High-Frequency Trading Systems: Advancements in Ultra-Fast Computing for Enhanced Market Efficiency

Abstract

High-frequency trading (HFT) engines have radically transformed the world of financial markets by leading the way in terms of ultra-fast computing systems. This article discusses how custom hardware architectures, software optimisation methods, and machine-learning algorithms have significantly reduced the data-processing latency in trading settings. The milliseconds to nanosecond execution capabilities have changed the microstructure of the market, having improved the price-discovery mechanisms and liquidity-provisions in a variety of markets. Although these technological advancements have led to a reduction in the bid-ask spreads and enhanced market efficiency, they have, at the same time, caused serious problems in relation to market stability in the case of extreme events. The article examines regulatory reaction to such worries, such as circuit-breaker structures and principle-based structures that trade innovations and systemic-risk issues. Ethical issues relating to speed benefits and fair access to the market are resolved by exploring the alternative market designs, which seek to offset pure technological benefits and maintain efficient price discovery.