Un modelo multivariado para el seguimiento de la integración de las TIC en la educación : ONTEV.

Estudio de muestras entre los años 2001 y 2003 para 1) Conocer y valorar los cambios producidos en las infraestructuras disponibles en relación con las TIC y específicamente en cuanto a la ratio de alumnos por ordenador y por ordenador conectado. 2) Conocer y valorar las posibles diferencias producidas en el uso que se hace de Internet por parte de los profesores en el centro y en el aula, y por parte de los alumnos, en el centro y fuera del mismo, desde las perspectivas univariada y multivariada. 3) Valorar los cambios producidos en las actitudes de los profesores y alumnos con respecto al uso de Internet en la escuela, desde las perspectivas univariada y multivariada. 4) Determinar el grado de diferencias producidas en conocimiento y destreza de los profesores y de los alumnos en el manejo de Internet, en fuentes de formación desde la perspectiva univariada y multivariada. 5) Delimitar hasta qué punto ha aumentado en los colectivos implicados, la percepción de que Internet mejora la calidad de la educación, desde las perspectivas univariada y multivariada. 6) Precisar las alternativas y sugerencias.

American option valuation: implied calibration of GARCH pricing models

This study analyzes the issue of American option valuation when the underlying exhibits a GARCH-type volatility process. We propose the usage of Rubinstein's Edgeworth binomial tree (EBT) in contrast to simulation-based methods being considered in previous studies. The EBT-based valuation approach makes an implied calibration of the pricing model feasible. By empirically analyzing the pricing performance of American index and equity options, we illustrate the superiority of the proposed approach.

A note on estimating market–based minimum capital risk requirements: a multivariate GARCH approach

Internal risk management models of the kind popularized by J. P. Morgan are now used widely by the world’s most sophisticated financial institutions as a means of measuring risk. Using the returns on three of the most popular futures contracts on the London International Financial Futures Exchange, in this paper we investigate the possibility of using multivariate generalized autoregressive conditional heteroscedasticity (GARCH) models for the calculation of minimum capital risk requirements (MCRRs). We propose a method for the estimation of the value at risk of a portfolio based on a multivariate GARCH model. We find that the consideration of the correlation between the contracts can lead to more accurate, and therefore more appropriate, MCRRs compared with the values obtained from a univariate approach to the problem.

Testing for a unit root in a process exhibiting a structural break in the presence of GARCH errors

This paper considers the effect of GARCH errors on the tests proposed byPerron (1997) for a unit root in the presence of a structural break. We assessthe impact of degeneracy and integratedness of the conditional varianceindividually and find that, apart from in the limit, the testing procedure isinsensitive to the degree of degeneracy but does exhibit an increasingover-sizing as the process becomes more integrated. When we consider the GARCHspecifications that we are likely to encounter in empirical research, we findthat the Perron tests are reasonably robust to the presence of GARCH and donot suffer from severe over-or under-rejection of a correct null hypothesis.

Forecasting VaR using analytic higher moments for GARCH processes

It is widely accepted that some of the most accurate Value-at-Risk (VaR) estimates are based on an appropriately specified GARCH process. But when the forecast horizon is greater than the frequency of the GARCH model, such predictions have typically required time-consuming simulations of the aggregated returns distributions. This paper shows that fast, quasi-analytic GARCH VaR calculations can be based on new formulae for the first four moments of aggregated GARCH returns. Our extensive empirical study compares the Cornish–Fisher expansion with the Johnson SU distribution for fitting distributions to analytic moments of normal and Student t, symmetric and asymmetric (GJR) GARCH processes to returns data on different financial assets, for the purpose of deriving accurate GARCH VaR forecasts over multiple horizons and significance levels.

Benchmarks and the accuracy of GARCH model estimation

This paper reviews nine software packages with particular reference to their GARCH model estimation accuracy when judged against a respected benchmark. We consider the numerical consistency of GARCH and EGARCH estimation and forecasting. Our results have a number of implications for published research and future software development. Finally, we argue that the establishment of benchmarks for other standard non-linear models is long overdue.

A Double-threshold GARCH Model for the French Franc/Deutschmark exchange rate

This paper combines and generalizes a number of recent time series models of daily exchange rate series by using a SETAR model which also allows the variance equation of a GARCH specification for the error terms to be drawn from more than one regime. An application of the model to the French Franc/Deutschmark exchange rate demonstrates that out-of-sample forecasts for the exchange rate volatility are also improved when the restriction that the data it is drawn from a single regime is removed. This result highlights the importance of considering both types of regime shift (i.e. thresholds in variance as well as in mean) when analysing financial time series.

The effect of (mis-specified) GARCH filters on the finite sample distribution of the BDS test

This paper considers the effect of using a GARCH filter on the properties of the BDS test statistic as well as a number of other issues relating to the application of the test. It is found that, for certain values of the user-adjustable parameters, the finite sample distribution of the test is far-removed from asymptotic normality. In particular, when data generated from some completely different model class are filtered through a GARCH model, the frequency of rejection of iid falls, often substantially. The implication of this result is that it might be inappropriate to use non-rejection of iid of the standardised residuals of a GARCH model as evidence that the GARCH model ‘fits’ the data.

The influence of ARIMA-GARCH parameters in feed forward neural networks prediction

The objective of this article is to find out the influence of the parameters of the ARIMA-GARCH models in the prediction of artificial neural networks (ANN) of the feed forward type, trained with the Levenberg-Marquardt algorithm, through Monte Carlo simulations. The paper presents a study of the relationship between ANN performance and ARIMA-GARCH model parameters, i.e. the fact that depending on the stationarity and other parameters of the time series, the ANN structure should be selected differently. Neural networks have been widely used to predict time series and their capacity for dealing with non-linearities is a normally outstanding advantage. However, the values of the parameters of the models of generalized autoregressive conditional heteroscedasticity have an influence on ANN prediction performance. The combination of the values of the GARCH parameters with the ARIMA autoregressive terms also implies in ANN performance variation. Combining the parameters of the ARIMA-GARCH models and changing the ANN`s topologies, we used the Theil inequality coefficient to measure the prediction of the feed forward ANN.

Método para controle estatístico multivariado de processos em batelada

As cartas de controle estatístico têm sido amplamente utilizadas no monitoramento do desempenho de processos. Com a crescente informatização dos processos industriais, tem-se verificado um aumento sensível na quantidade de informações disponíveis sobre variáveis de processo. Via de regra, essas variáveis apresentam-se fortemente correlacionadas. Em casos especiais, como nos processos em batelada, tais variáveis descrevem um perfil de variação ao longo do tempo, caracterizando o comportamento normal do processo. Nessas condições especiais, as cartas de controle tradicionais não proporcionam um monitoramento eficaz sobre o processo. Esta dissertação de mestrado apresenta uma alternativa para o monitoramento on line de processos em bateladas: a proposição de uma metodologia para implantação de cartas de controle multivariadas baseadas em componentes principais. A idéia central dessas cartas é monitorar simultaneamente diversas variáveis, controlando somente algumas poucas combinações lineares independentes delas; tais combinações são denominadas componentes principais. O presente trabalho ilustra a metodologia proposta em um estudo de caso realizado na etapa de fermentação do processo de fabricação de cerveja de uma indústria de bebidas, localizada na região metropolitana de Porto Alegre.