An Entropy-Based Approach to Measurement of Stock Market Depth

Abstract

The aim of this study is to investigate market depth as a stock market liquidity dimension. A new methodology for market depth measurement exactly based on Shannon information entropy for high-frequency data is introduced and utilized. The proposed entropy-based market depth indicator is supported by an algorithm inferring the initiator of a trade. This new indicator seems to be a promising liquidity measure. Both market entropy and market liquidity can be directly measured by the new indicator. The findings of empirical experiments for real-data with a time stamp rounded to the nearest second from the Warsaw Stock Exchange (WSE) confirm that the new proxy enables us to effectively compare market depth and liquidity for different equities. Robustness tests and statistical analyses are conducted. Furthermore, an intra-day seasonality assessment is provided. Results indicate that the entropy-based approach can be considered as an auspicious market depth and liquidity proxy with an intuitive base for both theoretical and empirical analyses in financial markets.

Regularity in Stock Market Indices within Turbulence Periods: The Sample Entropy Approach

“…Entropy is an universal measure, and therefore many applications of entropy have been proposed in the literature, including economic, finance, and management studies (for a brief literature review see for instance [ 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 ] and the references therein).…”

Twitter Sentiment Analysis and Influence on Stock Performance Using Transfer Entropy and EGARCH Methods

“…Transfer entropy was applied for the in-depth analysis (it can be seen as liquidity) of the market with intraday frequency for the Warsaw Stock Exchange in [ 37 ] and in portfolio selection (multiperiod and fuzzy returns) in [ 38 ]; in the same line of portfolio selection using entropy, the authors of [ 39 ] applied an approach considering mean, variance, and skewness. The research directions embodied by mentioned studies are proposed for future opportunities to improve the speed and efficiency of existing approaches used to measure signals in real time.…”

Stock Portfolio Optimization on JII Index using Multi-Objective Mean-Absolute Deviation-Entropy

“…C. Mean-Absolute Deviation and Entropy model 𝐻(𝑥), as the uncertainty value, was first introduced by Shannon [10] in previous research. The main advantage of using entropy is that it creates a well-diversified portfolio.…”