The Impact of High-Frequency Trading Algorithms on Market Microstructure and Price Discovery Dynamics

Abstract

High-frequency trading (HFT) has changed the nature of contemporary financial markets by making it possible to execute trades much faster and provide liquidity 24/7. As much as HFT can enhance efficiency in the market and speed up the process of price discovery, it also presents volatility and systemic risks especially when the market is under stress. The paper investigates HFT effects on market microstructure and price discovery processes with transaction-based depth of the order book data of major U.S. equities. Empirical evidence shows that HFT is a major source of bid-ask spread reduction, where the breadth of the order book is heightened, and price efficiency is short-term, in normal conditions. Nevertheless, in stressed market conditions, HFT leads to increased volatility, liquidity, and short-term poor price discovery. Such results inform regulators and market participants about the two-fold impact of algorithm trading on the quality of the market. Keywords- High-frequency trading, market microstructure, price discovery, liquidity, volatility, algorithmic trading.