Metaorder limit prices in evaluating expected market impact and assessing execution service quality

This article analyzes whether the factors of the mechanism of high-frequency trading (HFT) or intraday trading affect the process of price reversal and continuation. The price reversal phenomenon is gaining importance rapidly due to the increasingly intensive use of IT/Fintech-based trading automation facilities on the Indonesia Stock Exchange. However, one knows little about how their trading affects volatility and liquidity pressures that cause price reversals. A new research approach uses the factors of market microstructure mechanism based on high-frequency data (HFD-intraday). The research method uses purposive random sampling, which classified price fractions into three groups, specifically low price, medium price, and high price, which are analyzed by logistic panel regression. The research variables used include price reversal (dependent), stock return, trading volume, transaction frequency, volume/frequency (V/F) proxy, volatility, and liquidity. According to low price model research findings, all variables show a significant effect on price reversal; for medium price model, all variables except liquidity show a significant effect on price reversal; and for high price model, all variables have a significant effect on price reversal, except trading volume and volatility. In conclusion, low price shares tend to have higher price reversal probability compared to continuity because they tend to be liquid, low institutional ownership, and minimal reporting/analysis and are controlled by HFTs (uninformed traders). Some variables are not significant because of the bounce effect around the bid-ask spread.

Acknowledgment
Many thanks to Armida S. Alisjahbana, Roy H. Sembel, Budiono, Rahardi S. Rahmanto, and the anonymous referee/reviewer for valuable inputs and feedback.

This paper provides a practical, empirical and theoretical framework that allows investment managers to evaluate stock exchanges’ market quality when choosing among different plausible international trading venues. To compare trading exchanges, it extends the hypothesis of market microstructure invariance to trading across exchanges. A measure ω, the ratio of the market-wide volatility to microstructure invariance, is introduced. The paper computes ω for the exchanges around the world. Its value for the NSE (India) is 24.5%, the Korea Exchange (Korea) is 7.9%, the Shanghai Exchange (China) is 3.5%, and the Shenzhen Exchange (China) is 4.4%, which is significantly different from that of major exchanges in the USA (NYSE – 0.8%, NASDAQ – 1.3%) and Europe (LSE (UK) – 0.4). This country risk dimension clearly identifies which equity exchanges cannot hold their own direct correlational hedges and therefore mandatorily require derivative positions, and has significant implications for the decision making of global long-short equity asset allocators in the Asian listed equity markets.

Researchers have scrutinized the link between investor sentiment and stock market liquidity globally, yet few have delved into this dynamic in emerging markets, especially China. Utilizing a sample of 1,839 publicly listed companies in China from 2010 to 2019, this study applies firm- and year-fixed-effects models to explore the nexus between investor sentiment and stock illiquidity, employing the Amihud measure for stock illiquidity assessment. The outcomes of these fixed-effect regressions illustrate a significantly positive relationship between investor sentiment and stock liquidity in the Chinese market. The positive link is more evident in scenarios characterized by high firm leverage, rapid revenue growth, larger corporations, greater institutional ownership, higher stock volatility, and lower book-to-market ratios. Intriguingly, this analysis incorporates the quadratic term of investor sentiment to examine the potential for a nonlinear dynamic between stock illiquidity and investor sentiment. The findings elucidate that the effect of investor sentiment on stock liquidity diminishes at elevated levels of sentiment, revealing a nonlinear inverse U-shaped relationship. The positive correlation between investor sentiment and stock liquidity persists across the three divisions of the Chinese Shenzhen Stock Exchange and remains robust using alternative liquidity measures, such as Roll’s impact and zeros impact. Addressing causality concerns, current investor sentiment appears to influence subsequent liquidity levels. These results provide valuable perspectives for policymakers, business executives, and investors in the stock market.

Acknowledgment
This research was funded by the Department of Education of Zhejiang Province General Program [Y202353438], the Wenzhou Association for Science and Technology—Service and Technology Innovation Program [jczc0254], the Wenzhou-Kean University Student Partnering with Faculty Research Program [WKUSPF2023004], and the Wenzhou-Kean University International Collaborative Research Program [ICRP2023002].