Bivariate Integer-Valued Long Memory Model for High Frequency Financial Count Data
AbstractWe develop a model to account for the long memory property in a bivariate count data framework. We propose a bivariate integer-valued fractional integrated (BINFIMA) model and apply the model to high frequency stock transaction data. The BINFIMA model allows for both positive and negative correlations between the counts. The unconditional and conditional first and second order moments are given. The CLS and FGLS estimators are discussed. The model is capable of capturing the covariance between and within intra-day time series of high frequency transaction data due to macroeconomic news and news related to a specific stock. Empirically, it is found that Ericsson B has mean recursive process while AstraZeneca has long memory property. It is also found that Ericsson B and AstraZenica react in a similar way due to macroeconomic news.
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Bibliographic InfoPaper provided by Center for Innovation and Technology Research, Blekinge Institute of Technology in its series CITR Working Paper Series with number 2014/03.
Length: 11 pages
Date of creation: 02 Apr 2014
Date of revision:
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Postal: CITR (Center for Innovation and Technology Research), Department of Industrial Economics, Blekinge Inst of Technology, 371 79 Karlskrona, Sweden
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More information through EDIRC
Count data; Intra-day; Time series; Estimation; Reaction time; Finance;
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 &bull Diffusion Processes
- 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; Trading Volume; Bond Interest Rates
- G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
This paper has been announced in the following NEP Reports:
- NEP-ALL-2014-04-11 (All new papers)
- NEP-ECM-2014-04-11 (Econometrics)
- NEP-ETS-2014-04-11 (Econometric Time Series)
- NEP-GER-2014-04-11 (German Papers)
- NEP-MST-2014-04-11 (Market Microstructure)
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