Algorithmic trading has become a hugely important tool to investment firms in recent years as time is one of the few advantages they can have over their rivals.
Historically, investors could gain an edge over the competition through contacts, meetings and researching less well-known companies. But in a fast-paced, internet-driven world, markets are said to have become more efficient – that is to say, that most information is now out in the public forum and it is difficult to gain an informational edge. How then, to beat your rivals to a trade?
Spotting Patterns
Algorithmic trading is all about how quickly a computer can spot patterns and buy and sell. One element of this is high frequency trading: when a trading order is placed, there is a slight delay between the time it takes a stock exchange computer to process that order and when the purchase goes through. High-frequency traders use that fraction of a second to jump in and buy or sell first, thus securing the better price.
You may have heard about the phenomenon in the Michael Lewis book Flash Boys, which revealed stories of trading houses paying billions to move their tech millimetres closer to a computer server to gain a time advantage equivalent to thousandths or even just millionths of a second.
Algorithmic trading is slightly different – it is less about the speed of a trade, and more about spotting patterns. If an algorithm spots a huge buy order or a share price travelling upwards, for example, it may be programmed to jump in and buy shares. This helps to drive the share price up further so the trader can sell the shares at a profit shortly after.
Jordan Hiscott, chief trader at BUX Financial Markets, says: “Algorithmic trading can be executing a trade when some pre-determined conditions are met, for example: an asset moves above its 50-day average and makes a new high for 30 minutes and has traded more than a certain percentage of its typically daily volume. Once all three criteria are met, an automated program enters a trade.
“In addition, another program can be created to scan different social media platforms and the web in general for certain phrases which could trigger positive or negative sentiment, which could also trigger a program to execute trade.”
Flash Crashes
Both algorithmic and high frequency trading have proved controversial, blamed for several so-called flash crashes, whereby a share price or stock market inexplicably plunges for a few minutes – or just moments – before righting itself.
One of the most famous of these “flash crashes” occurred on May 6 2010, when major world indices such as the Dow Jones, S&P 500 and Nasdaq plunged then recovered, triggering short-term panic among traders. Five years later, US prosecutors laid at least some of the blame with UK-based day trader Navinder Singh Sarao, saying that he used software to place then immediately cancel thousands of orders in a practice now banned known as “spoofing”. The Commodity Futures Trading Association published a detailed report into the event. It concluded that high frequency traders (HFTs) do not improve liquidity in markets and amplify price volatility.
And so-called algo-trading has come to fore again in the furore surrounding the shorting of Burford Capital shares by US hedge fund firm Muddy Waters. Burford has now accused Muddy Waters of “illegal market manipulation” after analysis of trading in its shares revealed that traders placed and then cancelled £90 million of sell orders. Trading algorithms, it is thought, may have noticed the sell orders and followed with their own in the belief the share price would fall.
Muddy Waters also publicised its intentions to short a stock on Twitter, which experts say may have contributed to Burford’s share price plunge. The day before publishing its report the firm tweeted: “8am London time we will announce a new short position on an accounting fiasco that’s potentially insolvent and possibly facing a liquidity crunch.”
Buford’s shares fell 65% the following day. It is a standout case of shorting because of how aggressively the share price moved. Some commentators have speculated that the use of social media may have exacerbated the situation as some trading algorithms scour the internet for key words such as “insolvent” and “liquidity risks” to inform their trades.
Hiscott says: “Misleading comments, market manipulation and spoofing is illegal: spoofing is the practice of the misleading the market of trade size to either buy or sell. It is relatively easy for regulators to spot.”
Short-Selling
So, while short-selling a stock that you genuinely believe is overvalued is a legitimate form of investing, as we discuss in our overview here, using misleading comments and market manipulation is not.
Routinely placing and then cancelling trades is an illegal form of market manipulation and the Financial Conduct Authority has revealed it has been undertaking “wide-ranging enquiries” since Muddy Waters’ first tweet.
Ryan Hughes, head of active portfolios at AJ Bell, says: “High frequency trading will always be an emotive topic, with many seeing it as part of the market that doesn’t add any value and actually exacerbates volatility. However, there is an argument that it can add liquidity to markets and make trading cheaper for everyone.”
It is not yet clear whether Muddy Waters has fallen foul of the rules. The firm says it welcomes scrutiny by the FCA and would be ready to assist with any inquiry: “Spoofing and layering are issues that have arisen in the high frequency and computer-driven trading world and Muddy Waters has neither the capability nor the incentive to engage in these practices. They have nothing to do with us."
Hiscott says: “Alleged market manipulation is a contentious issue. It has always been a factor when trading financial assets but has become even more pertinent as we go further into the digital age.”
Hughes adds: “While there may be benefits, such as liquidity, to high frequency and algorithmic trading, my view is that it tends to only really benefit those involved in it and can often be to the detriment of long-term investors.”
