Quantifying bid-ask spreads in the Chinese stock market using limit-order book data: Intraday pattern, probability distribution, long memory, and multifractal nature
Gao-Feng Gu (ECUST), Wei Chen (SZSE), Wei-Xing Zhou (ECUST)

TL;DR
This study analyzes the statistical properties of bid-ask spreads in the Chinese stock market, revealing intraday patterns, power-law distributions, long memory, and the absence of multifractality in the spread time series.
Contribution
It provides a comprehensive analysis of bid-ask spread characteristics in the Chinese market, including intraday patterns, distribution laws, long memory, and multifractal analysis, which were not previously detailed.
Findings
Bid-ask spreads show a big L-shape pattern intraday.
Spread distributions decay as power laws with tail exponents between 2 and 3.
Bid-ask spread time series exhibit long memory but are not multifractal.
Abstract
The statistical properties of the bid-ask spread of a frequently traded Chinese stock listed on the Shenzhen Stock Exchange are investigated using the limit-order book data. Three different definitions of spread are considered based on the time right before transactions, the time whenever the highest buying price or the lowest selling price changes, and a fixed time interval. The results are qualitatively similar no matter linear prices or logarithmic prices are used. The average spread exhibits evident intraday patterns consisting of a big L-shape in morning transactions and a small L-shape in the afternoon. The distributions of the spread with different definitions decay as power laws. The tail exponents of spreads at transaction level are well within the interval and that of average spreads are well in line with the inverse cubic law for different time intervals. Based on the…
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Taxonomy
TopicsComplex Systems and Time Series Analysis · Financial Risk and Volatility Modeling · Chaos control and synchronization
