Download or read book Forecasting Realized Volatility with Linear and Nonlinear Models written by Michael McAleer and published by . This book was released on 2009 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Forecasting Realized Volatility with Linear and Nonlinear Univariate Models written by Michael McAleer and published by . This book was released on 2010 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Linear and Nonlinear Models for Forecasting the Realized Volatility of Cryptocurrencies written by Ivan Mitkov and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Forecasting Realized Volatility written by Rafael Branco and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We evaluate the performance of several linear and nonlinear machine learning models in forecasting the realized volatility (RV) of ten global stock market indices in the period from January 2000 to December 2021. We train models using a dataset which includes past values of the RV and additional predictors (composed by lagged returns and macroeconomic variables), and compare them to the widely used heterogeneous autoregressive (HAR) model. Our main conclusions are that (i) the additional predictors improve the out-of-sample forecasts of 1-day-ahead RV, and (ii) we find no evidence that nonlinear models can outperform statistically either linear models or HAR models with additional predictors.
Download or read book Nonlinear Financial Econometrics Forecasting Models Computational and Bayesian Models written by G. Gregoriou and published by Springer. This book was released on 2010-12-21 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book investigates several competing forecasting models for interest rates, financial returns, and realized volatility, addresses the usefulness of nonlinear models for hedging purposes, and proposes new computational techniques to estimate financial processes.
Download or read book Coupling High Frequency Data with Nonlinear Models in Multiple Step Ahead Forecasting of Energy Markets Volatility written by Jozef Baruník and published by . This book was released on 2015 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the past decade, the popularity of realized measures and various linear models for volatility forecasting has attracted attention in the literature on the price variability of energy markets. However, results that would guide practitioners to a specific estimator and model when aiming for the best forecasting accuracy are missing. This paper contributes to the ongoing debate with a comprehensive evaluation of multiple-step-ahead volatility forecasts of energy markets using several popular high-frequency measures and forecasting models. To capture the complex patterns hidden to linear models commonly used to forecast realized volatility, this paper also contributes to the literature by coupling realized measures with artificial neural networks as a forecasting tool. Forecasting performance is compared across models as well as realized measures of crude oil, heating oil, and natural gas volatility during three qualitatively distinct periods covering the pre-crisis period, recent global turmoil of markets in 2008, and the most recent post-crisis period. We conclude that coupling realized measures with artificial neural networks results in both statistical and economic gains, reducing the tendency to over-predict volatility uniformly during all tested periods. Our analysis favors the median realized volatility, as it delivers the best performance and is a computationally simple alternative for practitioners.
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 Forecasting Realized Volatility With Kernel Ridge Regression written by Blake LeBaron and published by . This book was released on 2018 with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper explores a common machine learning tool, the kernel ridge regression, as applied to financial volatility forecasting. It is shown that kernel ridge provides reliable forecast improvements to both a linear specification, and a fitted nonlinear specification which represents well known empirical features from volatility modeling. Therefore, the kernel ridge specification is still finding some nonlinear improvements that are not part of the usual volatility modeling toolkit. Various diagnostics show it to be a reliable and useful tool. Finally, the results are applied in a dynamic volatility control trading strategy. The kernel ridge results again show improvements over linear modeling tools when applied to building a dynamic strategy.
Download or read book Model Selection and Multimodel Inference written by Kenneth P. Burnham and published by Springer Science & Business Media. This book was released on 2007-05-28 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unique and comprehensive text on the philosophy of model-based data analysis and strategy for the analysis of empirical data. The book introduces information theoretic approaches and focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. It contains several new approaches to estimating model selection uncertainty and incorporating selection uncertainty into estimates of precision. An array of examples is given to illustrate various technical issues. The text has been written for biologists and statisticians using models for making inferences from empirical data.
Download or read book Modern Linear and Nonlinear Econometrics written by Joseph Plasmans and published by Springer Science & Business Media. This book was released on 2006-08-30 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: The basic characteristic of Modern Linear and Nonlinear Econometrics is that it presents a unified approach of modern linear and nonlinear econometrics in a concise and intuitive way. It covers four major parts of modern econometrics: linear and nonlinear estimation and testing, time series analysis, models with categorical and limited dependent variables, and, finally, a thorough analysis of linear and nonlinear panel data modeling. Distinctive features of this handbook are: -A unified approach of both linear and nonlinear econometrics, with an integration of the theory and the practice in modern econometrics. Emphasis on sound theoretical and empirical relevance and intuition. Focus on econometric and statistical methods for the analysis of linear and nonlinear processes in economics and finance, including computational methods and numerical tools. -Completely worked out empirical illustrations are provided throughout, the macroeconomic and microeconomic (household and firm level) data sets of which are available from the internet; these empirical illustrations are taken from finance (e.g. CAPM and derivatives), international economics (e.g. exchange rates), innovation economics (e.g. patenting), business cycle analysis, monetary economics, housing economics, labor and educational economics (e.g. demand for teachers according to gender) and many others. -Exercises are added to the chapters, with a focus on the interpretation of results; several of these exercises involve the use of actual data that are typical for current empirical work and that are made available on the internet. What is also distinguishable in Modern Linear and Nonlinear Econometrics is that every major topic has a number of examples, exercises or case studies. By this `learning by doing' method the intention is to prepare the reader to be able to design, develop and successfully finish his or her own research and/or solve real world problems.
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 Modeling and Forecasting S P 500 Volatility written by Martin Martens and published by . This book was released on 2007 with total page 43 pages. Available in PDF, EPUB and Kindle. Book excerpt: The sum of squared intraday returns provides an unbiased and almost error-free measure of ex-post volatility. In this paper we develop a nonlinear Autoregressive Fractionally Integrated Moving Average (ARFIMA) model for realized volatility, which accommodates level shifts, day-of-the-week effects, leverage effects and volatility level effects. Applying the model to realized volatilities of the Samp;P 500 stock index and three exchange rates produces forecasts that clearly improve upon the ones obtained from a linear ARFIMA model and from conventional time-series models based on daily returns, treating volatility as a latent variable.
Download or read book An Empirical Investigation of Non linear Effects in Realized Volatility written by Kayhan Alci and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis empirically applies the heterogeneous autoregressive (HAR) model to realized volatility obtained from high-frequency data of the EURO STOXX 50 index. After primary investigations of jumps and asymmetric effects, general non-linear effects expressed in terms of regime changes and structural breaks are analyzed in a tree-structured threshold model. Whereas thresholds for the short-term model are only found in endogenous variables, regimes with respect to exogenous variables such as U.S. stock market conditions and expectations of the EUR/USD volatility are identified for the mid- and long-term ones. Out-sample forecasting experiments show that the inclusion of regime shifts significantly improves performances, especially regarding short- to medium-term forecasts and predictions in highly volatile periods.
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 The Oxford Handbook of Economic Forecasting written by Michael P. Clements and published by OUP USA. This book was released on 2011-07-08 with total page 732 pages. Available in PDF, EPUB and Kindle. Book excerpt: Greater data availability has been coupled with developments in statistical theory and economic theory to allow more elaborate and complicated models to be entertained. These include factor models, DSGE models, restricted vector autoregressions, and non-linear models.
Download or read book Forecasting in the Presence of Structural Breaks and Model Uncertainty written by David E. Rapach and published by Emerald Group Publishing. This book was released on 2008-02-29 with total page 691 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting in the presence of structural breaks and model uncertainty are active areas of research with implications for practical problems in forecasting. This book addresses forecasting variables from both Macroeconomics and Finance, and considers various methods of dealing with model instability and model uncertainty when forming forecasts.
Download or read book Modeling and Forecasting Realized Volatility written by Torben G. Andersen and published by . This book was released on 2001 with total page 62 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper discusses the measurement, modeling, and forecasting of daily and lower frequency volatility and return distributions.
