We present several estimates of measures of risk amongst the most well-known, using both high and low frequency data. The aim of the article is to show which lower frequency measures can be an acceptable substitute to the high precision measures, when transaction data is unavailable for a long...

In this paper we deal with the problem of non-stationarity encountered in a lot of data sets coming from existence of multiple seasonnalities, jumps, volatility, distorsion, aggregation, etc. We study the problem caused by these non stationarities on the estimation of the sample autocorrelation...

This paper presents a 2-regime SETAR model with different long-memory processes in both regimes. We briefly present the memory properties of this model and propose an estimation method. Such a process is applied to the absolute and squared returns of five stock indices. A comparison with simple...

This paper presents a 2-regime SETAR model with a long-memory process in the first regime and a short-memory process in the second regime. We briefly introduce the properties of this model and methods for locating the threshold parameter are proposed. Such a process is applied to stock indices...

In this paper we discuss different aspects of long memory behaviorand applicable parametric models. We discuss the confusion thatcan arise when the empirical autocorrelation function decreasesin an hyperbolic way.

This paper presents a 2-regime SETAR model for the volatility with a long-memory process in the first regime and a short-memory process in the second regime. Persistence properties are studied and estimation methods are proposed. Such a process is applied to stock indices and individual asset...

This paper generalizes the standard long memory modeling by assuming that the long memory parameter d is stochastic and time varying: we introduce a STAR process on this parameter characterized by a logistic function. We propose an estimation method of this model. Some simulation experiments are...

This paper presents a 2-regime SETAR model with different longmemory processes in both regimes. We briefly present the memory properties of this model and propose an estimation method. Such a process is applied to the absolute and squared returns of five stock indices. A comparison with simple...

This paper proposes a new fractional model with a time-varying long-memory parameter. The latter evolves nonlinearly according to a transition variable through a logistic function. We present a LR-based test that allows to discriminate between the standard fractional model and our model. We...

In this paper we use a bivariate, fractionally integrated, autoregressive, moving average model of money and real output to extend Fisher and Seater (1993) long-run neutrality requirements to long-memory processes. We derive new restrictions on the order of the nominal and real variable and...