More on High Frequency Trading and Liquidity
Tyler is more optimistic about financial innovation than I am. Strange, but true. I recommend Andrew Haldane’s speech, The Race to Zero, on high frequency trading (HFT). Haldane is Executive Director for Financial Stability at the Bank of England and his speech is eminently quotable. First, some background from Haldane:
- As recently as 2005, HFT accounted for less than a fifth of US equity market turnover by volume. Today, it accounts for between two-thirds and three-quarters.
- HFT algorithms have to be highly adaptive, not least to keep pace with the evolution of new algorithms. The half-life of an HFT algorithm can often be measured in weeks.
- As recently as a few years ago, trade execution times reached “blink speed” – as fast as the blink of an eye….As of today, the lower limit for trade execution appears to be around 10 micro-seconds. This means it would in principle be possible to execute around 40,000 back-to-back trades in the blink of an eye. If supermarkets ran HFT programmes, the average household could complete its shopping for a lifetime in under a second.
- HFT has had three key effects on markets. First, it has meant ever-larger volumes of trading have been compressed into ever-smaller chunks of time. Second, it has meant strategic behaviour among traders is occurring at ever-higher frequencies. Third, it is not just that the speed of strategic interaction has changed but also its nature. Yesterday, interaction was human-to-human. Today, it is machine-to-machine, algorithm-to-algorithm. For algorithms with the lifespan of a ladybird, this makes for rapid evolutionary adaptation.
Consistent with the research cited by Tyler, Haldane notes that bid-ask spreads have fallen dramatically.
Bid-ask spreads have fallen by an order of magnitude since 2004, from around 0.023 to 0.002 percentage points. On this metric, market liquidity and efficiency appear to have improved. HFT has greased the wheels of modern finance.
But at the same time that bid-ask spread have decreased on average, volatility has sharply increased, as illustrated most clearly with the flash crash
Taken together, this evidence suggests something important. Far from solving the liquidity problem in situations of stress, HFT firms appear to have added to it. And far from mitigating market stress, HFT appears to have amplified it. HFT liquidity, evident in sharply lower peacetime bid-ask spreads, may be illusory. In wartime, it disappears.
In particular, what has happened is that stock prices have become less normal (Gaussian), more fat-tailed, over shorter periods of time.
Cramming ever-larger volumes of strategic, adaptive trading into ever-smaller time intervals would, following Mandelbrot, tend to increase abnormalities in prices when measured in clock time. It will make for fatter, more persistent tails at ever-higher frequencies. That is what we appear, increasingly, to find in financial market prices in practice, whether in volatility and correlation or in fat tails and persistence.
HFT strategies work across markets (e.g. derivatives), exchanges, and stocks and can have negative externality effects on low frequency traders. As a result, micro fat-tails can become macro fat-tails.
Taken together, these contagion channels suggest that fat-tailed persistence in individual stocks could quickly be magnified to wider classes of asset, exchange and market. The micro would transmute to the macro. This is very much in the spirit of Mandelbrot’s fractal story. Structures exhibiting self-similarity magnify micro behaviour to the macro level. Micro-level abnormalities manifest as system-wide instabilities.
For these reasons I am not enthusiastic about innovations in HFT. Earlier I compared high-tech swimming suits and high-frequency trading:
High-tech swimming suits and trading systems are primarily about distribution not efficiency. A small increase in speed over one’s rivals has a large effect on who wins the race but no effect on whether the race is won and only a small effect on how quickly the race is won. We get too much investment in innovations with big influences on distribution and small, or even negative, improvements in efficiency and not enough investment in innovations that improve efficiency without much influencing distribution, i.e. innovations in goods with big positive externalities.