Download or read book Estimation of Portfolio Value at risk and Expected Shortfall Using Copulas Extreme Value Theory and Doubly Noncentral T Distribution written by Miao Zhong and published by . This book was released on 2007 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Estimation of VAR Using Copula and Extreme Value Theory written by Luiz Koodi Hotta and published by . This book was released on 2013 with total page 14 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper proposes a method for estimating the VaR of a portfolio based on copula and extreme value theory. Each return is modeled by ARMAxGARCH models with the joint distribution of innovations modeled by copula. The marginal distributions are modeled by the generalized Pareto distribution in the left tail (large loss) and empirical distribution otherwise. The copula is estimated by an estimator which gives more weight to observations with large loss. The method is applied to a two-asset portfolio and compared to other traditional methods.

Download or read book Extreme Value Modeling and Risk Analysis written by Dipak K. Dey and published by CRC Press. This book was released on 2016-01-06 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: Extreme Value Modeling and Risk Analysis: Methods and Applications presents a broad overview of statistical modeling of extreme events along with the most recent methodologies and various applications. The book brings together background material and advanced topics, eliminating the need to sort through the massive amount of literature on the subje

Download or read book Extreme Value Methods with Applications to Finance written by Serguei Y. Novak and published by CRC Press. This book was released on 2011-12-20 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: Extreme value theory (EVT) deals with extreme (rare) events, which are sometimes reported as outliers. Certain textbooks encourage readers to remove outliers-in other words, to correct reality if it does not fit the model. Recognizing that any model is only an approximation of reality, statisticians are eager to extract information about unknown di

Download or read book Extreme Value Theory and Copula Theory written by Jia Liu and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Deregulation of the energy market and surging trading activities have made the energy markets even more volatile in recent years. Under such circumstances, it becomes increasingly important to assess the probability of rare and extreme price movement in the risk management of energy futures. Similar to other financial time series, energy futures exhibit time varying volatility and fat tails. An appropriate risk measurement of energy futures should be able to capture these two features of the returns. In the first portion of this dissertation, we use the conditional Extreme Value Theory model to estimate Value-at-Risk (VaR) and Expected Shortfall (ES) for long and short trading positions in the energy markets. The statistical tests on the backtests show that this approach provides a significant improvement over the widely used Normal distribution based VaR and ES models. In the second portion of this dissertation, we extend our analysis from a single security to a portfolio of energy futures. In recent years, commodity futures have gained tremendous popularity as many investors believe they provide much needed diversification to their portfolios. In order to properly account for any diversification benefits, we employ a time-varying conditional bivariate copula approach to model the dependence structure between energy futures. In contrast to previous studies on the same subject, we introduce fundamental supply and demand factors into the copula models to study the dependence structure between energy futures. We find that energy futures are more likely to move together during down markets than up markets. In the third part of this dissertation, we extend our study of bivariate copula models to multivariate copula theory. We employ a pair-copula approach to estimate VaR and ES of a portfolio consisting of energy futures, the S & P 500 index and the US Dollar index. Our empirical results show that although the pair copula approach does not offer any addedadvantage in VaR and ES estimation over a long backtest horizon, it provides much moreaccurate estimates of risk during the period of high co-dependence among assets after the recent financial crisis.

Download or read book Empirical Analysis of Value at Risk and Expected Shortfall in Portfolio Selection Problem written by Liyuan Ding and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Safety first criterion and mean-shortfall criterion both explore cases of assets allocation with downside risk. In this paper, I compare safety first portfolio selection problem and mean-shortfall portfolio optimization problem, considering risk averse investors in practice. Safety first portfolio selection uses Value at Risk (VaR) as a risk measure, and mean-shortfall portfolio optimization uses expected shortfall as a risk measure, respectively. VaR is estimated by implementing extreme theory using a semi-parametric method. Expected shortfall is estimated by two nonparametric methods: a natural estimation and a kernel-weighted estimation. I use daily data on three international stock indices, ranging from January 1986 to February 2012, to provide empirical evidence in asset allocations and illustrate the performances of safety first and mean-shortfall with their risk measures. Also, the historical data has been divided in two ways. One is truncated at year 1998 and explored the performance during tech boom and financial crisis. the mean-shortfall portfolio optimization with the kernel-weighted method performed better than the safety first criterion, while the safety first criterion was better than the mean-shortfall portfolio optimization with the natural estimation method. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/148430

Download or read book Nonparametric Estimation of Conditional Value at risk and Expected Shortfall Based on Extreme Value Theory written by Carlos Martins-Filho and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Extreme Values and Financial Risk written by Saralees Nadarajah and published by MDPI. This book was released on 2019-01-15 with total page 115 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "Extreme Values and Financial Risk" that was published in JRFM

Download or read book On extreme value statistics written by Chen Zhou and published by Rozenberg Publishers. This book was released on 2008 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the 18th century, statisticians sometimes worked as consultants to gamblers. In order to answer questions like "If a fair coin is flipped 100 times, what is the probability of getting 60 or more heads?", Abraham de Moivre discovered the so-called "normal curve". Independently, Pierre-Simon Laplace derived the central limit theorem, where the normal distribution acts as the limit for the distribution of the sample mean. Nowadays, statisticians sometimes work as consultants for economists, to whom the normal distribution is far from a satisfactory model. For example, one may need to model large-impact financial events in order to to answer questions like "What is the probability of getting into a crisis period similar to the credit squeeze in 2007 in the coming 10 years?". At first glance, estimating the chances of events that rarely happen or even have never happened before sounds like a "mission impossible". The development of Extreme Value Theory (EVT) shows that it is in fact possible to achieve this goal. Different from the central limit theorem, Extreme Value Theory starts from the limit distribution of the sample maximum. Initiated by M. Frechet, R. Fisher and R. von Mises, the limit theory completed by B. Gnedenko, gave the fundamental assumption in EVT, the "extreme value condition". Statistically, the extreme value condition provides a semi-parametric model for the tails of distribution functions. Therefore it can be applied to evaluate the rare events. On the other hand, since the assumption is rather general and natural, the semi-parametric model can have extensive applications in numerous felds.

Download or read book The New Hybrid Value at Risk Approach Based on the Extreme Value Theory written by Nikola Radivojevic and published by . This book was released on 2016 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper the authors introduce a new hybrid approach based on the Extreme Value Theory (EVT) to joint estimation of Value at Risk (VaR) and Expected Shortfall (ES) for high quantiles of return distributions. The approach is suitable for measuring market risk in the emerging markets. It is designed to capture the empirical features of returns with emerging markets, such as leptokurtosis, asymmetry, autocorrelation and heteroscedasticity.

Download or read book Portfolio Risk Estimation and Diversification Based on Time varying Copulae written by Sachin Kuruvithadam and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In the present thesis, we review and reassess the use of dynamic copulae as a tool to forecast value-at-risk (VaR) and expected shortfall (ES) of an equally-weighted portfolio consisting of sector-based funds. Moreover, we evaluate the potential of sectorial diversification based on the conditional diversification benefit (CDB), a measure developed by Christoffersen et al. (2012). To this purpose, nine sector-based S & P depositary receipt exchange-traded funds (SPDR ETFs) are selected. The sample period is split into two equally long subperiods for parameter estimation and backtesting. Log returns are filtered by GJR-GARCH and the fitted standardized residuals modeled by means of the empirical distribution function for the interior part and a generalized Pareto distribution (GPD) for the tails. Dependence is established by introducing dynamic Gaussian and t copula structures between standardized residuals. After estimating the copula parameters, one-day ahead copula realizations are simulated, converted into log returns through the GJR-GARCH-GPD specification, and finally aggregated into portfolio returns. VaR and ES are then estimated and compared to the ex-post realized returns via backtesting techniques. The obtained ES estimates are also used to measure CDB. The results prove that, although dynamic copulae allow the incorporation of recent news and therefore increasing or decreasing intensity of comovements, VaR underestimation is still significant during the financial crisis, especially at extremely high confidence levels, whereas VaR estimates accurately reflect the risk of the portfolio during relatively stable periods at all confidence levels. On the contrary, ES estimation is validated by backtesting techniques at high confidence levels in all periods. Furthermore, we show that CDB oscillates conditional on the swings of the market, but appears to remain constant over the long term.

Download or read book Problems of Value At Risk A Critical View written by Alexander Melichar and published by GRIN Verlag. This book was released on 2010-11-26 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt: Seminar paper from the year 2009 in the subject Business economics - Controlling, grade: 1,5, University of Innsbruck (Institut für Banken und Finanzen), course: Seminar SBWL Risk Management, language: English, abstract: This seminar paper is divided in the following chapters: 1. Definition of Value at Risk: What is VaR, several definitions of this figure. 2. The three common approaches for calculating Value at Risk: Historical simulation, Monte Carlo simulation, Variance-Covariance model. 3. The critical view: Problems and limitations of Value at Risk. Which approach can be meaningfully used and when not? Why is Value at Risk not the “only truth” in financial institutions? What are the strengths and weaknesses of the several approaches in calculating Value at Risk?

Download or read book Extreme Value Theory and Applications written by J. Galambos and published by Springer Science & Business Media. This book was released on 2013-12-01 with total page 526 pages. Available in PDF, EPUB and Kindle. Book excerpt: It appears that we live in an age of disasters: the mighty Missis sippi and Missouri flood millions of acres, earthquakes hit Tokyo and California, airplanes crash due to mechanical failure and the seemingly ever increasing wind speeds make the storms more and more frightening. While all these may seem to be unexpected phenomena to the man on the street, they are actually happening according to well defined rules of science known as extreme value theory. We know that records must be broken in the future, so if a flood design is based on the worst case of the past then we are not really prepared against floods. Materials will fail due to fatigue, so if the body of an aircraft looks fine to the naked eye, it might still suddenly fail if the aircraft has been in operation over an extended period of time. Our theory has by now penetrated the so cial sciences, the medical profession, economics and even astronomy. We believe that our field has come of age. In or~er to fully utilize the great progress in the theory of extremes and its ever increasing acceptance in practice, an international conference was organized in which equal weight was given to theory and practice. This book is Volume I of the Proceedings of this conference. In selecting the papers for Volume lour guide was to have authoritative works with a large variety of coverage of both theory and practice.

Download or read book A Copula and Extreme Value Based Methodology for Estimating the Required Economic Capital in a Retail Credit Portfolio written by Adan Diaz Hernandez and published by . This book was released on 2010 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper poses a new methodology to estimate the required economic capital for a retail-credit portfolio. The methodology is based on both the general copula concepts and some core results from the extreme value theory (EVT). The main results support the fact that the proposed methodology is more flexible than other traditional techniques, in particular when it makes use of elliptical generalized or grouped t Student copulas to model the dependence structure of risk-parameters or when it includes elements of the EVT to analyze the extreme losses behavior of a retail-credit portfolio. When applying algorithms, the paper includes data from a Mexican bank.

Download or read book Analyzing Value at Risk and Expected Shortfall Methods written by Xinxin Huang and published by . This book was released on 2014 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Value at Risk (VaR) and Expected Shortfall (ES) are methods often used to measure market risk. Inaccurate and unreliable Value at Risk and Expected Shortfall models can lead to underestimation of the market risk that a firm or financial institution is exposed to, and therefore may jeopardize the well-being or survival of the firm or financial institution during adverse markets. The objective of this study is therefore to examine various Value at Risk and Expected Shortfall models, including fatter tail models, in order to analyze the accuracy and reliability of these models. Thirteen VaR and ES models under three main approaches (Parametric, Non-Parametric and Semi-Parametric) are examined in this study. The results of this study show that the proposed model (ARMA(1,1)-GJR-GARCH(1,1)-SGED) gives the most balanced Value at Risk results. The semi-parametric model (Extreme Value Theory, EVT) is the most accurate Value at Risk model in this study for S&P 500.

Download or read book Backtesting Extreme Value Theory Models of Expected Shortfall written by Alfonso Novales Cinca and published by . This book was released on 2017 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt: We use stock market data to analyze the quality of alternative models and procedures to estimate Expected Shortfall (ES) at different significance levels. We consider conditional models applied to the full distribution of returns as well as models that focus on tail events using extreme value theory (EVT) under the two-step procedure proposed by McNeil&Frey (2000). The performance of the different models is assessed using a variety of ES backtests recently proposed in the literature. Our results suggest that conditional EVT-based models produce more accurate 1- and 10-day ES forecasts than non-EVT based models. Under either approach, asymmetric probability distributions for return innovations are clearly more appropriate. These qualitative results are also valid for the recent crisis period, even though all models then undervalue the level of risk. Filtered Historic Simulation narrows the range of numerical forecasts obtained from alternative models, thereby reducing model risk. Combining EVT and FHS seems to be the best approach to obtain accurate ES forecasts.

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...