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 . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The estimation of risk measures is an area of highest importance in the financial industry. Risk measures play a major role in the risk-management and in the computation of regulatory capital. The Basel III document [13] has suggested to shift from Value-at-Risk (VaR) into Expected Shortfall (ES) as a risk measure and to consider stressed scenarios at a new con dence level of 97:5%. This change is motivated by the appealing theoretical properties of ES as a measure of risk and the poor properties of VaR. In particular, VaR fails to control for tail risk". In this transition, the major challenge faced by nancial institutions is the unavailability of simple tools for evaluation of ES forecasts (i.e. backtesting ES) The objective of this thesis is to compare the performance of a variety of models for VaR and ES estimation for a collection of assets of di erent nature: stock indexes, individual stocks, bonds, exchange rates, and commodities. Throughout the thesis, by a VaR or an ES model" is meant a given speci cation for conditional volatility, combined with an assumption on the probability distribution of return innovations...

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 Essays on Risk and Uncertainty in Economics and Finance written by Jorge Mario Uribe Gil and published by Ed. Universidad de Cantabria. This book was released on 2022-11-22 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book adds to the resolution of two problems in finance and economics: i) what is macro-financial uncertainty? : How to measure it? How is it different from risk? How important is it for the financial markets? And ii) what sort of asymmetries underlie financial risk and uncertainty propagation across the global financial markets? That is, how risk and uncertainty change according to factors such as market states or market participants. In Chapter 2, which is entitled “Momentum Uncertainties”, the relationship between macroeconomic uncertainty and the abnormal returns of a momentum trading strategy in the stock market is studies. We show that high levels of uncertainty in the economy impact negatively and significantly the returns of a portfolio of stocks that consist of buying past winners and selling past losers. High uncertainty reduces below zero the abnormal returns of momentum, extinguishes the Sharpe ratio of the momentum strategy, while increases the probability of momentum crashes both by increasing the skewness and the kurtosis of the momentum return distribution. Uncertainty acts as an economic regime that underlies abrupt changes over time of the returns generated by momentum strategies. In Chapter 3, “Measuring Uncertainty in the Stock Market”, a new index for measuring stock market uncertainty on a daily basis is proposed. The index considers the inherent differentiation between uncertainty and the common variations between the series. The second contribution of chapter 3 is to show how this financial uncertainty index can also serve as an indicator of macroeconomic uncertainty. Finally, the dynamic relationship between uncertainty and the series of consumption, interest rates, production and stock market prices, among others, is analized. In chapter 4: “Uncertainty, Systemic Shocks and the Global Banking Sector: Has the Crisis Modified their Relationship?” we explore the stability of systemic risk and uncertainty propagation among financial institutions in the global economy, and show that it has remained stable over the last decade. Additionally, a new simple tool for measuring the resilience of financial institutions to these systemic shocks is provided. We examine the characteristics and stability of systemic risk and uncertainty, in relation to the dynamics of the banking sector stock returns. This sort of evidence is supportive of past claims, made in the field of macroeconomics, which hold that during the global financial crisis the financial system may have faced stronger versions of traditional shocks rather than a new type of shock. In chapter 5, “Currency downside risk, liquidity, and financial stability”, downside risk propagation across global currency markets and the ways in which it is related to liquidity is analyzed. Two primary contributions to the literature follow. First, tail-spillovers between currencies in the global FX market are estimated. This index is easy to build and does not require intraday data, which constitutes an important advantage. Second, we show that turnover is related to risk spillovers in global currency markets. Chapter 6 is entitled “Spillovers from the United States to Latin American and G7 Stock Markets: A VAR-Quantile Analysis”. This chapter contributes to the studies of contagion, market integration and cross-border spillovers during both regular and crisis episodes by carrying out a multivariate quantile analysis. It focuses on Latin American stock markets, which have been characterized by a highly positive dynamic in recent decades, in terms of market capitalization and liquidity ratios, after a far-reaching process of market liberalization and reforms to pension funds across the continent during the 80s and 90s. We document smaller dependences between the LA markets and the US market than those between the US and the developed economies, especially in the highest and lowest quantiles.

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 Comparative Analyses of Expected Shortfall and VaR written by Yasuhiro Yamai and published by . This book was released on 2001 with total page 56 pages. Available in PDF, EPUB and Kindle. Book excerpt: Expected shortfall is compared with Value-at-Risk (VaR) in three aspects: estimation errors, decomposition into risk factors, and optimization. Advantages and disadvantages of expected shortfall over VaR are shown, and that expected shortfall is easily decomposed (needing a larger size of sample than VaR for the same level of accuracy) and optimized, while VaR is not.

Download or read book Nonparametric Estimation of Expected Shortfall written by Song Xi Chen and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The expected shortfall is an increasingly popular risk measure in financial risk management and it possesses the desired sub-additivity property, which is lacking for the value at risk (VaR). We consider two nonparametric expected shortfall estimators for dependent financial losses. One is a sample average of excessive losses larger than a VaR. The other is a kernel smoothed version of the first estimator (Scaillet, 2004 Mathematical Finance), hoping that more accurate estimation can be achieved by smoothing. Our analysis reveals that the extra kernel smoothing does not produce more accurate estimation of the shortfall. This is different from the estimation of the VaR where smoothing has been shown to produce reduction in both the variance and the mean square error of estimation. Therefore, the simpler ES estimator based on the sample average of excessive losses is attractive for the shortfall estimation.

Download or read book Skewness Sampling Risk and the Importance of Diversification written by R. Stephen Sears and published by . This book was released on 1984 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Simple Skewed Distribution with Asset Pricing Applications written by Frans de Roon and published by . This book was released on 2016 with total page 53 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent research has identified skewness and downside risk as one of the most important features of risk. We present a new distribution which makes modeling skewed risks no more difficult than normally distributed (symmetric) risks. Our distribution is a combination of the "downside" and "upside" half of two normal distributions, and its parameters can be calculated in closed-form to match a given mean, variance, and skewness. Value-at-risk, expected shortfall, portfolio weights, and risk premia have simple expressions for our distribution and show economically meaningful deviations from the normal case already for very modest levels of skewness. An empirical application suggests that our distribution fits the data well.

Download or read book Statistics and Data Analysis for Financial Engineering written by David Ruppert and published by Springer. This book was released on 2015-04-21 with total page 736 pages. Available in PDF, EPUB and Kindle. Book excerpt: The new edition of this influential textbook, geared towards graduate or advanced undergraduate students, teaches the statistics necessary for financial engineering. In doing so, it illustrates concepts using financial markets and economic data, R Labs with real-data exercises, and graphical and analytic methods for modeling and diagnosing modeling errors. These methods are critical because financial engineers now have access to enormous quantities of data. To make use of this data, the powerful methods in this book for working with quantitative information, particularly about volatility and risks, are essential. Strengths of this fully-revised edition include major additions to the R code and the advanced topics covered. Individual chapters cover, among other topics, multivariate distributions, copulas, Bayesian computations, risk management, and cointegration. Suggested prerequisites are basic knowledge of statistics and probability, matrices and linear algebra, and calculus. There is an appendix on probability, statistics and linear algebra. Practicing financial engineers will also find this book of interest.

Download or read book Systemic Contingent Claims Analysis written by Mr.Andreas A. Jobst and published by International Monetary Fund. This book was released on 2013-02-27 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt: The recent global financial crisis has forced a re-examination of risk transmission in the financial sector and how it affects financial stability. Current macroprudential policy and surveillance (MPS) efforts are aimed establishing a regulatory framework that helps mitigate the risk from systemic linkages with a view towards enhancing the resilience of the financial sector. This paper presents a forward-looking framework ("Systemic CCA") to measure systemic solvency risk based on market-implied expected losses of financial institutions with practical applications for the financial sector risk management and the system-wide capital assessment in top-down stress testing. The suggested approach uses advanced contingent claims analysis (CCA) to generate aggregate estimates of the joint default risk of multiple institutions as a conditional tail expectation using multivariate extreme value theory (EVT). In addition, the framework also helps quantify the individual contributions to systemic risk and contingent liabilities of the financial sector during times of stress.

Download or read book The Estimation of Leverage Effect with High Frequency Data written by Dan Christina Wang and published by . This book was released on 2012 with total page 101 pages. Available in PDF, EPUB and Kindle. Book excerpt: The leverage effect has become an extensively studied phenomenon that describes the (usually) negative correlation between stock returns and volatility. All the previous studies have focused on the origin and properties of the leverage effect. Even though most studies of the leverage effect are based on cross-sectional calibration with parametric models, few of them have carefully studied its estimation. However, estimation of the leverage effect is important because sensible inference is possible only when the leverage effect is estimated reliably. In this thesis, we provide the first nonparametric estimation for a class of stochastic measures of the leverage effect. Unlike most previous work conducted over daily or longer return horizons, we study the estimation of the leverage effect with high frequency data. In order to construct estimators with good statistical properties, we introduce a new stochastic leverage effect parameter, which is usually not specified by other studies. The estimators and their statistical properties are provided in cases both with and without microstructure noise, under the stochastic volatility model. In asymptotics, the consistency and limiting distribution of the estimators are derived and corroborated by simulation results. For consistency, a previously unknown bias correction factor is added to the estimators. In finite samples, we provide two modifications of the estimator to improve its performance. In addition, we explore several applications of the estimators. In one application, we apply the estimators in high frequency regression and discover a novel predictor of volatility that depends on an estimator of the leverage effect. A related study reveals that the leverage effect improves estimation of volatility. In another application, we discover the first theoretical connection between skewness and the leverage effect, which yields a new predictor of skewness.

Download or read book The Estimation of Leverage Effect with High Frequency Data written by Christina Dan Wang and published by . This book was released on 2014 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage effect has become an extensively studied phenomenon which describes the negative relation between the stock return and its volatility. Although this characteristic of stock returns is well acknowledged, most studies about it are based on cross-sectional calibration with parametric models. Other than that, most previous work are over daily or longer return horizons and usually do not specify the quantitative measure of it. This paper provides nonparametric estimation of a class of stochastic measures of leverage effect for both cases with and without microstructure noise, and studies the statistical properties of the estimators when the log price process is a quite general continuous semimartingale, in the stochastic volatility context and for high frequency data. The consistency and limit distribution of the estimators are derived, and simulation results present the properties accordingly. This estimator also provides the opportunity to study the empirical relation between skewness and leverage effect, which further leads to the prediction of skewness. Furthermore, adopting similar ideas to these in this paper, it is easy to extend the study to other important aspects of the stock returns, e.g. volatility of volatility.

Download or read book Calculation of Value at risk and Expected Shortfall Under Model Uncertainty written by and published by . This book was released on 2015 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt:

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 Value at Risk and Expected Shortfall When There Is Long Range Dependence written by Wolfgang K. Härdle and published by . This book was released on 2017 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt: Empirical studies have shown that a large number of financial asset returns exhibit fat tails and are often characterized by volatility clustering and asymmetry. Also revealed as a stylized fact is Long memory or long range dependence in market volatility, with significant impact on pricing and forecasting of market volatility. The implication is that models that accomodate long memory hold the promise of improved long-run volatility forecast as well as accurate pricing of long-term contracts. On the other hand, recent focus is on whether long memory can affect the measurement of market risk in the context of Value-at-Risk (V aR). In this paper, we evaluate the Value-at-Risk (VaR) and Expected Shortfall (ESF) in financial markets under such conditions. We examine one equity portfolio, the British FTSE100 and three stocks of the German DAX index portfolio (Bayer, Siemens and Volkswagen). Classical VaR estimation methodology such as exponential moving average (EMA) as well as extension to cases where long memory is an inherent characteristics of the system are investigated. In particular, we estimate two long memory models, the Fractional Integrated Asymmetric Power-ARCH and the Hyperbolic-GARCH with different error distribution assumptions. Our results show that models that account for asymmetries in the volatility specifications as well as fractional integrated parametrization of the volatility process, perform better in predicting the one-step as well as five-step ahead VaR and ESF for short and long positions than short memory models. This suggests that for proper risk valuation of options, the degree of persistence should be investigated and appropriate models that incorporate the existence of such characteristic be taken into account.

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 Stochastic Volatility written by Neil Shephard and published by Oxford University Press, USA. This book was released on 2005 with total page 534 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic volatility is the main concept used in the fields of financial economics and mathematical finance to deal with time-varying volatility in financial markets. This work brings together some of the main papers that have influenced this field, andshows that the development of this subject has been highly multidisciplinary.