Download or read book Daily VAR Forecasts with Realized Volatility and GARCH Models written by Barbara Bedowska-Sojka and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper we evaluate alternative volatility forecasting methods under Value at Risk (VaR) modelling. We calculate one-step-ahead forecasts of daily VaR for the WIG20 index quoted on the Warsaw Stock Exchange within the period from 2007 to 2011. Our analysis extends the existing research by broadening the class of the models, including both the GARCH class models based on daily data and models for realized volatility based on intraday returns (HAR-RV, HAR-RV-J and ARFIMA). We find that the VaR estimates obtained from the models for daily returns and realized volatility give comparable results. Both long memory features and asymmetry are found to improve the VaR forecasts. However, when loss functions are considered, the models based on daily data allow minimizing regulatory loss function, whereas the models based on realized volatility allow minimizing the opportunity cost of capital.

Download or read book Value at Risk Forecasting written by Thedo Linssen and published by . This book was released on 2019 with total page 43 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this paper is to investigate whether a dynamic Value at Risk model and high frequency realized volatility models can improve the accuracy of 1-day ahead VaR forecasting beyond the performance of frequently used models. As such, this paper constructs 60 conditional volatility forecasting models. Several extensions of the GARCH model are included, such as the nonlinear and asymmetric models. Moreover, several return distributions are assumed for the error term, in order to allow for more flexible modeling in the tails. A rolling Model Confidence Set is subsequently constructed, ensuring that only models with superior out-of-sample forecasting performance remain. A model averaging technique is applied to the remaining superior models, which generates the dynamic VaR forecasts. Moreover, several extensions of the HAR realized volatility model are included in this paper to forecast VaR. In a series of extensive back tests, this paper finds that the dynamic VaR model produces forecasts which are superior to traditional models and HAR models. The result hold for the 95% VaR, but are even more pronounced for the 99% VaR. The traditional models severely underestimate risk at higher confidence levels, whereas the applied dynamic VaR correctly accounts for it.

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.

Download or read book Modelling Daily Value at Risk Using Realized Volatility and Arch Type Models written by Pierre Giot and published by . This book was released on 2003 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper we show how to compute a daily VaR measure for two stock indexes (CAC40 and SP500) using the one-day-ahead forecast of the daily realized volatility. The daily realized volatility is equal to the sum of the squared intraday returns over a given day and thus uses intraday information to define an aggregated daily volatility measure. While the VaR specification based on an ARFIMAX(0,d,1)-skewed Student model for the daily realized volatility provides adequate one-day-ahead VaR forecasts, it does not really improve on the performance of a VaR model based on the skewed Student APARCH model and estimated using daily data. Thus, for the two financial assets considered in an univariate framework, both methods seem to be equivalent. This paper also shows that daily returns standardized by the square root of the one-day-ahead forecast of the daily realized volatility are not normally distributed.

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 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 Forecasts Based on Data Sampled at Different Frequencies written by Barbara Bedowska-Sojka and published by . This book was released on 2013 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt: Measuring and modeling unobservable volatility is one of the key issues in finance and risk management. Value at Risk (VaR) is a natural application of volatility estimates and therefore allows to differentiate between volatility estimation approaches. In this paper we consider daily VaR measures for WIG20 index using one-step-ahead forecasts of volatility in a crisis period. We compare forecasts from GARCH family models based on daily data with forecasts from HAR-RV and ARFIMA models for realized volatility based on intraday returns. Both VaR forecasts obtained from models that use intraday information in defining volatility and simple models based on daily returns deliver similar results. However, when loss functions are considered, HAR-RV models allow to minimize opportunity cost of capital.

Download or read book Forecasting Realized Volatility of Russian Stocks Using Google Trends and Implied Volatility written by Timofey Bazhenov and published by . This book was released on 2019 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work proposes to forecast the Realized Volatility (RV) and the Value-at-Risk (VaR) of the most liquid Russian stocks using GARCH, ARFIMA and HAR models, including both the implied volatility computed from options prices and Google Trends data. The in-sample analysis showed that only the implied volatility had a significant effect on the realized volatility across most stocks and estimated models, whereas Google Trends did not have any significant effect. The out-of-sample analysis highlighted that models including the implied volatility improved their forecasting performances, whereas models including internet search activity worsened their performances in several cases. Moreover, simple HAR and ARFIMA models without additional regressors often reported the best forecasts for the daily realized volatility and for the daily Value-at-Risk at the 1 % probability level, thus showing that efficiency gains more than compensate any possible model misspecifications and parameters biases. Our empirical evidence shows that, in the case of Russian stocks, Google Trends does not capture any additional information already included in the implied volatility.

Download or read book Value at Risk 3rd Ed written by Philippe Jorion and published by McGraw Hill Professional. This book was released on 2006-11-09 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since its original publication, Value at Risk has become the industry standard in risk management. Now in its Third Edition, this international bestseller addresses the fundamental changes in the field that have occurred across the globe in recent years. Philippe Jorion provides the most current information needed to understand and implement VAR-as well as manage newer dimensions of financial risk. Featured updates include: An increased emphasis on operational risk Using VAR for integrated risk management and to measure economic capital Applications of VAR to risk budgeting in investment management Discussion of new risk-management techniques, including extreme value theory, principal components, and copulas Extensive coverage of the recently finalized Basel II capital adequacy rules for commercial banks, integrated throughout the book A major new feature of the Third Edition is the addition of short questions and exercises at the end of each chapter, making it even easier to check progress. Detailed answers are posted on the companion web site www.pjorion.com/var/. The web site contains other materials, including additional questions that course instructors can assign to their students. Jorion leaves no stone unturned, addressing the building blocks of VAR from computing and backtesting models to forecasting risk and correlations. He outlines the use of VAR to measure and control risk for trading, for investment management, and for enterprise-wide risk management. He also points out key pitfalls to watch out for in risk-management systems. The value-at-risk approach continues to improve worldwide standards for managing numerous types of risk. Now more than ever, professionals can depend on Value at Risk for comprehensive, authoritative counsel on VAR, its application, and its results-and to keep ahead of the curve.

Download or read book Cointegration Causality and Forecasting written by Halbert White and published by Oxford University Press, USA. This book was released on 1999 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: A collection of essays in honour of Clive Granger. The chapters are by some of the world's leading econometricians, all of whom have collaborated with and/or studied with both) Clive Granger. Central themes of Granger's work are reflected in the book with attention to tests for unit roots and cointegration, tests of misspecification, forecasting models and forecast evaluation, non-linear and non-parametric econometric techniques, and overall, a careful blend of practical empirical work and strong theory. The book shows the scope of Granger's research and the range of the profession that has been influenced by his work.

Download or read book Systemic Risk Tomography written by Monica Billio and published by Elsevier. This book was released on 2016-11-25 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: In April 2010 Europe was shocked by the Greek financial turmoil. At that time, the global financial crisis, which started in the summer of 2007 and reached systemic dimensions in September 2008 with the Lehman Brothers' crash, took a new course. An adverse feedback loop between sovereign and bank risks reflected into bubble-like spreads, as if financial markets had received a wake-up call concerning the disregarded structural vulnerability of economies at risk.These events inspired the SYRTO project to "think and rethink the economic and financial system and to conceive it as an "ensemble of Sovereigns and Banks with other Financial Intermediaries and Corporations. Systemic Risk Tomography: Signals, Measurement and Transmission Channels proposes a novel way to explore the financial system by sectioning each part of it and analyzing all relevant inter-relationships. The financial system is inspected as a biological entity to identify the main risk signals and to provide the correct measures of prevention and intervention. - Explores the economic and financial system of Sovereigns, Banks, other Financial Intermediaries, and Corporations - Presents the financial system as a biological entity to be explored in order to identify the main risk signals and provide the right measures of prevention and interventions - Offers a new, systemic-based approach to construct a hierarchical, internally coherent framework to be used in developing an effective early warning system

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 Elements of Financial Risk Management written by Peter Christoffersen and published by Academic Press. This book was released on 2011-11-22 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Second Edition of this best-selling book expands its advanced approach to financial risk models by covering market, credit, and integrated risk. With new data that cover the recent financial crisis, it combines Excel-based empirical exercises at the end of each chapter with online exercises so readers can use their own data. Its unified GARCH modeling approach, empirically sophisticated and relevant yet easy to implement, sets this book apart from others. Five new chapters and updated end-of-chapter questions and exercises, as well as Excel-solutions manual, support its step-by-step approach to choosing tools and solving problems. Examines market risk, credit risk, and operational risk Provides exceptional coverage of GARCH models Features online Excel-based empirical exercises

Download or read book VaR and Intra Day Volatility Forecasting written by Timotheos Angelidis and published by . This book was released on 2005 with total page 12 pages. Available in PDF, EPUB and Kindle. Book excerpt: We evaluate the performance of symmetric and asymmetric ARCH models in forecasting one-day-ahead Value-at-Risk (VaR) and realized intra-day volatility of two equity indices in the Athens Stock Exchange (ASE). Under the framework of three distributional assumptions, we find out that the most appropriate method for the Bank index in forecasting the one-day-ahead VaR is the symmetric model with normally distributed innovations, while the asymmetric model with asymmetric conditional distribution applies for the General index. On the other hand, the asymmetric model tracks closer the one-step-ahead intra-day realized volatility with conditional normally distributed innovations for the Bank index but with asymmetric and leptokurtic distributed innovations for the General index. Therefore, as concerns the Greek stock market, there are adequate methods for predicting market risk but it does not seem to be a specific model that is the most accurate for all the forecasting tasks.

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.

Download or read book Modelling and Forecasting Dynamic VAR Thresholds for Risk Management and Regulation written by David E. Allen and published by . This book was released on 2010 with total page 14 pages. Available in PDF, EPUB and Kindle. Book excerpt: The paper describes alternative methods of estimating Value-at-Risk (VaR) thresholds based on two calibrated models and three conditional volatility or GARCH models. The five models of volatility are used to estimate and forecast the VaR thresholds of an equally-weighted portfolio, comprising four financial stock indexes, namely Samp;P500, CAC40, FTSE100 a Swiss market index (SMI). On the basis of the number of (non-)violations of the Basel Accord thresholds, the best performing model is PS-GARCH, followed closely by VARMA-AGARCH, neither of which would lead to the imposition of any penalties. The next best performing threshold forecasts are given by the Portfolio-GARCH and RiskmetricsTM-EWMA models, both of which would have a penalty of 0.5. Not surprisingly, the worst forecasts are obtained from the standard normal method based on historical variances.

Download or read book Forecasting One Day Ahead VAR and Intra Day Realized Volatility in the Athens Stock Exchange Market written by Timotheos Angelidis and published by . This book was released on 2007 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt: We evaluate the performance of symmetric and asymmetric ARCH models in forecasting one-day-ahead Value-at-Risk (VaR) and realized intra day volatility of two equity indices in the Athens Stock Exchange (ASE). Under the framework of three distributional assumptions, we find out that the most appropriate method for the Bank index in forecasting the one-day-ahead VaR is the symmetric model with normally distributed innovations, while the asymmetric model with asymmetric conditional distribution applies for the General index. On the other hand, the asymmetric model tracks closer the one-step-ahead intra day realized volatility with conditional normally distributed innovations for the Bank index but with asymmetric and leptokurtic distributed innovations for the General index. Therefore, as concerns the Greek stock market, there are adequate methods for predicting market risk but it does not seem to be a specific model that is the most accurate for all the forecasting tasks.