{"title":"股票价格变动背后:市场微观结构中的供求关系和市场影响","authors":"Jingle Liu, Sanghyun Park","doi":"10.3905/jot.2015.10.3.013","DOIUrl":null,"url":null,"abstract":"This article studies explanatory factors for short-term stock price movement in the U.S. equity market by exploiting the relationship among liquidity supply, liquidity demand, and market movement. Liquidity provision and taking activities at the market-microstructure level are quantitatively measured by central limit order book imbalance and trade imbalance. The authors find that a multivariate linear model, fitted on empirical results of 42 individual U.S. stocks, is able to explain up to 78% of stock movement in short time intervals, with its explanatory powers and model coefficients varying with the length of interval ranging from 30 seconds to 1 hour. This study offers insight in quantifying supply-demand dynamics in market microstructure and provides meaningful ways for trading algorithms to minimize the market impact of orders and maximize liquidity extraction.","PeriodicalId":254660,"journal":{"name":"The Journal of Trading","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Behind Stock Price Movement: Supply and Demand in Market Microstructure and Market Influence\",\"authors\":\"Jingle Liu, Sanghyun Park\",\"doi\":\"10.3905/jot.2015.10.3.013\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article studies explanatory factors for short-term stock price movement in the U.S. equity market by exploiting the relationship among liquidity supply, liquidity demand, and market movement. Liquidity provision and taking activities at the market-microstructure level are quantitatively measured by central limit order book imbalance and trade imbalance. The authors find that a multivariate linear model, fitted on empirical results of 42 individual U.S. stocks, is able to explain up to 78% of stock movement in short time intervals, with its explanatory powers and model coefficients varying with the length of interval ranging from 30 seconds to 1 hour. This study offers insight in quantifying supply-demand dynamics in market microstructure and provides meaningful ways for trading algorithms to minimize the market impact of orders and maximize liquidity extraction.\",\"PeriodicalId\":254660,\"journal\":{\"name\":\"The Journal of Trading\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Journal of Trading\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3905/jot.2015.10.3.013\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Journal of Trading","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3905/jot.2015.10.3.013","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Behind Stock Price Movement: Supply and Demand in Market Microstructure and Market Influence
This article studies explanatory factors for short-term stock price movement in the U.S. equity market by exploiting the relationship among liquidity supply, liquidity demand, and market movement. Liquidity provision and taking activities at the market-microstructure level are quantitatively measured by central limit order book imbalance and trade imbalance. The authors find that a multivariate linear model, fitted on empirical results of 42 individual U.S. stocks, is able to explain up to 78% of stock movement in short time intervals, with its explanatory powers and model coefficients varying with the length of interval ranging from 30 seconds to 1 hour. This study offers insight in quantifying supply-demand dynamics in market microstructure and provides meaningful ways for trading algorithms to minimize the market impact of orders and maximize liquidity extraction.