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LongMemory, Count Data, Time Series Modelling for Financial Application

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  • Quoreshi, Shahiduzzaman

    ()
    (Department of Economics, Umeå University)

Abstract

A 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 Info

Paper provided by Umeå University, Department of Economics in its series Umeå Economic Studies with number 673.

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Length: 19 pages
Date of creation: 11 Apr 2006
Date of revision:
Handle: RePEc:hhs:umnees:0673

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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
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Web page: http://www.econ.umu.se/
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Keywords: Intra-day; High frequency; Estimation; Fractional integration; Reaction time;

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References

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  1. Bhardwaj, Geetesh & Swanson, Norman R., 2006. "An empirical investigation of the usefulness of ARFIMA models for predicting macroeconomic and financial time series," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 539-578.
  2. Quoreshi, Shahiduzzaman, 2005. "Bivariate Time Series Modelling of Financial Count Data," UmeÃ¥ Economic Studies 655, Umeå University, Department of Economics.
  3. Lo, Andrew W. (Andrew Wen-Chuan), 1989. "Long-term memory in stock market prices," Working papers 3014-89., Massachusetts Institute of Technology (MIT), Sloan School of Management.
  4. Granger, Clive W. J. & Ding, Zhuanxin, 1996. "Varieties of long memory models," Journal of Econometrics, Elsevier, vol. 73(1), pages 61-77, July.
  5. Baillie, Richard T., 1996. "Long memory processes and fractional integration in econometrics," Journal of Econometrics, Elsevier, vol. 73(1), pages 5-59, July.
  6. Granger, C. W. J., 1980. "Long memory relationships and the aggregation of dynamic models," Journal of Econometrics, Elsevier, vol. 14(2), pages 227-238, October.
  7. Kurt Brannas & A. M. M. Shahiduzzaman Quoreshi, 2010. "Integer-valued moving average modelling of the number of transactions in stocks," Applied Financial Economics, Taylor & Francis Journals, vol. 20(18), pages 1429-1440.
  8. Francis X. Diebold, 1988. "Random walks versus fractional integration: power comparisons of scalar and joint tests of the variance-time function," Finance and Economics Discussion Series 41, Board of Governors of the Federal Reserve System (U.S.).
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Citations

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Cited by:
  1. Quoreshi, A.M.M. Shahiduzzaman, 2008. "A vector integer-valued moving average model for high frequency financial count data," Economics Letters, Elsevier, vol. 101(3), pages 258-261, December.
  2. Quoreshi, A.M.M. Shahiduzzaman, 2014. "Bivariate Integer-Valued Long Memory Model for High Frequency Financial Count Data," CITR Working Paper Series 2014/03, Center for Innovation and Technology Research, Blekinge Institute of Technology.

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