Algorithmic Trading: Issues and Preliminary Evidence
In 1971, while the organization of trading on the NYSE had not changed much since its creation in 1792, Fischer Black (1971) was asking whether trading could be automated and whether the specialist's judgement could be replaced by that of a computer (the specialist is a market-maker designated to post bid and ask quotes for stocks listed on the NYSE). Forty years later, market forces have given a positive reponse to these questions.
Computerization of trading in financial markets began in the early 1970s with the introduction of the NYSE's “designated order turnaround” (DOT) system that routed orders electronically to the floor of the NYSE. It was then followed with the development of program trading, the automation of index arbitrage in the 1980s, and the introduction of fully computerized matching engines (e.g., the CAC trading system in France in 1986 or the Electronic Communication Networks in the US in the 1990s). In recent years, this evolution accelerated with traders using computers to implement a wide variety of trading strategies, e.g., market-making, at a very fine time scale (the millisecond).
The growing importance of these “high frequency traders” (HFTs) has raised various questions about the effects of algorithmic trading on financial markets. These questions are hotly debated among practitioners, regulators, and in the media. There is no agreement on the effects of HFTs.1