LongMemory, Count Data, Time Series Modelling for Financial Application
AbstractA 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.
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Bibliographic InfoPaper provided by Umeå University, Department of Economics in its series Umeå Economic Studies with number 673.
Length: 19 pages
Date of creation: 11 Apr 2006
Date of revision:
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Postal: Department of Economics, Umeå University, S-901 87 Umeå, Sweden
Phone: 090 - 786 61 42
Fax: 090 - 77 23 02
Web page: http://www.econ.umu.se/
More information through EDIRC
Intra-day; High frequency; Estimation; Fractional integration; Reaction time;
Find related papers by JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing
- G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies
This paper has been announced in the following NEP Reports:
- NEP-ALL-2006-04-22 (All new papers)
- NEP-ECM-2006-04-22 (Econometrics)
- NEP-ETS-2006-04-22 (Econometric Time Series)
- NEP-FIN-2006-04-22 (Finance)
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