scholarly journals The Price Impact of Order Book Events from a Dimension of Time

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Wentao Chi ◽  
Xuemei Zhao ◽  
Lufei Huang
Keyword(s):  
Stock Market ◽  
High Frequency ◽  
Time Window ◽  
Explanatory Power ◽  
Chinese Mainland ◽  
Price Impact ◽  
Order Book ◽  
Chinese Stock Market ◽  
Time Dimension ◽  
The Difference

We propose a new linear model to explain the price move by Level-2 high-frequency data in Chinese mainland stock market. In Chinese stock market, the cancellation ratio is very low, and imbalanced order flow prevails most of the time in the trading periods. From time dimension viewpoint, we find the difference of efficiency of limit orders executed, respectively, in bid/ask limit order book, order execution imbalance (OEI), could improve the classic model of Cont et al. (2014) based on market microstructure of Chinese mainland stock market. In particular, when market’s liquidity is booming, our model’s explanatory power and R-squared increased sharply. And the correlations of OEI are very high that may be exploited to predict the price move in the next time window for doing high-frequency trading.

Broker ID transparency and price impact of trades: evidence from the Korean Exchange

2015 ◽  
Vol 11 (1) ◽  
pp. 117-131 ◽  
Author(s):  
Thu Phuong Pham
Keyword(s):  
Stock Market ◽  
Private Information ◽  
Stock Exchange ◽  
Price Impact ◽  
Least Square ◽  
Market Quality ◽  
Order Book ◽  
Information Effect ◽  
Content Type ◽  
Market Depth

Purpose – The purpose of this paper is to examine the changes in the price impact of trades in the major Korean stock market following the introduction of disclosure to all traders of the top five brokers on the buy-side and the top five brokers on the sell-side of trades in real time for each stock in the KOSDAQ market. Design/methodology/approach – The paper uses several alternative metrics for the price impact of trades. The study applies estimation methodology that accounts for the potential endogeneity of other market quality proxies, which are used as control variables in price impact regressions, by utilizing two-stage-least-square methods with fixed effect specification. Findings – This study finds that the permanent price impact (information effect) of both buyer- and seller-initiated trades increases, which indicates that information is disseminated quicker in a transparent market. Uninformed trades have a larger permanent price impact than informed trades on both the buy and sell sides. The liquidity price effects are found to be mixed for buys and sells. Research limitations/implications – The study supports the current policy of the Korean Exchange to publicly display the five most active broker IDs on both the buy and sell sides, as it attracts both informed and liquidity traders, leading to faster price discovery in a more transparent market. However, a future study which analyzes the change in the market quality in both local markets would provide a complete picture of the effects of the policy. Originality/value – Earlier studies documenting the effect of broker ID disclosure on market quality used effective spreads, market depth or order book imbalance as market quality measures. This study contributes to the existing literature by examining the changes in direct measures of the private information effect and liquidity effect of trades in a stock market – the Korean Stock Exchange – when the other part of the exchange (the KOSDAQ stock market) shifts to public broker ID transparency at the same transparency level.

scholarly journals Financial Technology: China’s Stock Markets vs U.S. Stock Markets

2021 ◽  
Vol 275 ◽  
pp. 01006
Author(s):  
Ruiqian Chang
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
The United States ◽  
Chinese Stock Market ◽  
Chinese Market ◽  
The Difference ◽  
The Many ◽  
Excessive Speculation ◽  
The U.S ◽  
Financial Technology

This paper provides a detailed analysis of the difference between the Chinese stock market and the U.S. stock market under the development of financial technology. In conclusion, we find that the Chinese stock market is more dominated by retail investors, but the United States owns more stocks, mostly held by institutional investors, and has a better financial mindset. The behavior of investors in the Chinese stock market is mainly the excessive speculation of investors in the Chinese market. This is one of the reasons for the many fluctuations in the Chinese stock market. Due to the speculative nature of China’s stock market, the floating ratio reflects the management mechanism of China’s stock market and helps to observe the correlation with the U.S. stock market. And technology and digitalization affect the trading of the stock market. This research is correlational, and there is no causality implied.

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