There’s a myth out there about HFTs. Or, algos. Or, machines. Or, vacuum tubes.
That myth, in its dumbed-down form, goes something like this: HFTs are liquidity providers and, contrary to popular belief (and common sense), algorithmic trading actually makes markets more stable.
It doesn’t take an expert on market structure to know how absurd that is.
This is one of those stories that, thanks in no small part to Flash Boys, has become so ubiquitous that the ubiquity is actually clouding the debate. That is, all you need to do is step back and think about what it is we’re talking about here to understand why it’s detrimental.
Does it seem like a good idea to have headline-scanning, momentum-chasing robots “who”, by virtue of being robots, have no sense of nuance running the show? And relatedly, does it make sense to have systematic strats in place that buy and sell indiscriminately when volatility spikes? Of course not.
Well on Tuesday, SocGen was out with a note that offers a very simple explanation for heightened volatility in the metals complex:
Here are the relevant excerpts from the note:
Increasing role being played by algos/high frequency traders
Price volatility has always been attributed to the impact that these fund players have and continue to have on metals markets. Periods of extreme price volatility are more frequent due to the increasing role being played by algorithmic players (algos) and high frequency traders (HFT).
Computer-driven algorithmic trading models (so called “black boxes”) generate buy or sell recommendations according to chart patterns or employ momentum/volatility and/or trend following systems. Algos and HFTs utilise algorithmic computer models to drive high frequency trades, moving in and out of the market in a fraction of a second, taking advantage of small price discrepancies. They are very active in other financial markets such as equities and fixed income and are increasingly active in commodities. Some key characteristics of these players would include:
- Headline-driven,
- Use streaming feeds and rules programmed to recognise “key words”,
- Price moves, often miniscule,
- Trading momentum/volatility signals,
- Trend following,
- Majority of trades are small lot sizes — typically just one lot
Large investment houses are investing in quant, machine learning and artificial intelligence in order to give them an added edge. Indeed, new electronic proprietary (prop) companies utilising quant platforms such as Jump Trading and XTX Markets have become members of the LME.
The jury is out as to whether these players are good or bad for the market. Some would argue it increases liquidity and therefore are good. However, others would argue it creates an uneven playing field and are therefore bad. We would observe that prices are a good deal choppier now than before.
We would disagree on one point. “The jury,” as it were, is not in fact “still out.”
