James Surowiecki (writer in the New Yorker) wrote a very informative review (in the New York Review of Books) of Michael Lewis’ book ‘Flash Boys’ about the rise of high-frequency trading (HFT) on Wall Street. As the name suggests, high-frequency traders buy and sell in large volumes and at an extraordinary fast pace, trading thousands of times a second. The decisions of the trader are driven by complex algorithms which are designed to follow a defined set of instructions in order to generate profits at a speed and frequency that is impossible for a human trader. The defined sets of rules are based on timing, price, quantity or any mathematical model.
It is estimated that 70% of trading in US stocks is done using. Lewis notes that:
By the summer of 2013, the world’s financial markets were designed to maximize the number of collisions between ordinary investors and high-frequency traders – at the expense of ordinary investors, and for the benefit of high-frequency traders, exchanges, Wall Street banks, and online brokerage firms.
Advocates of HFT will tell you that HFT provides liquidity and this means that the market has a lot of buyers and sellers which suggests that you can make trades without moving the price too much. A liquid market means that people will be more likely to invest. However there are those that worry about the liquidity of HFT as it could be illusory as it could disappear very quickly if stock prices collapse. Andrew Haldane of the Bank of England put it – the fear about this liquidity is that ‘in wartime, it disappears’. Furthermore, HFT has also produced huge swings in stock prices. On 6th May 2010 – know as the ‘Flash Crash of 2.45pm’ – the DJIA fell 9% in 5 minutes but then recovered most of that loss in the subsequent few minutes. But what is most worrying is that nobody can agree what happened because nobody had any control over it. It seems that we are writing things (algorithms) that we can no longer read. We should be worried about HFT as it reduces the amount of the quantity of real and valuable information in the stock market system. It make the system as a whole less stable and more risky. And it devotes an enormous amount of resources to an arms race that is of dubious value.
HFT and the real economy
A recent study of the commodity market found that up to 70% of all price movements in those markets didn’t correlate to events in the global economy. The price movements were driven by algorithms reacting to internal action in the market. This not only makes the market dumber but also a lot more unstable as humans find it impossible to oversee it – e.g Flash Crash of 2.45pm. If HFT traders add liquidity to the market then when the market crashed on 6th May they should have stepped in by buying falling prices of stocks. Turmoil in the markets is nothing new but the speed that it happens today makes trading harder to control raising systemic risk. Some companies will go to get great lengths to improve the speed of trades. In July 2010 a one-inch cable was completed to send a signal from Chicago to New Jersey at a cost of US$300 million. The improvements brought down the estimated roundtrip time of the signal from 13.1 milliseconds to 12.98 milliseconds. But when you are an algorithm 0.3 milliseconds is a long time. The billions of dollars that have been put into HFT over the last 6 years have only had a small impact on the ordinary investor. HFT looks like an arms race as it consumes an enormous amount of resource but generates very little social value and damages the market in the process.
Another High Frequency Trading graphic from the NYT . Having read the reviews of Flash Boys in the NYT and especially that of Diane Coyle on her blog The Enlightened Economist it seems to be a good read.
High-frequency-trading activity is not constant; it occurs in microbursts. The line at the bottom of this graphic is the stock-market activity involving General Electric shares over 100 milliseconds (one-tenth of a second) at 12:44 p.m. on Dec. 19, 2013. The gray box magnifies a five-millisecond window, during which GE experienced heavy bid and offer activity and a total of 44 trades. Credit Graphic: CLEVERºFRANKE. Data source: IEX.
Continuing with the theme of High Frequency Trading here is a graphic from the New York Times which gives you a description of what a millisecond is. The importance of speed in HFT is imperative if you are going to make money. Below is an extract from Kevin Slavin’s TED talk (See video clip below) which shows the lengths that some will go to get closer to the internet.
‘the algorithms of Wall Street are dependent on one quality above all else, which is speed. And they operate on milliseconds and microseconds. And just to give you a sense of what microseconds are, it takes you 500,000 microseconds just to click a mouse. But if you’re a Wall Street algorithm and you’re five microseconds behind, you’re a loser. So if you were an algorithm, you’d look for an architect like the one that I met in Frankfurt who was hollowing out a skyscraper — throwing out all the furniture, all the infrastructure for human use, and just running steel on the floors to get ready for the stacks of servers to go in — all so an algorithm could get close to the Internet.’
Here is a video from a PBS interview with Michael Lewis talking about his new book “Flash Boys: A Wall Street Revolt.” Much of the stock market trading that occurs today is done with computer servers, completing hundreds of millions of orders in a system known as high-frequency trading. Author Michael Lewis has made this practice the subject of his latest book.
Click below to view an adaptation from The New York Times magazine.
The Wolf Hunters of Wall Street
Whilst away on hockey tour in Malaysia I was able to avail myself of the ‘The Straits Times’ newspaper which is published in Singapore. One article that particularly caught my attention was that concerning the creativity of algorithms. Most are oblivious to their creativity yet highly sophisticated algorithms have created music based on the works of great artists but in a style that is personalised and therefore indicative of you the individual. They are also replacing writers – Professor Phil Parker of the Insead Business School in Paris has published more than a million reports on Amazon in just a couple of years. Using a proprietary algorithm that produces a report in 10 – 20 minutes instead of about 4 weeks. The algorithm pulls information from the web, performs econometric analyses, creates tables, formats the report and publishes it as a Word document. Professor Parker has also developed algorithms to produce poems, videos and video games.
Although we could question the efficacy of algorithms on intangible dimensions such as “soul’ and “depth”, one area where they trounce human beings is stock trading. With up to 75% of trades on Wall Street done using computer programmes it is no wonder that algorithms execute trade at lightening speed and carry out numerous transactions every second. On the NYSE the average round-trip transaction time is 600 microseconds. To put into perspective if you blinked it takes you 300 milliseconds to complete the action – during that time NYSE executed 500 trades. This desire to improve efficiency in the market has led to extremely low costs of trading and very high stock liquidity. However it has also produced huge swings in stock prices. On 6th May 2010 – know as the ‘Flash Crash’ – the DJIA fell 9% in minutes but then recovered most of that loss in the subsequent few minutes.
The landscape of society was always made up by this uneasy relationship between nature and man. But now there is this third co-evolutionary force – Algorithms – and we will have to understand them as nature and in a way they are. Kevin Slavin Ted Talk
From Felix Salmon of Reuters – this astonishing GIF comes from Nanex, what we see here is relatively low levels of high-frequency trading through all of 2007. Then, in 2008, a pattern starts to emerge: a big spike right at the close, at 4pm, which is soon mirrored by another spike at the open. This is the era of traders going off to play golf in the middle of the day, because nothing interesting happens except at the beginning and the end of the trading day. But it doesn’t last long.
By the end of 2008, odd spikes in trading activity show up in the middle of the day, and of course there’s a huge flurry of activity around the time of the financial crisis. And then, after that, things just become completely unpredictable. There’s still a morning spike for most of 2009, but even that goes away eventually, to be replaced with sheer noise. Sometimes, like at the end of 2010, high-frequency trading activity is very low. At other times, like at the end of 2011, it’s incredibly high. Intraday spikes can happen at any time of day, and volumes can surge and fall back in pretty much random fashion.
Although I have mentioned this TED talk on a previous post – The Fear Index – I thought it deserves a separate post for people to view the presentation.
Kevin Slavin argues that we’re living in a world designed for — and increasingly controlled by — algorithms. In this riveting talk from TEDGlobal, he shows how these complex computer programs determine: espionage tactics, stock prices, movie scripts, and architecture. And he warns that we are writing code we can’t understand, with implications we can’t control.