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Algorithmic trading

About: Algorithmic trading is a research topic. Over the lifetime, 6718 publications have been published within this topic receiving 162209 citations. The topic is also known as: algotrading & Algorithmic trading.


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Journal ArticleDOI
TL;DR: In this paper, the authors develop an equilibrium model for stock market liquidity and its impact on asset prices when constant market presence is costly, and demonstrate a negative relation between these measures and expected stock returns.
Abstract: In this paper, we develop an equilibrium model for stock market liquidity and its impact on asset prices when constant market presence is costly. We show that even when agents' trading needs are perfectly matched, costly market presence prevents them from synchronizing their trades and hence gives rise to endogenous order imbalances and the need for liquidity. Moreover, the endogenous liquidity need, when it occurs, is characterized by excessive selling of significant magnitudes. Such liquidity-driven selling leads to market crashes in the absence of any aggregate shocks. Finally, we show that illiquidity in the market leads to high expected returns, negative and asymmetric return serial correlation, and a positive relation between trading volume and future returns. We also propose new measures of liquidity based on its asymmetric impact on prices and demonstrate a negative relation between these measures and expected stock returns.

42 citations

Journal ArticleDOI
TL;DR: In this paper, the predictability of long time series of stock index levels and stock prices using both statistical and trading rule methodologies is investigated using both ARMA-ARCH models and bootstrap methods.
Abstract: The predictability of long time series of stock index levels and stock prices is investigated using both statistical and trading rule methodologies. The trading rule analysis uses a double moving-average rule and the methods of Brock, Lakonishok and LeBaron. Results are obtained for the FTA, FTSE-100, DJIA and S&P-500 indices, prices for twelve UK stocks and indices derived from these stock prices. Statistical analysis shows that the index and price series are not random walks. The trading rule analysis generally confirms this conclusion. However, small transaction costs would eliminate the profitability of the moving-average rule. Standard ARMA-ARCH models are estimated for time series of returns and bootstrap methods are used to decide if the models can explain the observed trading statistics. The models provide a reasonable description but there is evidence from the trading rule methodology that standard models sometimes fail to describe the dynamics of the indices and prices. Several comparisons are m...

42 citations

Journal ArticleDOI
TL;DR: In this article, the authors studied the return reversals of exchange traded real estate securities using an arbitrage portfolio approach and found that there exist significant return reversal in such securities if trading costs can be ignored.
Abstract: This paper studies the return reversals of exchange traded real estate securities using an arbitrage portfolio approach. Using the approach, we find that there exist significant return reversals in such securities. These return reversals could be exploited by arbitrage traders if trading costs can be ignored. However, the arbitrage profits disappear after deducting trading costs and taking into account the implicit cost of bid-ask spread. Thus, the real estate securities market is efficient at weekly intervals in the sense that one could not exploit the price reversals via some simple trading rules.

41 citations

Journal ArticleDOI
TL;DR: In this paper, a self-enforcing agreement between broker-dealers and long-lived clients is proposed to support short-term trading losses in adverse selection models of security market microstructure.
Abstract: In adverse-selection models of security market microstructure, a market maker could enhance efficiency if he or she were willing to sustain short-term trading losses We show that this desirable activity can be supported as a self-enforcing agreement between broker-dealers and long-lived clients An implication is that brokers who sustain such losses should charge higher fees to long-term clients for trades where the broker merely receives a commission This prediction is supported by an analysis of brokerage rates on the Australian Stock Exchange By contrast, market makers who make trading profits charge lower agency fees to large, long-term clients Copyright 1995 by University of Chicago Press

41 citations

Journal ArticleDOI
TL;DR: In this paper, an empirical analysis of the intraday market liquidity and volume concentration on the Swiss Stock Exchange is presented, showing that the US market influences the Swiss trading day to a remarkable extent.
Abstract: This study is an empirical analysis of the intraday market liquidity and volume concentration on the Swiss Stock Exchange. The intraday market liquidity on the Swiss market exhibits a triple-U shaped pattern. An intraday pattern of volume concentration also exists. The empirical evidence shows that the US market influences the Swiss trading day to a remarkable extent. The results also suggest the dynamics of an order-driven market. Disequilibrium between demand and supply conditions are associated with an increase in trading volume and a thinner limit order book. In this market condition, trades engender a wider spread and price volatility.

41 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202397
2022190
2021144
2020167
2019126
2018160