the recent past, ARCH is at least as important as options for forecasting future stock market volatility. Conversely, if volume was high during period t-1 relative to the recent past, option-implied volatility is much more important than ARCH for forecasting future volatility. Considering relative trading volume as a proxy for changes in the set of information available to investors, our findings reveal an important switching role for trading volume between a volatility forecast that reflects relatively stale information (the historical ARCH estimate) and the option-implied forward-looking estimate.
Download or read book Forecasting Volatility written by Louis H. Ederington and published by . This book was released on 2004 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt: The paper compares the forecasting ability of the most popular volatility forecasting models and develops an alternative. The comparison of existing models focuses on four issues: 1) the relative weighting of recent versus older observations, 2) the estimation criteria, 3) the trade-off in terms of out-of-sample forecasting error between simple and complex models, and 4) the emphasis placed on large shocks. Like previous studies, we find that financial markets have longer memories than reflected in GARCH(1,1) model estimates but find this has little impact on out-of-sample forecasting ability. While more complex models which allow a more flexible weighting pattern than the exponential model forecast better on an in-sample basis, due to the additional estimation error introduced by additional parameters, they forecast poorly out-of-sample. With the exception of GARCH models, we find that models based on absolute return deviations generally forecast volatility better than otherwise equivalent models based on squared return deviations. Among the most popular time series models, we find that GARCH(1,1) generally yields better forecasts than the historical standard deviation and exponentially weighted moving average models though between GARCH and EGARCH there is no clear favorite. However, in terms of forecast accuracy, all are dominated by a new, simple, non-linear least squares model, based on historical absolute return deviations, that we develop and test here.
Download or read book Essentials of Time Series for Financial Applications written by Massimo Guidolin and published by Academic Press. This book was released on 2018-05-29 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: Essentials of Time Series for Financial Applications serves as an agile reference for upper level students and practitioners who desire a formal, easy-to-follow introduction to the most important time series methods applied in financial applications (pricing, asset management, quant strategies, and risk management). Real-life data and examples developed with EViews illustrate the links between the formal apparatus and the applications. The examples either directly exploit the tools that EViews makes available or use programs that by employing EViews implement specific topics or techniques. The book balances a formal framework with as few proofs as possible against many examples that support its central ideas. Boxes are used throughout to remind readers of technical aspects and definitions and to present examples in a compact fashion, with full details (workout files) available in an on-line appendix. The more advanced chapters provide discussion sections that refer to more advanced textbooks or detailed proofs. - Provides practical, hands-on examples in time-series econometrics - Presents a more application-oriented, less technical book on financial econometrics - Offers rigorous coverage, including technical aspects and references for the proofs, despite being an introduction - Features examples worked out in EViews (9 or higher)
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
Download or read book Volatility Forecasting written by Torben Gustav Andersen and published by . This book was released on 2005 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: Volatility has been one of the most active and successful areas of research in time series econometrics and economic forecasting in recent decades. This chapter provides a selective survey of the most important theoretical developments and empirical insights to emerge from this burgeoning literature, with a distinct focus on forecasting applications. Volatility is inherently latent, and Section 1 begins with a brief intuitive account of various key volatility concepts. Section 2 then discusses a series of different economic situations in which volatility plays a crucial role, ranging from the use of volatility forecasts in portfolio allocation to density forecasting in risk management. Sections 3, 4 and 5 present a variety of alternative procedures for univariate volatility modeling and forecasting based on the GARCH, stochastic volatility and realized volatility paradigms, respectively. Section 6 extends the discussion to the multivariate problem of forecasting conditional covariances and correlations, and Section 7 discusses volatility forecast evaluation methods in both univariate and multivariate cases. Section 8 concludes briefly.
Download or read book Handbook of Economic Forecasting written by Graham Elliott and published by Elsevier. This book was released on 2013-08-23 with total page 667 pages. Available in PDF, EPUB and Kindle. Book excerpt: The highly prized ability to make financial plans with some certainty about the future comes from the core fields of economics. In recent years the availability of more data, analytical tools of greater precision, and ex post studies of business decisions have increased demand for information about economic forecasting. Volumes 2A and 2B, which follows Nobel laureate Clive Granger's Volume 1 (2006), concentrate on two major subjects. Volume 2A covers innovations in methodologies, specifically macroforecasting and forecasting financial variables. Volume 2B investigates commercial applications, with sections on forecasters' objectives and methodologies. Experts provide surveys of a large range of literature scattered across applied and theoretical statistics journals as well as econometrics and empirical economics journals. The Handbook of Economic Forecasting Volumes 2A and 2B provide a unique compilation of chapters giving a coherent overview of forecasting theory and applications in one place and with up-to-date accounts of all major conceptual issues. - Focuses on innovation in economic forecasting via industry applications - Presents coherent summaries of subjects in economic forecasting that stretch from methodologies to applications - Makes details about economic forecasting accessible to scholars in fields outside economics
Download or read book Predicting Financial Volatility written by Martin Martens and published by . This book was released on 2008 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent evidence suggests option implied volatility provides better forecasts of financial volatility than time-series models based on historical daily returns. In particular it is found that daily GARCH forecasts have no or little incremental information over that already contained in implied volatilities. In this study both the measurement and the forecasting of financial volatility is improved using high-frequency data and the latest proposed model for volatility, a long memory model. The results indicate that volatility forecasts based on historical intraday returns do provide good volatility forecasts that can compete with implied volatility and sometimes even outperform implied volatility.
Download or read book Forecasting Volatility written by Charbel Slaiby and published by . This book was released on 2016 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: Originality/value – the literature did not reach a conclusion concerning the superiority of one model of the other; moreover, you cannot find any study that jointly targeted the volatility f these three instruments in the life of traders, analysts, and risk managers. In addition, there isnt any paper that combines GARCH, EWMA, EGARCH, GJR-GARCH, and implied volatility together. EWMA was somehow neglected or forgotten in previous studies, but it proved to be essential in every study. Furthermore, the study highlights the steps that should be followed to estimate EGARPH and the other models on excel.
Download or read book Predicting Forex and Stock Market with Fractal Pattern written by Young Ho Seo and published by www.algotrading-investment.com. This book was released on 2020-04-09 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: About this book This book provides you the powerful and brand new knowledge on predicting financial market that we have discovered in several years of our own research and development work. This book will help you to turn your intuition into the scientific prediction method. In the course of recognizing the price patterns in the chart of Forex and Stock market, you should be realized that it was your intuition working at the background for you. The geometric prediction devised in this book will show you the scientific way to predict the financial market using your intuition. Many of us made a mistake of viewing the financial market with deterministic cycle. Even though we knew that market would not show us such a simple prediction pattern, we never stop using the concept of deterministic cycle to predict the financial market, for example, using Fourier transform, and other similar techniques. Why is that so? The reason is simple. It is because no one presented an effective way of predicting stochastic cycle. Stochastic cycle is the true face of the financial market because many variables in the market are suppressing the predictable cycle with fixed time interval. So how we predict the stochastic cycle present in the financial market? The key to answer is the Fractal Pattern and Fractal Wave. The geometric prediction on Fractal Wave solves the puzzles of the stochastic cycle modelling problem together. In another words, your intuition, more precisely your capability to recognize geometric shape, is more powerful than any other technical indicators available in the market. Hence, the geometric prediction, which comes from your intuition, would maximize your ability to trade in the financial market. In this book, Geometric prediction is described as the combined ability to recognize the geometric regularity and statistical regularity from the chart. We provide the examples of geometric regularity and statistical regularity. In addition, we will show you how these regularities are related to your intuition. The chart patterns covered in this book include support, resistance, Fibonacci Price pattern, Harmonic Pattern, Falling Wedge pattern, Rising Wedge pattern, and Gann Angles with probability. We use these chart patterns to detect geometric regularity. Then, we use the turning point probability as the mean of detecting statistical regularity. In our trading, we combine both to improve the trading performance.
Download or read book Empirical Evidence on Forecasting Exchange Rate Volatility written by Natacha Nehme and published by . This book was released on 2017 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research limitations -- A limitation that could have biased the results is that the return of EUR/USD, JPY/USD, GBP/USD and CHF/USD exchange rates was calculated based on the daily exchange rate. In fact, using intra-day volatility measurement could have led to better results in forecasting exchange rate volatility. Moreover, other models could have been used that exhibit different characteristics than GARCH (1, 1), EGARCH, GJR GARCH and EWMA models such as the Autoregressive Integrated Moving Average (ARIMA), the Integrated in Variance (IGARCH) and the Fractionally Integrated Generalized Autoregressive Conditional Heteroskedasticity (FIGARCH). In addition, other software could have replace EViews, such as Matlab. Practical implications -- The empirical results of this research have direct and fundamental implication on international investors and firms to better hedge currency risk. The findings will also assist policy makers in the international capital budgeting by understanding the pattern of exchange rates. Originality/value -- This study is an endeavor to fill the gap of previous literature by implementing the symmetric and asymmetric models to forecast the exchange rate volatility. In addition, it compares the performance of implied volatility to financial models, a topic that was ignored in previous researches. Moreover, no recent papers tackled the in-sample and out-of-sample EUR/USD, JPY/USD, GBP/USD and CHF/USD exchange rate volatility under a recent sample period and using this basket of models: GARCH (1, 1), EGARCH, GJR GARCH and EWMA. Therefore, the findings of this research will be used as a benchmark for investors, hedges, economists and financial institutions to accurately predict exchange rate volatility.
Download or read book Forecasting and Timing Markets a Quantitative Approach written by Henry Liu and published by . This book was released on 2021-04-15 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt: Financial markets are essentially time-series data driven events consisting of valleys, peaks, and in-betweens of ups and downs. For more than a century, many pioneers had attempted to come up with various theoretical models to facilitate forecasting and timing market moves. For example, as early as in 1902, or 119 years ago, S. A. Nelson, a friend of Charles H. Dow, attempted to explain Dow's methods in his book titled The A B C of Stock Speculation, which became later known as "the Dow Theory." 20 years later in 1922, William Peter Hamilton carried on and wrote the book The Stock Market Barometer, which explained the Dow Theory in more detail. More recently in the last few decades, the advent of advanced computing technologies helped create numerous technical indicators, such as Relative Strength Index (RSI) by J. Welles Wilder (1978), Moving Average Convergence Divergence (MACD) by Gerald Appel (2005), Stochastic Oscillator (SO) by George Lane (2007), and Bollinger Bands (BB) by John Bollinger (2002), etc. Those powerful theories and indicators have been heavily studied and well-known in the financial circle. However, they are empirical and lack quantitative verifications out of solid backtest results. This book helps fill these vacancies. This text attempts to help explore how one can forecast and time markets more quantitatively. For this purpose, the author developed a model-based system, named AlphaCovaria, to help demonstrate how to use various simplest, readily available technical indicators to forecast and time markets approximately while eliminating subjective speculations at the same time. Centered on various math models, the author's AlphaCovaria system has three main components: an AlphaCurve program for charting, a BTDriver program for running all backtests, and an AlphaCovaria driver for generating buy/sell signals based on symbol profiles learned through backtests. This kind of formula-driven approach is more promising for building more high-performance strategies. The text is made concise and precise of about 100 pages only, as a working method does not need to be wordy. Math models, data and charts can help explain more effectively and convincingly. Also, inspired by those classical models, the author came up with a new indicator named simple cascading indicator (sci), which beat all those classical models in most cases, based on the backtest results with 29 carefully selected symbols and past 15 years' price data. This 2nd edition of the book also shared my live trading experience using real money in my Fidelity and eTrade accounts with my AlphaCovaria system. Such data can be found nowhere else.
Download or read book Volatility Forecasts Trading Volume and the Arch vs Option Implied Volatility Tradeoff written by R. Glen Donaldson and published by . This book was released on 2014 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt: Market expectations of future return volatility play a crucial role in finance; so too does our understanding of the process by which information is incorporated in security prices through the trading process. This paper seeks to learn something about both of these issues by investigating empirically the role of trading volume (a) in predicting the relative informativeness of volatility forecasts produced by ARCH models versus the volatility forecasts derived from option prices, and (b) in improving volatility forecasts produced by ARCH and option models and combinations of models. We find that if trading volume was low during period t-1 then ARCH is much more important than options for forecasting future stock market volatility. Conversely, if volume was high during period t-1, then option-implied volatility is much more important than ARCH for forecasting future volatility. Our findings reveal an important regime-switching role for trading volume and suggest that option markets may be more efficient in high volume states. Results from various tests also uncover possible sources of volume-related nonlinearity in the relationship between past and future return innovations as captured by asymmetric ARCH models.
Download or read book Beyond Beta written by Samuel Kotz and published by World Scientific. This book was released on 2004 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical distributions are fundamental to Statistical Science and are a prime indispensable tool for its applications. This monograph is the first to examine an important but somewhat neglected field — univariate continuous distribution on a bounded domain, excluding the beta distribution. It provides an elementary but thorough discussion of “novel” contributions developed in recent years, such as the two-sided power, generalized trapezoidal and generalized Topp and Leone distributions, among others. It discusses a general framework for constructing two-sided distributions and some of its properties. It contains a comprehensive chapter on the triangular distribution as well as a chapter on earlier extensions not emphasized in existing literature. Special attention is given to estimation, in particular, non-standard maximum likelihood procedures. The applications are drawn mainly from the econometric and engineering domains.
Download or read book Time Series Models for Business and Economic Forecasting written by Philip Hans Franses and published by Cambridge University Press. This book was released on 2014-04-24 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: With a new author team contributing decades of practical experience, this fully updated and thoroughly classroom-tested second edition textbook prepares students and practitioners to create effective forecasting models and master the techniques of time series analysis. Taking a practical and example-driven approach, this textbook summarises the most critical decisions, techniques and steps involved in creating forecasting models for business and economics. Students are led through the process with an entirely new set of carefully developed theoretical and practical exercises. Chapters examine the key features of economic time series, univariate time series analysis, trends, seasonality, aberrant observations, conditional heteroskedasticity and ARCH models, non-linearity and multivariate time series, making this a complete practical guide. Downloadable datasets are available online.
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
