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An Entropy-Based Approach to Measurement of Stock Market Depth.

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This study introduces a novel entropy-based market depth indicator for measuring stock market liquidity. This new proxy effectively compares market depth and liquidity across different equities using high-frequency data.

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dimensions of market liquidityentropyhigh-frequency dataintra-day seasonalitymarket depthmarket microstructure

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Area of Science:

  • Quantitative Finance
  • Financial Econometrics
  • Market Microstructure

Background:

  • Market depth is a crucial dimension of stock market liquidity.
  • Existing measures may not fully capture the dynamics of high-frequency trading.
  • A robust and intuitive measure is needed for theoretical and empirical financial analysis.

Purpose of the Study:

  • To introduce a new methodology for measuring market depth using Shannon information entropy.
  • To develop an entropy-based indicator for stock market liquidity.
  • To validate the proposed indicator's effectiveness on real-world high-frequency data.

Main Methods:

  • Application of Shannon information entropy to high-frequency financial data.
  • Development of an algorithm to infer trade initiators.
  • Empirical analysis using data from the Warsaw Stock Exchange (WSE).
  • Robustness tests and intra-day seasonality assessment.

Main Results:

  • The proposed entropy-based market depth indicator effectively measures both market entropy and liquidity.
  • The indicator allows for effective comparison of market depth and liquidity across different equities.
  • Empirical results confirm the proxy's utility on real trading data.

Conclusions:

  • The entropy-based approach offers a promising and intuitive proxy for market depth and liquidity.
  • This new indicator provides a solid foundation for further theoretical and empirical financial market research.
  • The method demonstrates effectiveness in comparing liquidity across various stocks.