Topic
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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TL;DR: The authors examined the impact of shifting liquidity and institutional trading in the corporate bond market on inferences regarding informational efficiency and found that when institutional trade dominance and other bond trading features are accounted for, stock leads evidenced in earlier studies surprisingly disappear.
77 citations
TL;DR: In this article, the authors distinguish two components of self-confidence in a financial market: private selfconfidence measures the selfconfidence of speculators, while public self confidence measures the confidence they attribute to their competitors, and study how independent changes in these components affect the trading strategies.
76 citations
TL;DR: In this article, the authors use two extremely liquid S&P 500 ETFs to analyze the prevailing trading conditions when mispricing allowing arbitrage opportunities is created, and they show that their minor differences are not responsible for the misprice.
Abstract: We use two extremely liquid S&P 500 ETFs to analyze the prevailing trading conditions when mispricing allowing arbitrage opportunities is created. While these ETFs are not perfect substitutes, we show that their minor differences are not responsible for the mispricing. Spreads increase just before arbitrage opportunities, consistent with a decrease in liquidity. Order imbalance increases as markets become more one-sided and spread changes become more volatile which suggests an increase in liquidity risk. The price deviations are economically significant (mean profit of 6.6% p.a. net of spreads) and are followed by a tendency to quickly correct back towards parity.
76 citations
TL;DR: In this article, an order-driven market with heterogeneous investors, who submit limit or market orders according to their own trading rules, is introduced, and the trading rules are repeatedly updated via simple learning and adaptation of the investors.
Abstract: This paper introduces an order-driven market with heterogeneous investors, who submit limit or market orders according to their own trading rules. The trading rules are repeatedly updated via simple learning and adaptation of the investors. We analyze markets with and without learning and adaptation. The simulation results show that our model with learning and adaptation successfully replicates long-memories in trading volume, stock return volatility, and signs of market orders in an informationally efficient market. We also discuss why evolutionary dynamics are important in generating these features.
76 citations
TL;DR: In this paper, the authors introduce a new high-frequency foreign exchange dataset from EBS (Electronic Broking Service) that includes trading volume in the global interdealer spot market, data not previously available to researchers.
Abstract: We introduce a new high-frequency foreign exchange dataset from EBS (Electronic Broking Service) that includes trading volume in the global interdealer spot market, data not previously available to researchers. The data also gives live transactable quotes, rather than the indicative quotes that have been used in most previous high frequency foreign exchange analysis. We describe intraday volume and volatility patterns in euro-dollar and dollar-yen trading. We study the effects of scheduled U.S.macroeconomic data releases, first confirming the finding of recent literature that the conditional mean of the exchange rate responds very quickly to the unexpected component of data releases. We next study the effects of data releases on trading volumes. News releases cause volume to rise, and to remain elevated for a longer period. However, in contrast to the result for the level of the exchange rate, even if the data release is entirely in line with expectations, we find that there is still typically a large pickup in trading volume.
76 citations