Download or read book Extreme value theory a conditional approach for value at risk estimation in the brazilian stock market written by and published by . This book was released on 2000 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Um dos fatos estilizados mais pronunciados acerca das distribuições de retornos financeiros diz respeito à presença de caudas pesadas. Isso torna os modelos paramétricos tradicionais de cálculo de Valor em Risco (VaR) inadequados para a estimação de VaR de baixas probabilidades (1% ou menos), dado que estes se baseiam na hipótese de normalidade para as distribuições dos retornos. Tais modelos não são capazes de inferir sobre as reais possibilidades de ocorrência de retornos atípicos. Sendo assim, o objetivo do presente trabalho é investigar o desempenho de modelos baseados na Teoria dos Valores Extremos para o cálculo de VaR, comparando-os com modelostradicionais. Um modelo incondicional, proposto a caracterizar o comportamento de longo prazo da série, e um modelo condicional, sugerido por McNeil e Frey(1999), proposto a caracterizar a dependência presente na variância condicional dos retornos foram utilizados e testados em quatro séries de retornos de ações representativas do mercado brasileiro: retornos de Ibovespa, retornos deIbovespa Futuro, retornos das ações da Telesp e retornos das ações da Petrobrás. Os resultados indicam que os modelos baseados na Teoria dos Valores Extremos são mais adequados para a modelagem das caudas, e conseqüentemente para a estimação de Valor em Risco quando os níveisde probabilidade de interesse são baixos. Além disso, o modelo condicional é mais adequado em épocas de crise, pois, ao contrário do modelo incondicional, tem a capacidade de responder rapidamente a mudanças na volatilidade. Medidas alternativas de risco, como a perda média e a perda mediana também foram propostas, a fim de fornecer estimativas para as perdas no caso do VaR ser violado.
Download or read book Empirical Tests of Parametric and Non parametric Value at Risk VaR and Conditional Value at Risk CVaR Measures for the Brazilian Stock Market Index written by Luciano Martin Rostagno and published by . This book was released on 2005 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt: This study aims to verify empirically the accuracy of parametric and non-parametric approaches in estimating Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR) measures of the Brazilian stock market index (Ibovespa). The period of analysis goes from the first day of trade of 1995 to the last day of trade of 2004, which is used for estimation and test of the risk parameters. Parametric approaches assume that daily returns follow a normal and a t-distribution. Non-parametric approaches are the historical simulation and the volatility-weighted historical simulation technique. The binomial test is applied to verify if the failure rates predicted by VaR measures given by the models are acceptable and the sample differences paired test is used to evaluate the accuracy of the CVaR measures in forecasting tail losses. The results point out that the volatility-weighted historical simulation approach gives better estimates of both measures of risk. The rates of losses exceeding volatility-weighted historical simulation VaRs (VWHS-VaRs) ranged between 4.7-6.0%, at the 95% cl, and between 0.9-1.2%, at the 99% cl. For all periods of estimation used (1, 2, 3, 4, and 5 years), at the 95% cl, the sample differences paired test indicated no statistically significant differences between the VWHS-CVaR estimates and the losses beyond its VaR estimates. Risk lines for the normal and historical simulation VaR (HS-VaR) estimates presented flatness, or excessive smoothness, for large periods of estimation, and the student t VaR (T-VaR) estimates were sometimes too low or too high. For these models, short periods of estimation gave more accurate VaR estimates. For the CVaR estimates, the normal and t-distribution assumptions caused overestimation of the value of the tail losses. Finally, the HS-CVaR had similar performance of HS-VaR providing, at the 95% cl, good estimates of tail losses when short periods of estimation were used.
Download or read book A Comparison of Extreme Value Theory Approaches for Determining Value at Risk written by Chris Brooks and published by . This book was released on 2005 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper compares a number of different extreme value models for determining the value at risk of three LIFFE futures contracts. A semi-nonparametric approach is also proposed where the tail events are modeled using the Generalised Pareto Distribution and normal market conditions are captured by the empirical distribution function. The value at risk estimates from this approach are compared with those of standard nonparametric extreme value tail estimation approaches, with a small sample bias-corrected extreme value approach, and with those calculated from bootstrapping the unconditional density and bootstrapping from a GARCH(1,1) model. The results indicate that for a hold-out sample, the proposed semi-nonparametric extreme value approach yields superior results to other methods, but the small sample tail index technique is also accurate.
Download or read book From Value at Risk to Stress Testing written by François M. Longin and published by . This book was released on 1999 with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 Value Theory for Value at Risk Estimation written by Evdoxia Pliota and published by . This book was released on 2009 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Brazilian stock return series volatility and value at risk written by and published by . This book was released on 2001 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: O objetivo principal do trabalho é o estudo dos resultados obtidos com a aplicação de diferentes modelos para estimar a volatilidade das ações brasileiras. Foram analisadas as séries de retornos diários de seis ações, num período de 1200 dias de pregão. Inicialmente, as séries foram estudadas quanto a suas propriedades estatísticas: estacionariedade, distribuição incondicional e independência. Concluiu-se que as séries são estacionárias na média, mas não houve conclusão quanto à variância, nesta análise inicial. A distribuição dos retornos não é normal, por apresentar leptocurtose. Os retornos mostraram dependência no tempo, linear e, principalmente, não linear. Modelada a dependência linear, foram aplicados dez modelos diferentes para tentar capturar a dependência não linear através da modelagem da volatilidade: os modelos foram avaliados, dentro e fora da amostra, pelos seus resíduos e pelos erros de previsão. Os resultados indicaram que os modelos menos elaborados tendem a representar pior oprocesso gerador dos dados, mas que os modelos pouco parcimoniosos são de difícil estimação e seus resultados não correspondem ao que seria esperado em função de suasofisticação. As volatilidades estimadas pelos dez modelos foram utilizadas para prever valor em risco (VaR), usando-se dois processos para determinar os quantis das distribuições dos resíduos: distribuição empírica e teoria de valores extremos. Os resultados indicaram que os modelos menos elaborados prevêem melhor o VaR. Isto se deve à nãoestacionariedade das séries na variância, que fica evidente ao longo do trabalho.
Download or read book Extreme Value Theory and Value at Risk written by Viviana Fernandez and published by . This book was released on 2008 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Value at Risk (VaR) is a measure of the maximum potential change in value of a portfolio of financial assets with a given probability over a given time horizon. VaR became a key measure of market risk since the Basle Committee stated that banks should be able to cover losses on their trading portfolios over a ten-day horizon, 99 percent of the time. A common practice is to compute VaR by assuming that changes in value of the portfolio are normally distributed, conditional on past information. However, assets returns usually come from fat-tailed distributions. Therefore, computing VaR under the assumption of conditional normality can be an important source of error. We illustrate this point with Chilean and U.S. returns series by resorting to extreme value theory (EVT) and GARCH-type models. In addition, we show that dynamic estimation of empirical quantiles can also give more accurate VaR estimates than quantiles of a standard normal.
Download or read book Fractal Approaches for Modeling Financial Assets and Predicting Crises written by Nekrasova, Inna and published by IGI Global. This book was released on 2018-02-09 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: In an ever-changing economy, market specialists strive to find new ways to evaluate the risks and potential reward of economic ventures. They start by assessing the importance of human reaction during the economic planning process and put together systems to measure financial markets and their longevity. Fractal Approaches for Modeling Financial Assets and Predicting Crises is a critical scholarly resource that examines the fractal structure and long-term memory of the financial markets in order to predict prices of financial assets and financial crises. Featuring coverage on a broad range of topics, such as computational process models, chaos theory, and game theory, this book is geared towards academicians, researchers, and students seeking current research on pricing and predicting financial crises.
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 An Application of Extreme Value Theory in Value at risk Estimation written by Konstantinos Tolikas and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Refining Value at Risk Estimates written by Marius Galabe Sampid and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 Estimation of Value at Risk Using Methods from Extreme Value Theory written by and published by . This book was released on 1999 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Value at risk a comparison of methods to choose the sample fraction in tail index estimation of generalized extreme value distribution written by and published by . This book was released on 2002 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Valor em Risco -VaR- já é parte das ferramentas habituais que um analista financeiro utiliza para estimar o risco de mercado. Na implementação do VaR é necessário que sejaestimados quantis de baixa probabilidade para a distribuição condicional dos retornos dos portfólios. A metodologia tradicional para o cálculo do VaR requer a estimação de um modelo tipo GARCH com distribuição normal. Entretanto, a hipótese de normalidade condicional nem sempre é adequada, principalmente quando se deseja estimar o VaR em períodos atípicos, caracterizados pela ocorrência de eventos extremos. Nesta situações a distribuição condicional deve apresentar excesso de curtose. O uso de distribuições derivadas do Teorema do Valor Extremos -TVE-, conhecidas coletivamente como GEV, associadas aos modelos tipo GARCH, tornou possível o cálculo do VaR nestas situações. Um parâmetro chave nas distribuições da família GEV é o índice de cauda, o qual pode ser estimado através do estimador de Hill. Entretanto este estimador apresenta muita sensibilidade em termos de variância e viés com respeito à fração amostral utilizada na sua estimação. O objetivo principal desta dissertação foi fazer uma comparação entre três métodos de escolha da fração amostral, recentemente sugeridos na literatura: o método bootstrap duplo Danielsson, de Haan, Peng e de Vries 1999, o método threshold Guillou e Hall 2001 e o Hill plot alternativo Drees, de Haan e Resnick 2000. A avaliação dos métodos foi feita através do teste de cobertura condicional de Christoffersen 1998, o qual foi aplicado às séries de retornos dos índices: NASDAQ, NIKKEY, MERVAL e IBOVESPA. Os nossos resultados indicam que os três métodos apresentam aproximadamente o mesmo desempenho, com uma ligeira vantagem dos métodos bootstrap duplo e o threshold sobre o Hill plot alternativo, porque este ultimo tem um componente normativo na determinação do índice de cauda ótimo.
Download or read book Estimating the VAR Value at Risk of Brazilian Stock Portfolios Via GARCH Family Models and Via Monte Carlo Simulation written by Lucas Godeiro and published by . This book was released on 2013 with total page 21 pages. Available in PDF, EPUB and Kindle. Book excerpt: The objective this work is to calculate the VaR of portfolios via GARCH family models with normal and t-student distribution and via Monte Carlo Simulation. We used three portfolios composite with preferential stocks of five Ibovespa companies. The results show that the t distribution adjusts better to data, because the violation ratio of the VaR calculated with t distribution is less than the violation ratio estimated with normal distribution.
Download or read book Estimation of Extreme Value at Risk written by Yanping Yi and published by . This book was released on 2014 with total page 10 pages. Available in PDF, EPUB and Kindle. Book excerpt: We proposed a method to estimate extreme conditional quantiles by combining quantile GARCH model of Xiao and Koenker (2009) and extreme value theory (EVT) approach. We first estimate the latent volatility process using the information of intermediate quantiles. We then apply EVT to the tail observations to obtain a sound estimate of the likelihood of experiencing an extreme event. Quantile autoregression and EVT together improve efficiency in estimation of extreme quantiles, by borrowing information from neighbor quantiles. Monte Carlo simulation indicates that, the proposed method is promising to provide more accurate estimates for VaR of a financial portfolio, where non-Gaussian tail is present.
