Microstructural Features

By analysing the microstructure of the market can help detect trading activity of economic agents with asymmetric information.

Quants have analysed the microstructure of financial markets over the years and developed several potential predictive features. Over the years more and more data has become available leading to more advanced features in each generation. Describing these microstructural features in detail is beyond the scope of this whitepaper, however if the users wish to read more about them, then they can look at the referenced papers.

  • First Generation

    • These features were developed when there was limited data available and focus on estimating the bid-ask spread and volatility as a proxy of illiquidity.

      • Roll Measure

      • Roll Impact

      • Parkinson Volatility

      • Corwin Schultz Spread

      • Beckers Parkinson Volatility

  • Second Generation

    • These features focus on understanding and measuring illiquidity and have a stronger theoretical foundation.

      • Kyle's Lambda

      • Amihud's Lambda

      • Hasbrouck's Lambda

  • Third Generation

    • Sequential trade models were developed to model randomly selected traders arriving at the market sequentially and independently, these models have become increasingly popular as it models various sources of uncertainty.

      • Volume-Synchronised Probability of Informed Trading (VPIN)


  • Amihud, Y. (2002). Illiquidity and stock returns: cross-section and time-series effects. Journal of financial markets, 5(1), 31-56.

  • Beckers, S. (1983). Variances of security price returns based on high, low, and closing prices. Journal of Business, 97-112.

  • Corwin, S. A., & Schultz, P. (2012). A simple way to estimate bid‐ask spreads from daily high and low prices. The Journal of Finance, 67(2), 719-760.

  • De Prado, M. L. (2018). Advances in financial machine learning. John Wiley & Sons.

  • Easley, D., de Prado, M. M. L., & O'Hara, M. (Eds.). (2013). High-frequency trading: New realities for traders, markets and regulators. Incisive Media.

  • Hasbrouck, J. (2009). Trading costs and returns for US equities: Estimating effective costs from daily data. The Journal of Finance, 64(3), 1445-1477.

  • Kyle, A. S. (1985). Continuous auctions and insider trading. Econometrica: Journal of the Econometric Society, 1315-1335.

  • Roll, R. (1984), A Simple Implicit Measure of the Effective Bid‐Ask Spread in an Efficient Market. The Journal of Finance, 39: 1127-1139. https://doi.org/10.1111/j.1540-6261.1984.tb03897.x

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