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We explore the competitive effects of reaction time of automated tradingstrategies in simulated financial markets containing a single exchange withpublic limit order book and continuous double auction matching. A large body ofresearch conducted over several decades has been devoted to trading agentdesign and simulation, but the majority of this work focuses on pricingstrategy and does not consider the time taken for these strategies to compute.In real-world financial markets, speed is known to heavily influence the designof automated trading algorithms, with the generally accepted wisdom that fasteris better. Here, we introduce increasingly realistic models of trading speedand profile the computation times of a suite of eminent trading algorithms fromthe literature. Results demonstrate that: (a) trading performance is impactedby speed, but faster is not always better; (b) the Adaptive-Aggressive (AA)algorithm, until recently considered the most dominant trading strategy in theliterature, is outperformed by the simplistic Shaver (SHVR) strategy - shaveone tick off the current best bid or ask - when relative computation times areaccurately simulated.

Fools Rush In: Competitive Effects of Reaction Time in Automated Trading