Implications of High-Frequency Trading for Security Markets

Abstract

High-frequency trading (HFT) has grown substantially in recent years due to fast-paced technological developments and their rapid uptake, particularly in equity markets. This review investigates how HFT could evolve and, by developing a robust understanding of its effects, identifies potential risks and opportunities that HFT could present in terms of financial stability and other market outcomes such as volatility, liquidity, price efficiency, and price discovery. Despite commonly held negative perceptions, the available evidence indicates that HFT and algorithmic trading may have several beneficial effects on markets. However, these types of trading may cause instabilities in financial markets in specific circumstances. Carefully chosen regulatory measures are needed to address concerns in the shorter term. However, further work is needed to inform policies in the longer term, particularly in view of likely uncertainties and lack of data. This work will be vital in supporting evidence-based regulation in this controversial and rapidly evolving field.

New Dataset for Forecasting Realized Volatility: Is the Tokyo Stock Exchange Co-Location Dataset Helpful for Expansion of the Heterogeneous Autoregressive Model in the Japanese Stock Market?

“…There are pros and cons to HFT not only in Japan but also globally. Linton and Mahmoodzadeh (2018) indicate that fast algorithmic transactions place unexpectedly large orders due to program errors and algorithms that behave differently than the programmer tend to cause chain reactions, increase market volatility and disrupt market order (For instance, the May 2010 Flash Crash, August 2012 wrong order by Night Capital, October 2018 Tokyo Stock Exchange Markets Arrowhead system trouble triggered by Merrill Lynch, September 2020 Tokyo Stock Exchange Markets Arrowhead system trouble and so on). On the contrary, IOSCO reports that there is a close relationship between liquidity and volatility, in the sense that more liquidity can better absorb shocks to stock prices.…”

Understanding the Flash Crash – state of the art

“…Baron et al (2012) reported speculation that “profitability of HFT has decreased over time, perhaps due to increased competition” (Baron et al , 2012, p. 18); Chaparro (2017) identified in the low volatility era, recently entered by financial markets, as the major cause of profit slowdown, whereas Kaya (2016) found the probable causes of squeezing HFT profits increased in infrastructural costs together with fierce competition. The latter cause was indicated by Linton and Mahmoodzadeh (2018) as the main problem for HFTrs. Specialized press sits on the same sides: “High-speed traders have hit the wall” (Massa and Chilton, 2017), “the bonanza has now ended” (Meyer et al , 2018), and “high frequency trading is done, it's over” (Worstall, 2017).…”

A Survey of Fintech Research and Policy Discussion

“…The bidask spread that investors paid on market orders, which is a measure of trading costs for retail investors, was reduced. And the implementation shortfall, which is a measure of transaction cost for large institutional investors, was also largely reduced from 2001 to 2011; see Menkveld (2016), Jones (2013), and Linton and Mahmoodzadeh (2018).…”