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Impact of High-Frequency Trading on the Stock Returns of Large and Small Companies in the Tehran Stock Exchange

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  • Ahmad Sarlak
  • Zahra Talei

Abstract

The main objective of this study is to evaluate the effect of high-frequency trading on stock returns of the Exchange market in Tehran Stock Exchange. The research methodology in this study is in terms of the purpose, functional and in terms of the method of data collection, descriptive and in terms of the type, solidarity. Statistical society of this research is all companies in the Tehran Stock Exchange which in the past two years had been active in the stock market. In this study, companies are divided into two categories: large and small companies. Large companies that their assets logarithm is greater than the average total sample and small companies that their assets logarithm is less than the average total sample. To collect information has been used from the financial statements of accepted companies in Tehran Stock Exchange. MATLAB software has been used for data analysis. Used tests in this study are include (DF) Dickey-Fuller test, (ADF) Generalized Dickey-Fuller test, Phillips-Perron test, and time series methods. The results of this study show that the dynamics of stock returns of the Tehran Stock Exchange are non-linear functions and high Frequency trading of the large companies affect the turnover of small companies. As a result, volume of the high-frequency trading and the returns of small and large companies are different from each other.

Suggested Citation

  • Ahmad Sarlak & Zahra Talei, 2016. "Impact of High-Frequency Trading on the Stock Returns of Large and Small Companies in the Tehran Stock Exchange," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 8(4), pages 216-228, April.
    • Handle: RePEc:ibn:ijefaa:v:8:y:2016:i:4:p:216-228
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    References listed on IDEAS

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    1. Flavin, Thomas J. & Panopoulou, Ekaterini & Unalmis, Deren, 2008. "On the stability of domestic financial market linkages in the presence of time-varying volatility," Emerging Markets Review, Elsevier, vol. 9(4), pages 280-301, December.
    2. Ser-Huang Poon & Clive W.J. Granger, 2003. "Forecasting Volatility in Financial Markets: A Review," Journal of Economic Literature, American Economic Association, vol. 41(2), pages 478-539, June.
    3. Robert Ślepaczuk & Grzegorz Zakrzewski, 2009. "High-Frequency and Model-Free Volatility Estimators," Working Papers 2009-13, Faculty of Economic Sciences, University of Warsaw.
    4. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    5. Chaker Aloui, 2007. "Price and volatility spillovers between exchange rates and stock indexes for the pre- and post-euro period," Quantitative Finance, Taylor & Francis Journals, vol. 7(6), pages 669-685.
    6. Akgiray, Vedat, 1989. "Conditional Heteroscedasticity in Time Series of Stock Returns: Evidence and Forecasts," The Journal of Business, University of Chicago Press, vol. 62(1), pages 55-80, January.
    7. Morelli, David, 2002. "The relationship between conditional stock market volatility and conditional macroeconomic volatility: Empirical evidence based on UK data," International Review of Financial Analysis, Elsevier, vol. 11(1), pages 101-110.
    8. Valadkhani, Abbas & O'Brien, Martin & Karunanayake, Indika, 2009. "Modelling Australian Stock Market Volatility: A Multivariate GARCH Approach," Economics Working Papers wp09-11, School of Economics, University of Wollongong, NSW, Australia.
    9. Li, Hong & Majerowska, Ewa, 2008. "Testing stock market linkages for Poland and Hungary: A multivariate GARCH approach," Research in International Business and Finance, Elsevier, vol. 22(3), pages 247-266, September.
    10. Nelson M. P. C. Areal & Stephen J. Taylor, 2002. "The realized volatility of FTSE‐100 futures prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 22(7), pages 627-648, July.
    11. Yau, Hwey-Yun & Nieh, Chien-Chung, 2009. "Testing for cointegration with threshold effect between stock prices and exchange rates in Japan and Taiwan," Japan and the World Economy, Elsevier, vol. 21(3), pages 292-300, August.
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    More about this item

    Keywords

    high-frequency trading; MS- EGARCH; stock returns; stock exchange; assets log;
    All these keywords.

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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