In this paper we give the theoretical basis of a possible explanation for two stylized facts observed in long log-return series: the long range dependence (LRD) in volatility and the integrated GARCH (IGARCH). Both these effects can be theoretically explained if one assumes that the data is...

This paper investigates the relevance of the stationary, conditional, parametric ARCH modeling paradigm as embodied by the GARCH(1,1) process to describing and forecasting the dynamics of returns of the Standard & Poors 500 (S&P 500) stock market index. A detailed analysis of the series of S&P...

The paper investigates from an empirical perspective aspects related to the occurrence of the IGARCH effect and to its impact on volatility forecasting. It reports the results of a detailed analysis of twelve samples of returns on financial indexes from major economies (Australia, Austria,...

In this paper we propose a goodness of fit test that checks the resemblance of the spectral density of a GARCH process to that of the log-returns. The asymptotic behavior of the test statistics are given by a functional central limit theorem for the integrated periodogram of the data. A...

The paper outlines a methodology for analyzing daily stock returns that relinquishes the assumption of global stationarity. Giving up this common working hypothesis reflects our belief that fundamental features of the financial markets are continuously and significantly changing. Our approach...

This paper studies the integrated Garch (IGARCH) e®ect, a phenomenon often encountered when estimating conditional auto-regressive models on ¯nancial time series. The analysis of twelve indexes of major ¯nancial markets provides empirical evidence of its well-spread presence especially in...

We examine the impact of sustainability criteria, as measured by the KLD scores, on optimal portfolio selection performed on an investment universe containing the equities in the S&P500 index and covering the period between 1993 and 2008. The optimizations are done according to the Markowitz...

We examine the impact of including sustainability related constraints on optimal portfolio selection. Our analysis covers an investment set containing the components of the S&P500 index from 1993 to 2008. The optimizations are performed according to the classical mean-variance approach while...

The paper develops a non-parametric, non-stationary framework for business-cycle dating based on an innovative statistical methodology known as Adaptive Weights Smoothing (AWS). The methodology is used both for the study of the individual macroeconomic time series relevant to the dating of the...

Our study supports the hypothesis of global non-stationarity of the return time series. We bring forth both theoretical and empirical evidence that the long range dependence (LRD) type behavior of the sample ACF and the periodogram of absolute return series and the IGARCH effect documented in...