Article history: Received 10 May 2013 Received in revised form 2 September 2014 Accepted 2 September 2014 Available online 11 September 2014 The study investigates the relative performance of Value-at-Risk (VaR) models using daily share price index data from six different countries across Asia, Europe and the United States for a period of 10 years from January 01, 2000 toDecember 31, 2009. Them...

We use a discrete time analysis, giving necessary and sufficient conditions for the almost sure convergence of ARCH(1) and GARCH(1,1) discrete time models, to suggest an extension of the (G)ARCH concept to continuous time processes. Our “COGARCH” (continuous time GARCH) model, based on a single background driving Lévy process, is different from, though related to, other continuous time stochast...

We develop univariate regime-switching GARCH (RS-GARCH) models wherein the conditional variance switches in time from one GARCH process to another. The switching is governed by a time-varying probability, specified as a function of past information. We provide sufficient conditions for geometric ergodicity and existence of moments. Because of path dependence, maximum likelihood estimation is no...

Financial series occasionally exhibit large changes. To deal with those events, we assume that the observed return series consists of a conditionally Gaussian ARMA-GARCH (or -GJR) model contaminated by an additive jump component. In this framework, we propose a new test for additive jumps. The test is based on standardised returns, where the first two conditional moments of the non-contaminated...

This paper shows the effects of COVID-19 pandemic on energy markets. We estimate daily volatilities and correlations among commodities relying a mixed-frequency approach that exploits information from number weekly deaths related to in United States. The takes advantage MIxing-Data Sampling (MIDAS) methods. compare our results those obtained by employing two well-known models do not account for...

modeling dependence structure in financial economics is of paramount importance when estimating portfolio’s value at risk, since risk of an asset in addition to its own behavior is also dependent on the behavior of other assets in the portfolio. application of joint distribution copula is one of the methods for incorporation dependence at lower and upper tail of returns’ distribution in financi...

In this paper we use Gaussian Process (GP) regression to propose a novel approach for predicting volatility of financial returns by forecasting the envelopes of the time series. We provide a direct comparison of their performance to traditional approaches such as GARCH. We compare the forecasting power of three approaches: GP regression on the absolute and squared returns; regression on the env...

This paper considers tests for a unit root when the innovations follow a near-integrated GARCH process. We compare the asymptotic properties of the likelihood ratio statistic with that of the leastsquares based Dickey-Fuller statistic. We first use asymptotics where the GARCH variance process is stationary with fixed parameters, and then consider parameter sequences such that the GARCH process ...

This paper focuses on the performance of various GARCH models in terms of their ability of delivering volatility forecasts for stock return data. Volatility forecasts obtained from a variety of mean and variance specifications in GARCH models are compared to a proxy of actual volatility calculated using daily data. In-sample tests suggest that a regression of volatility estimates on actual vola...