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Electronic trading

About: Electronic trading is a research topic. Over the lifetime, 2923 publications have been published within this topic receiving 78911 citations. The topic is also known as: scripless trading & e-trading.


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Journal ArticleDOI

9,341 citations

Journal ArticleDOI
TL;DR: In this article, the average return on these securities is 10 percent above the return on the stock market as a whole in the 7 months following the individual months of intensive insider buying.
Abstract: Trading by corporate officers, directors, and large stockholders, who are commonly called insiders, commands widespread attention in the financial community. Academicians are interested in the amount of special information insiders possess, as well as in the profit they earn from such knowledge. The average investor seeks out useful information in the Official Summary of Insider Trading,' the monthly report listing the transactions of corporate officials. Previous research on corporate insiders has focused on the profitability of their trading. Some researchers, examining months of intensive insider activity, have concluded that insiders can predict stock price movement up to 6 months subsequent to trading. Rogoff for example, examines 45 companies in which, within a single month, three or more insiders buy their company's stock and no insiders sell the stock.2 He finds that the returns to the insiders of these companies in the following 6 months are on average 91/2 percent greater than the return to the stock market as a whole. Glass examines 14 different calendar months and selects the eight securities with the greatest excess of buyers to sellers among insiders within a month.3 He finds that the average return on these securities is 10 percent above the return on the stock market as a whole in the 7 months following the individual months of intensive buying. Lorie and Niederhoffer investigate stock performance following months in which there are at least two more buyers than sellers or at least two more sellers than buyers among the insiders of a company.4 They find that a security experiencing an intensive buying month is more likely to advance than to decline relative to the market in the 6 months subsequent to the event. Conversely, a security experiencing an intensive selling month is more likely to decline than to advance relative to the market in the 6 months subsequent to the event. Driscoll examines the trading by insiders prior to dividend changes

1,318 citations

Posted Content
TL;DR: Based on within-stock variation, it is found that algorithmic trading and liquidity are positively related and quoted and effective spreads narrow under autoquote and adverse selection declines, indicating that algorithms do causally improve liquidity.
Abstract: Algorithmic trading has sharply increased over the past decade Does it improve market quality, and should it be encouraged? We provide the first analysis of this question The NYSE automated quote dissemination in 2003, and we use this change in market structure that increases algorithmic trading as an exogenous instrument to measure the causal effect of algorithmic trading on liquidity For large stocks in particular, algorithmic trading narrows spreads, reduces adverse selection, and reduces trade-related price discovery The findings indicate that algorithmic trading improves liquidity and enhances the informativeness of quotes

1,190 citations

Journal ArticleDOI
TL;DR: In this article, the authors provided an analysis of an idealized electronic open limit order book and showed that the order book has a small-trade positive bid-ask spread, and limit orders profit from small trades.
Abstract: Under fairly general conditions, the article derives the equilibrium price schedule determined by the bids and offers in an open limit order book. The analysis shows: (1) the order book has a small-trade positive bid-ask spread, and limit orders profit from small trades; (2) the electronic exchange provides as much liquidity as possible in extreme situations; (3) the limit order book does not invite competition from third market dealers, while other trading institutions do; (4) If an entering exchange earns nonnegative trading profits, the consolidated price schedule matches the limit order book price schedule. THIS ARTICLE PROVIDES AN analysis of an idealized electronic open limit order book. The focus of the article is the nature of equilibrium in such a market and how an open limit order book fares against competition from other methods of exchanging securities. The analysis suggests that an electronic open limit order book mimics competition among anonymous exchanges. As a result, there is no incentive to set up a competing anonymous dealer market. On the other hand, any other anonymous exchange will invite "third market" competition. These conclusions suggest that an electronic open limit order book of the sort considered here has a chance of being a center of significant trading volume. The analysis does not imply that an electronic limit order book will be, or should be the only trading institution. It does suggest some of the characteristics that an alternative institution should have in ord'er to successfully compete with an electronic exchange. The results are obtained in a fairly general environment, and hence would appear to be robust. The motivation for the article lies in recent developments in information processing technology, the interest in institutional innovation in the securities industry, and the uncertainty about future developments in trading

1,070 citations

Journal ArticleDOI
TL;DR: In this article, a model of competitive stock trading is developed in which investors are heterogeneous in their information and private investment opportunities and rationally trade for both informational and noninformational motives.
Abstract: A model of competitive stock trading is developed in which investors are heterogeneous in their information and private investment opportunities and rationally trade for both informational and noninformational motives. I examine the link between the nature of heterogeneity among investors and the behavior of trading volume and its relation to price dynamics. It is found that volume is positively correlated with absolute changes in prices and dividends. I show that informational trading and noninformational trading lead to different dynamic relations between trading volume and stock returns.

957 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20239
202230
202125
202039
201939
201846