Download or read book Generalized Value at Risk Forecasting written by Alex Paseka and published by . This book was released on 2018 with total page 8 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, using estimating function approach, a new optimal volatility estimator is introduced, and, based on the recursive form of the estimator, a data-driven generalized EWMA model for VaR forecast is proposed. An appropriate data-driven model for volatility is identified by the relationship between the absolute deviation and the standard deviation for symmetric distributions with finite variance. It is shown that the asymptotic variance of the proposed volatility estimator is smaller than that of conventional estimators and is more appropriate for financial data with larger kurtosis. For IBM, Microsoft, and Apple stocks the proposed method is used to identify the model, estimate the volatility, and obtain VaR forecasts.

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 Data Driven Value at Risk Forecasting Using a SVR GARCH KDE Hybrid written by Marius Lux and published by . This book was released on 2018 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt: Appropriate risk management is crucial to ensure the competitiveness of financial institutions and the stability of the economy. One widely used financial risk measure is Value-at-Risk (VaR). VaR estimates based on linear and parametric models can lead to biased results or even underestimation of risk due to time varying volatility, skewness and leptokurtosis of financial return series. The paper proposes a nonlinear and nonparametric framework to forecast VaR. Mean and volatility are modeled via support vector regression~(SVR) where the volatility model is motivated by the standard generalized autoregressive conditional heteroscedasticity (GARCH) formulation. Based on this, VaR is derived by applying kernel density estimation (KDE). This approach allows for flexible tail shapes of the profit and loss distribution and adapts for a wide class of tail events. The SVR-GARCH-KDE hybrid is compared to standard, exponential and threshold GARCH models coupled with different error distributions. To examine the performance in different markets, one-day-ahead forecasts are produced for different financial indices. Model evaluation using a likelihood ratio based test framework for interval forecasts indicates that the SVR-GARCH-KDE hybrid performs competitive to benchmark models. Especially models that are coupled with a normal distribution are systematically outperformed.

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 Symmetric Multivariate and Related Distributions written by Kai Wang Fang and published by CRC Press. This book was released on 2018-01-18 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the publication of the by now classical Johnson and Kotz Continuous Multivariate Distributions (Wiley, 1972) there have been substantial developments in multivariate distribution theory especially in the area of non-normal symmetric multivariate distributions. The book by Fang, Kotz and Ng summarizes these developments in a manner which is accessible to a reader with only limited background (advanced real-analysis calculus, linear algebra and elementary matrix calculus). Many of the results in this field are due to Kai-Tai Fang and his associates and appeared in Chinese publications only. A thorough literature search was conducted and the book represents the latest work - as of 1988 - in this rapidly developing field of multivariate distributions. The authors are experts in statistical distribution theory.

Download or read book Measuring Market Risk with Value at Risk written by Pietro Penza and published by John Wiley & Sons. This book was released on 2001 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book, Measuring Market Risk with Value at Risk by Vipul Bansal and Pietro Penza, has three advantages over earlier works on the subject. First, it takes a decidedly global approach-an essential ingredient for any comprehensive work on market risk. Second, it ties the scientifically grounded, yet intuitively appealing, VaR measure to earlier, more idiosyncratic measures of market risk that are used in specific market environs (e.g., duration in fixed income). Finally, it encompasses all of the accepted approaches to calculating a VaR measure and presents them in a clearly explained fashion with supporting illustrations and completely worked-out examples." -from the Foreword by John F. Marshall, PhD, Principal, Marshall, Tucker & Associates, LLC "Measuring Market Risk with Value at Risk offers a much-needed intellectual bridge, a translation from the esoteric realm of mathematical finance to the domain of financial managers who seek guidance in applying developments from this important field of research as well as that of MBA-level graduate instruction. I believe the authors have done a commendable job of providing a carefully crafted, highly readable, and most useful work, and intend to recommend it to all those involved in business risk management applications." -Anthony F. Herbst, PhD, Professor of Finance and C.R. and D.S. Carter Chair, The University of Texas, El Paso and Founding editor of The Journal of Financial Engineering (1991-1998) "Finally there's a book that strikes a balance between rigor and application in the area of risk management in the banking industry. This innovative book is a MUST for both novices and professionals alike." -Robert P. Yuyuenyongwatana, PhD, Associate Professor of Finance, Cameron University "Measuring Market Risk with Value at Risk is one of the most complete discussions of this emerging topic in finance that I have seen. The authors develop a logical and rigorous framework for using VaR models, providing both historical references and analytical applications." -Kevin Wynne, PhD, Associate Professor of Finance, Lubin School of Business, Pace University

Download or read book Sample Size Skewness and Leverage Effects in Value at Risk and Expected Shortfall Estimation written by Laura García Jorcano and published by Ed. Universidad de Cantabria. This book was released on 2020-02-24 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: The thesis analyzes the effect that the sample size, the asymmetry in the distribution of returns and the leverage in their volatility have on the estimation and forecasting of market risk in financial assets. The goal is to compare the performance of a variety of models for the estimation and forecasting of Value at Risk (VaR) and Expected Shortfall (ES) for a set of assets of different nature: market indexes, individual stocks, bonds, exchange rates, and commodities. The three chapters of the thesis address issues of greatest interest for the measurement of risk in financial institutions and, therefore, for the supervision of risks in the financial system. They deal with technical issues related to the implementation of the Basel Committee's guidelines on some aspects of which very little is known in the academic world and in the specialized financial sector. In the first chapter, a numerical correction is proposed on the values usually estimatedwhen there is little statistical information, either because it is a financial asset (bond, investment fund...) recently created or issued, or because the nature or the structure of the asset or portfolio have recently changed. The second chapter analyzes the relevance of different aspects of risk modeling. The third and last chapter provides a characterization of the preferable methodology to comply with Basel requirements related to the backtesting of the Expected Shortfall.

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 Backtesting Value at Risk and Expected Shortfall written by Simona Roccioletti and published by Springer. This book was released on 2015-12-04 with total page 155 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book Simona Roccioletti reviews several valuable studies about risk measures and their properties; in particular she studies the new (and heavily discussed) property of "Elicitability" of a risk measure. More important, she investigates the issue related to the backtesting of Expected Shortfall. The main contribution of the work is the application of "Test 1" and "Test 2" developed by Acerbi and Szekely (2014) on different models and for five global market indexes.

Download or read book Risk Forecasting and Portfolio Optimization with Garch Skewed T Distributions and Multiple Timescales written by Yang Liu and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: ABSTRACT: It is well-established that distributions of financial returns are heavy-tailed and exhibit skewness and other non-Gaussian characteristics. As time series, return data have volatilities that vary over time and show profound serial correlation (or cross-correlation in the multivariate case). To address these issues, time series models such as GARCH (generalized autoregressive conditionally heteroskedastic) processes and non-Gaussian distributions such as generalized hyperbolic (GH) distributions have been introduced into financial modeling. A typical procedure featuring GARCH and non-Gaussian distributions involves the following steps. First, filter data with GARCH to get residuals that are approximately i.i.d. Second, calibrate parameters of a non-Gaussian distribution to those residuals. Finally, forecast various quantities based on knowledge of the calibrated distribution. Existing implementations of this procedure are fixed-frequency in nature. That is, all three steps are carried out on the same timescale. Reliable filtering and calibration requires a sufficient amount of historical data. As the forecast horizon grows, the model demands an increasingly long price history and may become infeasible if data are too scarce. To reduce the model's dependence on data availability, we propose a mixed-frequency method. Filtering and calibration are done on a relatively small timescale where data are more abundant. We then shift to a longer time horizon and make forecasts through aggregating GARCH processes and Monte Carlo simulation. We first apply this mixed-frequency approach to forecasting univariate value-at-risk (VaR) for stock index returns. Backtesting conducted on a variety of timescales shows that the method is indeed viable. Moreover, compared with the fixed-frequency method, our new method is able to produce VaR forecasts that respond more quickly to volatility changes. Therefore, even if data availability is not an issue, the mixed-frequency method is still a valuable alternative for risk managers. Portfolio optimization, a multivariate problem, is tackled next. We enhance traditional Markowitz optimization with expected shortfall (ES), which measures tail risks better than standard deviation, and skewed t distributions, a promising subfamily of GH distributions. The mixed-frequency idea is incorporated as well. Factors that affect the efficient frontier and optimal portfolio compositions are thoroughly discussed. Last but not least, we implement investment strategies based on GARCH-skewed t-ES portfolio optimization and evaluate their performance, both in terms of return and risk.

Download or read book Value at risk Forecasting Based on the Asymmetric Exponential Power Distribution written by Lu Ou and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Value-at-risk (VaR) is a standard measure of market risk in financial markets. This paper proposes a novel, adaptive, and flexible method to forecast volatility, asymmetry, and VaR. As an extension of the existing exponential smoothing as well as GARCH formulations, the method is motivated from an Asymmetric Exponential Power distribution, which includes the Laplace, Normal, and Uniform distributions as special cases and takes into account the potentially time-varying nature in volatility and skewness of financial return series. Results from a Monte Carlo simulation study and an empirical application to the S&P 500 index illustrate that the proposed method offers more accurate and robust VaR forecasts across a range of models at different confidence levels compared to other popular parametric alternatives.

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 Forecasting Value at risk and Expected Shortfall in Large Portfolios written by Marc Hallin and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Time Series Models written by D.R. Cox and published by CRC Press. This book was released on 2020-11-26 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: The analysis prediction and interpolation of economic and other time series has a long history and many applications. Major new developments are taking place, driven partly by the need to analyze financial data. The five papers in this book describe those new developments from various viewpoints and are intended to be an introduction accessible to readers from a range of backgrounds. The book arises out of the second Seminaire European de Statistique (SEMSTAT) held in Oxford in December 1994. This brought together young statisticians from across Europe, and a series of introductory lectures were given on topics at the forefront of current research activity. The lectures form the basis for the five papers contained in the book. The papers by Shephard and Johansen deal respectively with time series models for volatility, i.e. variance heterogeneity, and with cointegration. Clements and Hendry analyze the nature of prediction errors. A complementary review paper by Laird gives a biometrical view of the analysis of short time series. Finally Astrup and Nielsen give a mathematical introduction to the study of option pricing. Whilst the book draws its primary motivation from financial series and from multivariate econometric modelling, the applications are potentially much broader.

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 Value at Risk written by James Engel and published by . This book was released on 1999 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past decade value at risk (VaR) has become the most widely used technique for the quantification of market-risk exposure. VaR is a measure of the potential loss that may occur from adverse moves in market prices (interest rates, exchange rates, equity prices and so forth). The capacity for a VaR measure to accurately predict future risk exposures depends upon the forecasts of the volatility of market rates and the correlations between the various market rates (that is, the variance-covariance matrix) incorporated into the VaR model. In this paper we first present the results of tests of the stability of the variances, covariances and correlations for exchange rates and Australian interest rates. Secondly, we assess the performance of several time-series models that may be used to forecast the variance-covariance matrix. In particular three models for the variance-covariance matrix are considered: equally weighted historical variances and covariances, exponentially weighted averages of historical variances and generalised autoregressive conditional heteroskedasticity (GARCH). We conclude that simple models perform as well as their more sophisticated GARCH counterparts.

Download or read book Financial Risk Modelling and Portfolio Optimization with R written by Bernhard Pfaff and published by John Wiley & Sons. This book was released on 2016-08-16 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: Financial Risk Modelling and Portfolio Optimization with R, 2nd Edition Bernhard Pfaff, Invesco Global Asset Allocation, Germany A must have text for risk modelling and portfolio optimization using R. This book introduces the latest techniques advocated for measuring financial market risk and portfolio optimization, and provides a plethora of R code examples that enable the reader to replicate the results featured throughout the book. This edition has been extensively revised to include new topics on risk surfaces and probabilistic utility optimization as well as an extended introduction to R language. Financial Risk Modelling and Portfolio Optimization with R: Demonstrates techniques in modelling financial risks and applying portfolio optimization techniques as well as recent advances in the field. Introduces stylized facts, loss function and risk measures, conditional and unconditional modelling of risk; extreme value theory, generalized hyperbolic distribution, volatility modelling and concepts for capturing dependencies. Explores portfolio risk concepts and optimization with risk constraints. Is accompanied by a supporting website featuring examples and case studies in R. Includes updated list of R packages for enabling the reader to replicate the results in the book. Graduate and postgraduate students in finance, economics, risk management as well as practitioners in finance and portfolio optimization will find this book beneficial. It also serves well as an accompanying text in computer-lab classes and is therefore suitable for self-study.