Co-Founder at FlexFibre
Ten years on from the banking crisis, is high finance close to introducing a new inequality with its incessant need for speed?
With the tenth anniversary of Lehman’s collapse upon us, attention has turned once more to the banking system and the rarefied towers of high finance. Some, like former Barclays head Bob Diamond, believe that banks have become too risk averse. Others, such as former Prime Minister Gordon Brown, believe that we ‘are sleepwalking into another crisis,’ and that when it comes the tools of international collaboration are no longer as robust as they were in 2008, meaning that any response won’t be so effective. It is telling that two people who were at the centre of the maelstrom now have two completely opposing viewpoints.
Whilst the international will might no longer be so robust as it was a decade ago, with political fractures taking place across the globe, the technology that underpins finance has certainly moved on. With the rise of automated trading platforms, high frequency trading, and the need for faster access, modern finance has become a race for the microsecond advantage.
The drivers of these trends are cost savings and efficiency for institutions managing vast pools of wealth, but any new technology brings with it the risk of failure or, even worse, deliberate misuse.
In 2010 perhaps the most famous case of misuse of high frequency trading occurred. The Flash Crash of 2010, allegedly sparked by Navinder Singh Sarao, a 31 year old man operating out of his bedroom in Hounslow, wiped a trillion dollars off the stock markets, and for short period stocks such as Accenture fell to just a single cent a share. In the same period, Hewlett Packard and Apple Inc saw their share price rise to a hundred thousand dollars. It was a 36 minute period of chaos.
Whilst Mr. Sarao might have been the spark that caused the crash, the real problem was in how the financial systems reacted to his technique of putting in futures orders and then cancelling them before they went through, a process which sent signals to the market systems and caused them to crash. It didn’t help that it was at the time of the Greek Debt Crisis, when the future of the Euro was in doubt and fear of uncertainty was rife. (As John Bates, writing in 2015 for Traders Magazine Online News, put it so well: “Blaming one man in a bedroom for starting the trillion dollar crash was a bit like blaming lightning for starting a fire.”)
The 2010 example is essentially a case study in network failure. It illustrates how networks can be ‘tricked’ by a manipulator who has access to faster speeds.
And whilst some technology behind Mr. Sarao’s activity may now have been banned, the legislation wasn’t enough to prevent another, albeit minor, flash crash in 2015. It appears that legislation in such a complex, Byzantine industry, is falling ever further behind as the pace of innovation speeds up.
Since the Lehman’s collapse that marked the onset of the global financial crisis of 2008 and the lost decade that followed, we have seen the emergence of more powerful technologies. Combining automated trading platforms and algorithmic trading with super high speed market access, we are now at the dawn of what has been called ‘Cyborg Finance.’
The financial markets are fast moving, intricately connected ecosystems with many variations of hardware and software underlying the way they work. This makes them highly vulnerable to shocks, as we saw in the 2010 Flash Crash. With the possibility of artificial intelligence systems being added to algorithmic trading, the human factor is becoming increasingly obsolete in decision making processes made in microseconds.
The possibility of high frequency trading used in conjunction with these systems changes the investing playing field. Long term relationships between those with capital, who would analyse a company, review its management, and invest in it to grow it, and thus create jobs and economic benefits for society, could be replaced by a system that buys and sells many times each second, profiting by the tiniest margins (or losing). And all without serious human oversight.
This will have a detrimental affect on the economy as a whole, as businesses will become targets for the quick fire cyborg trades. And it might be considerably worse still: if these systems identify ways of provoking a network reaction that can crash a certain company or sector or commodity, then it will, and make vast profits in the short term for its owners.
Added to this is the fact that we are entering the age of the Internet of Things. In manufacturing, this technology is becoming widespread, to monitor quality and output and to improve processes, all in real time. It is also becoming used in consumable electronics and increasingly automated cars. In the near future, could these data streams be integrated into the trading AIs? Would they have a better understanding of the companies than any human who relies on quarterly reports or shareholder RNS? Where would we draw the line for such ‘insider trading?’
This isn’t entirely a speculative point either. History presents us with examples where the battle to be the first to be informed gives an advantage: the dubious legend of how the Rothschild family ‘made millions’ by a family agent bringing news back to England of Napoleon’s defeat at Waterloo, some hours before the official missive arrived, is an example believed by many as fact, and remains so long believed as true because of the underlying market belief in the advantage of inside knowledge.
Cyborg trading could go further than this however. It could, feasibly, actually endanger life. If the price of commodities can be manipulated, such as wheat and foodstuffs, then it could interrupt supplies whilst owners wait for better prices before selling. The example with the tragedy of the Irish famine in the 1840s is notable here: Ireland itself was exporting food as many people starved to death in a catastrophe of economics: it was not that food wasn’t available, it was simply too expensive.
A great criticism levelled at the banks after 2008 was that they didn’t know what they were buying. Finance, it was argued, had simply become too complicated and opaque. In a battle for speed linked to algorithmic trading platforms, and a not too distant future AI, the field of finance and investment will become much more complex. The individual investor, playing the traditional game of looking for a safe return over time, will be pitted against the tools of international capital: that of vast data centres, AI, and near light speed decision making, interested not in long term stability but in microsecond margins.
This technology is coming. It will arrive. And we will need the appropriate legislation in place to enforce the correct and responsible use of it. This will be necessary at an international level, and will need to be able to respond to market abuse and failure quickly.
For the consequences for society and the potential for inequality will be profound if the race for speed is allowed to run unregulated and unchecked.