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Microstructure Invariance in U.S. Stock Market Trades

Author

Listed:
  • Albert S. Kyle

    () (Robert H. Smith School of Business, University of Maryland)

  • Anna Obizhaeva

    () (New Economic School)

  • Tugkan Tuzun

    () (Board of Governors of the Federal Reserve System)

Abstract

This paper studies invariance relationships in tick-by-tick transaction data in the U.S. stock market. Over the 1993-2001 period, the estimated monthly regression coefficients of the log of trade arrival rate on the log of trading activity have an almost constant value of 0:666, strikingly close to the value of 2=3 predicted by the invariance hypothesis. Over the 2001-14 period, the estimated coefficients rise, and their average value is equal to 0:79, suggesting that the reduction in tick size in 2001 and the subsequent increase in algorithmic trading resulted in a more intense order shredding in more liquid stocks. The distributions of trade sizes, adjusted for differences in trading activity, resemble a log-normal before 2001; there is clearly visible truncation at the round-lot boundary and clustering of trades at even levels. These distributions change dramatically over the 2001-14 period with their means shifting downward. The invariance hypothesis explains about 88 percent of the cross-sectional variation in trade arrival rates and average trade sizes; additional explanatory variables include the invariance-implied measure of effective price volatility.

Suggested Citation

  • Albert S. Kyle & Anna Obizhaeva & Tugkan Tuzun, 2016. "Microstructure Invariance in U.S. Stock Market Trades," Working Papers w0230, Center for Economic and Financial Research (CEFIR).
  • Handle: RePEc:cfr:cefirw:w0230
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    References listed on IDEAS

    as
    1. Obizhaeva, Anna A. & Wang, Jiang, 2013. "Optimal trading strategy and supply/demand dynamics," Journal of Financial Markets, Elsevier, vol. 16(1), pages 1-32.
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    More about this item

    Keywords

    market microstructure; transactions data; market frictions; trade size; tick size; order shredding; clustering; TAQ data;

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors

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