Results 1 - 7 of 7

Filtering with heavy tails

by Filtering Heavy Tails, Andrew Harvey, Ra Luati, Andrew Harvey, Alessandra Luati , 2012
"... An unobserved components model in which the signal is buried in noise that is non-Gaussian may throw up observations that, when judged by the Gaussian yardstick, are outliers. We describe an ob-servation driven model, based on a conditional Student t-distribution, that is tractable and retains some ..."
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An unobserved components model in which the signal is buried in noise that is non-Gaussian may throw up observations that, when judged by the Gaussian yardstick, are outliers. We describe an ob-servation driven model, based on a conditional Student t-distribution, that is tractable and retains some of the desirable features of the lin-ear Gaussian model. Letting the dynamics be driven by the score of the conditional distribution leads to a speci…cation that is not only easy to implement, but which also facilitates the development of a comprehensive and relatively straightforward theory for the asymp-totic distribution of the ML estimator. The methods are illustrated with an application to rail travel in the UK. The …nal part of the article shows how the model may be extended to include explanatory variables.

Time series models with an EGB2 conditional distribution, Cambridge Working paper

by Michele Caivano, Andrew Harvey, Michele Caivano, Andrew Harvey, Michele Caivano, Andrew Harvey - in Economics, CWPE 1325 , 2013
"... Time series models with an EGB2 conditional distribution ..."
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Time series models with an EGB2 conditional distribution

and Applications

by Dong Hwan Oh, Andrew J. Patton, Tim Bollerslev, George Tauchen, Shakeeb Khan, Dong Hwan Oh, Andrew J. Patton, Tim Bollerslev, George Tauchen, Shakeeb Khan , 2014
"... The dissertation consists of four chapters that concern topics on copulas for high dimensions. Chapter 1 proposes a new general model for high dimension joint distri-butions of asset returns that utilizes high frequency data and copulas. The depen-dence between returns is decomposed into linear and ..."
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The dissertation consists of four chapters that concern topics on copulas for high dimensions. Chapter 1 proposes a new general model for high dimension joint distri-butions of asset returns that utilizes high frequency data and copulas. The depen-dence between returns is decomposed into linear and nonlinear components, which enables the use of high frequency data to accurately measure and forecast linear dependence, and the use of a new class of copulas designed to capture nonlinear de-pendence among the resulting linearly uncorrelated residuals. Estimation of the new class of copulas is conducted using a composite likelihood, making the model feasible even for hundreds of variables. A realistic simulation study verifies that multistage estimation with composite likelihood results in small loss in efficiency and large gain in computation speed. Chapter 2, which is co-authored with Professor Andrew Patton, presents new models for the dependence structure, or copula, of economic variables based on a factor structure. The proposed models are particularly attractive for high dimen-

Working Papers / Documents de travail Energy Markets and CO2 Emissions: Analysis by Stochastic Copula Autoregressive Model Energy Markets and CO 2 emissions: analysis by stochastic copula autoregressive model

by Vêlayoudom Marimoutou , Manel Soury , Vêlayoudom Marimoutou , Manel Soury
"... Abstract We examine the dependence between the volatility of the prices of the carbon dioxide "CO 2 " emissions with the volatility of one of their fundamental components, the energy prices. The dependence between the returns will be approached by a particular class of copula, the Stochas ..."
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Abstract We examine the dependence between the volatility of the prices of the carbon dioxide "CO 2 " emissions with the volatility of one of their fundamental components, the energy prices. The dependence between the returns will be approached by a particular class of copula, the Stochastic Autoregressive Copulas (SCAR), which is a time varying copula that was first introduced by Hafner and Manner (2012) The main result suggests that the dynamics of the dependence between the volatility of the CO 2 emission prices and the volatility of energy returns, coal, natural gas and Brent oil prices, do vary over time, although not much in stable periods but rise noticeably during the period of crisis and turmoils.
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Chapter 1.

by Andrew Harvey , 2012
"... The aim of this monograph is to set out a uni…ed and comprehensive theory for a class of nonlinear time series models that can deal with distributions that change over time. The emphasis is models in which the conditional distribution of an observation may be heavy-tailed and the location and/or ..."
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The aim of this monograph is to set out a uni…ed and comprehensive theory for a class of nonlinear time series models that can deal with distributions that change over time. The emphasis is models in which the conditional distribution of an observation may be heavy-tailed and the location and/or

Can we still benefit from international diversification? The case of the Czech and German stock marketsI

by Krenar Avdulaja, Jozef Barunika
"... One of the findings of the recent literature is that the 2008 financial crisis caused reduction in international diversification benefits. To fully understand the possible potential from diversification, we build an empirical model which combines gener-alised autoregressive score copula functions wi ..."
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One of the findings of the recent literature is that the 2008 financial crisis caused reduction in international diversification benefits. To fully understand the possible potential from diversification, we build an empirical model which combines gener-alised autoregressive score copula functions with high frequency data, and allows us to capture and forecast the conditional time-varying joint distribution of stock returns. Using this novel methodology and fresh data covering five years after the crisis, we compute the conditional diversification benefits to answer the question, whether it is still interesting for an international investor to diversify. As diversifi-cation tools, we consider the Czech PX and the German DAX broad stock indices, and we find that the diversification benefits strongly vary over the 2008–2013 crisis years.

Are benefits from oil – stocks diversification gone? A new evidence from a dynamic copulas and high frequency dataI

by Krenar Avdulaja, Jozef Barunika
"... Oil is widely perceived as a good diversification tool for stock markets. To fully understand the potential, we propose a new empirical methodology which combines generalized autoregressive score copula functions with high frequency data, and al-lows us to capture and forecast the conditional time-v ..."
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Oil is widely perceived as a good diversification tool for stock markets. To fully understand the potential, we propose a new empirical methodology which combines generalized autoregressive score copula functions with high frequency data, and al-lows us to capture and forecast the conditional time-varying joint distribution of the oil – stocks pair accurately. Our realized GARCH with time-varying copula yields statistically better forecasts of the dependence as well as quantiles of the distri-bution when compared to competing models. Using recently proposed conditional diversification benefits measure which take into account higher-order moments and nonlinear dependence, we document reducing benefits from diversification over the past ten years. Diversification benefits implied by our empirical model are moreover strongly varying over time. These findings have important implications for portfolio management.