Add to ORKGA model to account for the long memory property in a count data framework is proposed and applied to high frequency stock transactions data. The unconditional and conditional first and second order moments are given. The CLS and FGLS estimators are discussed. In its empirical application to two stock series for AstraZeneca and Ericsson B, we find that both series have a fractional integration property.Intra-day; High frequency; Estimation; Fractional integration; Reaction time
This paper considers a flexible class of time series models generated by Gegenbauer polynomials inco...
In this work we propose a new class of long-memory models with time-varying fractional parameter. In...
In this paper we fit the main features of financial returns by means of a two factor long memory sto...
This thesis comprises four papers concerning modelling of financial count data. Paper [1], [2] and [...
This paper analyses the long-memory properties of high frequency financial time series. It focuses o...
This paper analyses the long-memory properties of high frequency financial time series. It focuses o...
This paper provides a survey and review of the major econometric work on long memory processes, frac...
This paper proposes a general time series framework to capture the long-run behaviour of financial s...
International audienceThis paper generalizes the standard long memory modeling by assuming that the ...
Financial processes may possess long memory and their probability densities may display heavy tails....
This paper generalizes the standard long memory modeling by assuming that the long memory parameter ...
We develop a new simultaneous time series model for volatility and dependence in daily financial ret...
This paper introduces Quasi-Maximum Likelihood Estimation for Long Memory Stock Transaction Data of ...
Abstract: It is now recognized that long memory and structural change can easily be confused because...
This paper investigates persistence in financial time series at three different frequencies (daily,...
This paper considers a flexible class of time series models generated by Gegenbauer polynomials inco...
In this work we propose a new class of long-memory models with time-varying fractional parameter. In...
In this paper we fit the main features of financial returns by means of a two factor long memory sto...
This thesis comprises four papers concerning modelling of financial count data. Paper [1], [2] and [...
This paper analyses the long-memory properties of high frequency financial time series. It focuses o...
This paper analyses the long-memory properties of high frequency financial time series. It focuses o...
This paper provides a survey and review of the major econometric work on long memory processes, frac...
This paper proposes a general time series framework to capture the long-run behaviour of financial s...
International audienceThis paper generalizes the standard long memory modeling by assuming that the ...
Financial processes may possess long memory and their probability densities may display heavy tails....
This paper generalizes the standard long memory modeling by assuming that the long memory parameter ...
We develop a new simultaneous time series model for volatility and dependence in daily financial ret...
This paper introduces Quasi-Maximum Likelihood Estimation for Long Memory Stock Transaction Data of ...
Abstract: It is now recognized that long memory and structural change can easily be confused because...
This paper investigates persistence in financial time series at three different frequencies (daily,...
This paper considers a flexible class of time series models generated by Gegenbauer polynomials inco...
In this work we propose a new class of long-memory models with time-varying fractional parameter. In...
In this paper we fit the main features of financial returns by means of a two factor long memory sto...