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Invariance of Buy-Sell Switching Points

Author

Listed:
  • Kyoung-hun Bae

    (Hanyang University)

  • Albert S. Kyle

    (University of Maryland)

  • Eun Jung Lee

    (Hanyang University)

  • Anna A. Obizhaeva

    (New Economic School)

Abstract

Market microstructure invariance predicts business time to unfold at a rate proportional to the 2~3 power of the product of dollar volume and returns volatility. Define a "switching point" as an investor changing the direction of trading from buying to selling or selling to buying. For a specific market, the aggregate number of switching points is a good indicator of the pace of business time. Using data from the Korea Exchange (KRX) from 2008 to 2010, we calculate the number of switching points for each stock for each month. The estimated exponent is 0.675 (standard error 0.005, R2 = 0.93) validates the business time clock predicted by invariance. Most variation reflects variation in the number of accounts trading a stock, not variation of switching points per account.

Suggested Citation

  • Kyoung-hun Bae & Albert S. Kyle & Eun Jung Lee & Anna A. Obizhaeva, 2020. "Invariance of Buy-Sell Switching Points," Working Papers w0273, New Economic School (NES).
    • Handle: RePEc:abo:neswpt:w0273
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    References listed on IDEAS

    as
    1. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-155, January.
    2. Torben G. Andersen & Oleg Bondarenko & Albert S. Kyle & Anna Obizhaeva, 2016. "Intraday Trading Invariance in the E-mini S&P 500 Futures Market," Working Papers w0229, Center for Economic and Financial Research (CEFIR).
    3. Anna, Petrenko, 2016. "Мaркування готової продукції як складова частина інформаційного забезпечення маркетингової діяльності підприємств овочепродуктового підкомплексу," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 2(1), March.
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    More about this item

    Keywords

    finance; market microstructure; asset pricing; invariance; trading volume; volatility; liquidity; price impact; market depth;
    All these keywords.

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