HFT and illiquidity – Part 2 (English Language)

The present article continues a series dedicated to High Frequency Trading (HFT) and program trading, from which I derive my trading edge. In previous articles I have explained briefly what HFT and program trading are. Last week I have started a new series focusing on market illiquidity produced by the ever increasing presence of HFT. HFT is really dangerous for markets’ health. Hereunder the list of articles published so far:

‘As anticipated last week I have introduced an new series titled: “HFT and illiquidity” (part 1) that focus specifically on the problem of illiquidity, tightly connected to market crashes, caused by the overwhelming presence of High Frequency Trading (HFT). In the below article I will report on the results of some scientific-economic researches. In subsequent articles I will delve into some of the aspects and will provide some conclusions on this topic.

Computer based trading has transformed how financial markets operate. The volume of financial products traded through computer automated trading taking place at high speed and with little human involvement has increased dramatically in the past few years. For example, today, over one third of UK equity trading volume is generated through high frequency automated computer trading while in the US this figure is closer to three-quarters. Whilst the prevalence of computer based trading is not disputed, there are diverse views on the risks and benefits which it brings today, and how these could develop in the future. As anticipated, gaining a better understanding of these issues is critical as they affect the health of the financial services sector and the wider economies this serves. The increasingly rapid changes in financial markets mean that foresight is vital if a resilient regulatory framework is to be put in place. Following are three outcomes from some economic researches.

Outcome 1 – Economic research thus far provides no direct evidence that high frequency computer based trading has increased volatility. However, in specific circumstances, a key type of mechanism can lead to significant instability in financial markets with computer based trading (CBT): self-reinforcing feedback loops (the effect of a small change looping back on itself and triggering a bigger change, which again loops back and so on) within well-intentioned management and control processes can amplify internal risks and lead to undesired interactions and outcomes. The feedback loops can involve risk-management systems, and can be driven by changes in market volume or volatility, by market news, and by delays in distributing reference data. A second cause of instability is social: a process known as normalisation of deviance, where unexpected and risky events come to be seen as ever more normal (e.g. extremely rapid crashes, like the Flash Crash in 2010), until a disaster occurs.

Outcome 2 – Overall, liquidity has improved, transaction costs are lower, and market efficiency has not been harmed by computerised trading in regular market conditions. The nature of market making (i.e. the task of quoting both a buy and a sell price in a financial instrument or commodity held in inventory, hoping to make a profit on the bid-offer spread) has changed, shifting from designated providers to opportunistic traders. High frequency traders now provide the bulk of liquidity, but their use of limited capital combined with ultra-fast speed creates the potential for periodic illiquidity. Computer –driven portfolio rebalancing and deterministic algorithms create predictability in order flows. This allows greater market efficiency, but also new forms of market manipulation. Technological advances in extracting news will generate more demand for high frequency trading, while increased participation in this will limit its profitability.

Outcome 3 – Ongoing advances in the sophistication of ’robot‘ automated trading technology, and reductions in the cost of that technology, are set to continue for the foreseeable future. Today’s markets involve human traders interacting with large numbers of robot trading systems, yet there is very little scientific understanding of how such markets can behave. For time-critical aspects of automated trading, readily customisable, special-purpose silicon chips offer major increases in speed; where time is less of an issue, remotely-accessed ’cloud‘ computing services, offer even greater reductions in cost. Future trading robots will be able to adapt and learn with little human involvement in their design. Far fewer human traders will be needed in the major financial markets of the future.

In conclusion, there are researches putting focus on the causes of instability, both technical and social; some researches focus on the benefit of increased liquidity, but as we have seen in the first part of this series, the portion of human market participants reacts to the presence of HTF with a size back of their trades. Lastly, a thir group of researchers focuses on the technology advances indicating that the phenomen could even develop with less and less participation from humans. Next week I will continue to dwell on the outcomes illustrated so far.’

The above article appeared on my free Newsletter sent out last Sunday, November the 11th along with other information typically including: a weekly review for the Euro-Dollar cross, and S&P500 and other Forex, indices or commodities futures (FibStalker View on Currencies), articles on my trading method, market commentaries and HFT/Program Trading articles like the one you just read. Please, register here to receive the free weekly newsletter.

If you like this article, please share it with your friends and fellow traders. Thank you.

1 Comment

Filed under Articles, English language, Newsletter, Program Trading

One response to “HFT and illiquidity – Part 2 (English Language)

  1. You are welcome.

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