‘But here’s the thing. Human beings still read at the same speed as Aristotle did. The average American college student reads four hundred and fifty words per minute. The really clever ones can manage eight hundred. That’s about two pages a minute. But IBM just announced last year they’re building a new computer for the US government that can perform twenty thousand trillion calculations a second. There’s a physical limit to how much information we, as a species, can absorb. We’ve hit the buffers. But there’s no limit to how much a computer can absorb.
‘And language – the replacement of objects with symbols – has another big down side for us humans. The Greek philosopher Epictetus recognised this two thousand years ago when he wrote: “What disturbs and alarms man are not the things but his opinions and fancies about the things.” Language unleashed the power of the imagination, and with it came rumour, panic, fear. But algorithms don’t have an imagination. They don’t panic. And that’s why they’re so perfectly suited to trade on the financial markets.
‘What we have tried to do with our new generation of VIXAL algorithms is to isolate, measure, and factor into our market calculations the element of price that derives entirely from predictable patterns of human behaviour. Why, for example, does a stock price that rises on anticipation of positive results almost invariably fall below its previous price if those results turn out to be poorer than expected? Why do traders on some occasions stubbornly hold on to a particular stock even as it loses value and their losses mount, while on other occasions they sell a perfectly good stock they ought to keep, simply because the market in general is declining? The algorithm that can adjust its strategy in answer to these mysteries will have a huge competitive edge. We believe there is now sufficient data available for us to be able to begin anticipating these anomalies and profiting from them.’
Ezra Klein, who had been rocking back and forth with increasing frequency, could no longer contain himself. ‘But this is just behavioural finance!’ he blurted out. He made it sound like a heresy. ‘Okay, I agree, the EMH is bust, but how do you filter out the noise to make a tool from BF?’
‘When one subtracts out the valuation of a stock as it varies over time, what one is left with is the behavioural effect, if any.’
‘Yeah, but how do you figure out what caused the behavioural effect? That’s the history of the entire goddam universe, right there!’
‘Ezra, I agree with you,’ said Hoffmann calmly. ‘We can’t analyse every aspect of human behaviour in the markets and its likely trigger over the past twenty years, however much data is now digitally available, and however fast our hardware scans it. We realised from the start we would have to narrow the focus right down. The solution we came up with was to pick on one particular emotion for which we know we have substantive data.’
‘So which one have you picked?’
‘Fear.’
There was a stirring in the room. Although Hoffmann had tried to avoid jargon – how typical of Klein, he thought, to bring up EMH, the efficient market hypothesis – he had nevertheless sensed a growing bafflement among his audience. But now he had their attention, no question. He continued: ‘Fear is historically the strongest emotion in economics. Remember FDR in the Great Depression? It’s the most famous quote in financial history: “The only thing we have to fear is fear itself.” In fact fear is probably the strongest human emotion, period. Whoever woke at four in the morning because they were feeling happy? It’s so strong we’ve actually found it relatively easy to filter out the noise made by other emotional inputs and focus on this one signal. One thing we’ve been able to do, for instance, is correlate recent market fluctuations with the frequency rate of fear-related words in the media – terror, alarm, panic, horror, dismay, dread, scare, anthrax, nuclear. Our conclusion is that fear is driving the world as never before.’
Elmira Gulzhan said, ‘That is al-Qaeda.’
‘Partly. But why should al-Qaeda arouse more fear than the threat of mutually assured destruction did during the Cold War in the fifties and sixties – which, incidentally, were times of great market growth and stability? Our conclusion is that digitalisation itself is creating an epidemic of fear, and that Epictetus had it right: we live in a world not of real things but of opinion and fantasy. The rise in market volatility, in our opinion, is a function of digitalisation, which is exaggerating human mood swings by the unprecedented dissemination of information via the internet.’
‘And we’ve found a way to make money out of it,’ said Quarry happily. He nodded at Hoffmann to continue.
‘As most of you will be aware, the Chicago Board of Exchange operates what is known as the S and P 500 Volatility Index, or VIX. This has been running, in one form or another, for seventeen years. It’s a ticker, for want of a better word, tracking the price of options – calls and puts – on stocks traded in the S and P 500. If you want the math, it’s calculated as the square root of the par variance swap rate for a thirty-day term, quoted as an annualised variance. If you don’t want the math, let’s just say that what it does is show the implied volatility of the market for the coming month. It goes up and down minute by minute. The higher the index, the greater the uncertainty in the market, so traders call it “the fear index”. And it’s liquid itself, of course – there are VIX options and futures available to trade, and we trade them.
‘So the VIX was our starting point. It’s given us a whole bunch of useful data going back to 1993, which we can pair with the new behavioural indices we’ve compiled, as well as bringing in our existing methodology. In the early days it also gave us the name for our prototype algorithm, VIXAL-1, which has stuck all the way through, even though we’ve moved way beyond the VIX itself.
We’re now on to the fourth iteration, which with notable lack of imagination we call VIXAL-4.’
Klein jumped in again. ‘The volatility implied by the VIX can be to the up side as well as the down side.’
‘We take account of that,’ said Hoffmann. ‘In our metrics, optimism can be measured as anything from an absence of fear to a reaction against fear. Bear in mind that fear doesn’t just mean a broad market panic and a flight to safety. There is also what we call a “clinging” effect, when a stock is held in defiance of reason, and an “adrenalin” effect, when a stock rises strongly in value. We’re still researching all these various categories to determine market impact and refine our model.’ Easterbrook raised his hand. ‘Yes, Bill?’
‘Is this algorithm already operational?’
‘Why don’t I let Hugo answer that, as it’s practical rather than theoretical?’
Quarry said, ‘Incubation started back-testing VIXAL-1 almost two years ago, although naturally that was just a simulation, without any actual exposure to the market. We went live with VIXAL-2 in May 2009, with play money of one hundred million dollars. When we overcame the early teething problems we moved on to VIXAL-3 in November and gave it access to one billion. That was so successful we decided to allow VIXAL-4 to take control of the entire fund one week ago.’
‘With what results?’
‘We’ll show you all the detailed figures at the end. Off the top of my head, VIXAL-2 made twelve million dollars in its six-month trading period. VIXAL-3 made one hundred and eighteen million. As of last night, VIXAL-4 was up about seventy-nine-point-seven million.’
Easterbrook frowned. ‘I thought you said it had only been running a week?’
‘I did.’
‘But that means…’
‘That means,’ said Ezra Klein, doing the calculation in his head and almost jumping out of his chair, ‘that on a ten-billion-dollar fund, you’re looking at making a profit of four-point-one-four billion a year.’
‘And VIXAL-4 is an autonomous machine-learning algorithm,’ said Hoffmann. ‘As it collects and analyses more data, it’s only likely to become more effective.’
Whistles and murmurs ran around the table. The two Chinese started whispering to one another.
‘You can see why we’ve decided we want to bring in more investment,’ said Quarry with a smirk. ‘We need to exploit the hell out of this thing before anyone develops a clone strategy. And now, ladies and gentlemen, it seems to me that this might be a suitable moment to offer you a glimpse of VIXAL in operation.’
Three kilometres away, in Cologny, forensics had completed their examination of the Hoffmanns’ house. The scene-of-crimes officers – a young man and woman, who might have been students or lovers – had packed up their equipment and left. A bored gendarme sat in his car on the drive.
Gabrielle was in her studio, dismantling the portrait of the foetus, lifting each sheet of glass out of its slot on the wooden base, wrapping it in tissue paper and then in bubble wrap, and laying it in a cardboard box. She found herself thinking how strange it was that so much creative energy should have flowed from the black hole of this tragedy. She had lost the baby two years ago, at five and a half months: not the first of her pregnancies that had
