The Fear Index

6

The boardroom had the same corporate impersonality – the same soundproofed glass walls and floor-to-ceiling venetian blinds – as the managers’ offices. A giant blank screen for teleconferencing took up most of the end wall, looking down on to a big oval table of pale Scandinavian wood. As Hoffmann entered the room, all but one of the table’s eighteen chairs was occupied either by the principals or their advisers; the only spare place was next to Quarry at its head. Quarry’s gaze followed his progress round the edge of the room with evident relief. ‘Here he is at last,’ he said, ‘Dr Alexander Hoffmann, ladies and gentlemen, the president of Hoffmann Investment Technologies. As you can see, his brain’s so big we’ve had to let out his head to give it some breathing space. Sorry, Alex, only joking. I’m afraid he took a bit of a knock, hence the stitches, but he’s fine now, aren’t you?’

They all stared. Those nearest to Hoffmann twisted in their seats to look up at him. But Hoffmann, hot with embarrassment, avoided eye contact. He took his position next to Quarry, folded his hands on the table in front of him, and stared fixedly at his interlaced fingers. He felt Quarry’s hand grasp his shoulder, the weight increasing as the Englishman rose to his feet.

‘Right then, we can at last get started. So – welcome, friends, to Geneva. It’s almost eight years since Alex and I set up shop together, using his intelligence and my looks, to create a very special kind of investment fund, based exclusively on algorithmic trading. We started with just over a hundred million dollars in assets under management, a big chunk of it courtesy of my old friend over there, Bill Easterbrook, of AmCor – welcome, Bill. We made a profit that first year, and we’ve gone on making a profit every year, which is why we are now one hundred times larger than when we started, with AUM of ten billion dollars.

‘I’m not going to boast about our track record. I hope I don’t need to. You all get the quarterly statements and you know what we’ve achieved together. I’ll just give you one statistic. On the ninth of October 2007, the Dow Jones Industrial Average closed at 14,164. Last night – I checked it before I left my office – the Dow closed at 10,866. That represents a loss over more than two and a half years of almost one quarter. Imagine that! All those poor saps with their retirement plans and their tracker bonds have lost about twenty-five per cent of their investment. But you, by placing your trust in us over the same period, have seen your net asset value increase by eighty-three per cent. Ladies and gentlemen, I think you’ll agree that bringing your money to us was a pretty smart thing to have done.’

For the first time Hoffmann risked a brief glance around the table. Quarry’s audience was listening intently. (‘The two most interesting things in the world,’ Quarry once remarked: ‘other people’s sex lives and your own money.’) Even Ezra Klein, rocking back and forth like a student in a madrasa, was temporarily still, while Mieczyslaw Lukasinski simply could not keep the grin off his plump peasant face.

Quarry’s right hand continued to rest on Hoffmann’s shoulder; his left was thrust casually in his pocket. ‘In our business we call the gap between market performance and fund performance “alpha”. Over the past three years, Hoffmann has generated alpha of one hundred and twelve per cent. That’s why we’ve twice been voted Algorithmic Hedge Fund of the Year by the financial trade press.

‘Now,’ he went on, ‘this consistency of performance is not, I can assure you, a matter of luck. Hoffmann spends thirty-two million dollars a year on research. We employ sixty of the most brilliant scientific minds in the world – at least I’m told they’re brilliant: I can’t understand a word they’re on about.’

He acknowledged the rueful laughter. Hoffmann saw that the British banker, Iain Mould, was chuckling particularly hard, and he knew at once that he was a fool. Quarry withdrew his hands from Hoffmann’s shoulder and from his own pocket and placed them on the table. He leaned forward, suddenly serious and urgent.

‘About eighteen months ago, Alex and his team achieved a significant technological breakthrough. As a result we had to take the very difficult decision to hard-close the fund.’ Hard-close meant turning away additional investment even from existing clients. ‘And I know that every single one of you in this room – because that is why we’ve invited you here – was disappointed by that decision, and also bewildered, and that some of you were actually pretty angry about it.’

He glanced at Elmira Gulzhan listening at the opposite end of the table. She had screamed at Quarry down the phone, Hoffmann knew, and had even threatened to withdraw the family’s money from the fund or worse (‘You hard-close the Gulzhans – the Gulzhans hard-close you…).

‘Well,’ continued Quarry, with the merest hint of a kiss blown in Elmira’s direction, ‘we apologise for that. But we took the view that we had to concentrate on implementing this new investment strategy based on our existing asset size. There’s always a risk with any kind of fund, as I’m sure you’re aware, that increasing size translates into decreasing performance. We wanted to be as confident as we could be that that wouldn’t happen.

‘It is now our opinion that this new system, which we call VIXAL-4, is robust enough to cope with portfolio expansion. Indeed, the alpha generated over the last six months has been significantly greater than it was when we were relying on our original algorithms. Therefore, as of today, I can announce that Hoffmann is moving from a hard-closed to a soft-closed position, and is willing to accept additional investment from existing clients only.’

He stopped and took a sip of water to allow the impact of his words to sink in. There was complete silence in the room.

‘Cheer up, everyone,’ he said brightly, ‘this is supposed to be good news.’

The tension was released by laughter and for the first time since Hoffmann entered the room the clients looked openly at one another. They had become a private club, he realised: a freemasonry bound together by a shared secret knowledge. Complicit smiles spread around the table. They were on the inside track.

‘At which point,’ said Quarry, looking on contentedly, ‘I think the best thing I can do is hand you over to Alex here, who can fill you in a bit more on the technical side.’ He half-sat down then stood again. ‘With a bit of luck I may even be able to understand it myself.’

More laughter, and then the floor was Hoffmann’s.

He was not a man to whom speaking in public came naturally. The few classes he had taught at Princeton before leaving the United States had been torture for lecturer and students alike. But now he felt himself filled with a strange energy and clarity. He touched his fingers lightly to his sewn-up wound, took a couple of deep breaths, then rose to his feet.

‘Ladies and gentlemen, we have to be secretive about the detail of what we do in this company, to avoid having our ideas stolen by our competitors, but the general principle is no great mystery, as you well know. We take a couple of hundred different securities and we trade them over a twenty-four-hour cycle. The algorithms we have programmed into our computers pick the positions we hold based on a detailed analysis of previous trends, mostly liquid futures – the Dow, say, or the S and P 500 – and the familiar commodities: Brent crude, natural gas, gold, silver, copper, wheat, whatever. We also do some high-frequency trading, where we may hold positions for only a few milliseconds. It’s really not that complicated. Even the S and P two-hundred-day moving average can be a pretty reliable predictor of the market: if the current index is higher than the preceding average, the market is likely to be bullish; if lower, bearish. Or we can make a prediction, based on twenty years of data, that if tin is at this price and the yen at that, then it is more likely than not that the DAX will be here. Obviously we have vastly more pairs of averages than that to work with – several millions of them – but the principle can be simply stated: the most reliable guide to the future is the past. And we only have to be right about the markets fifty-five per cent of the time to make a profit.

‘When we started out, not many people could have guessed how important algorithmic trading would turn out to be. The pioneers in this business were frequently dismissed as quants, or geeks, or nerds – we were the guys who none of the girls would dance with at parties-’

‘That’s still true,’ interjected Quarry.

Hoffmann waved aside the interruption. ‘Maybe it is, but the successes we have achieved at this firm speak for themselves. Hugo pointed out that in a period when the Dow has declined by nearly twenty-five per cent, we’ve grown in value by eighty-three per cent. How has this happened? It’s very simple. There have been two years of panic in the markets, and our algorithms thrive on panic, because human beings always behave in such predictable ways when they’re frightened.’

He raised his hands. ‘“The space of heaven is filled with naked beings rushing through the air. Men, naked men, naked women who rush through the air and rouse gale and snowstorm. Do you hear it roaring? Roaring like the wing-beat of great birds high in the air? That is the fear of naked men. That is the flight of naked men.”’

He stopped. He looked around at the upturned faces of his clients. Several had their mouths open, like baby birds hoping for food. His own mouth felt dry. ‘Those are not my words. They’re the words of an Inuit holy man, quoted by Elias Canetti in Crowds and Power: when I was designing VIXAL-4 I used them as a screensaver. Can I have some water, Hugo?’ Quarry leaned over and passed him a bottle of Evian and a glass. Hoffmann ignored the glass, unscrewed the plastic cap and drank straight from the bottle. He didn’t know what effect he was having on his audience. He didn’t much care. He wiped his mouth on the back of his hand.

‘Around 350 BC, Aristotle defined human beings as “ zoon logon echon ” – “the rational animal” or, more accurately, “the animal that has language”. Language, above all, is what distinguishes us from the other creatures on the planet. The development of language freed us from a world of physical objects and substituted a universe of symbols. The lower animals may also communicate with one another in a primitive way, and may even be taught the meaning of a few of our human symbols – a dog can learn to understand “sit” or “come”, for example. But for perhaps forty thousand years only humans were zoon logon echon: the animal with language. Now, for the first time, that is no longer true. We share our world with computers.

‘Computers…’ Hoffmann gestured towards the trading floor with his bottle, slopping water across the table. ‘It used to be the case that we imagined that computers – robots – would take over the menial work in our lives, that they would put on aprons and run around and be our robot maids, doing the housework or whatever, leaving us free to enjoy our leisure. In fact, the reverse is happening. We have plenty of spare, unintelligent human capacity to do those simple, menial jobs, often for very long hours and poor pay. Instead, the humans that computers are replacing are members of the educated classes: translators, medical technicians, legal clerks, accountants, financial traders.

‘Computers are increasingly reliable translators in the sectors of commerce and technology. In medicine they can listen to a patient’s symptoms and are diagnosing illnesses and even prescribing treatment. In the law they search and evaluate vast amounts of complex documents at a fraction of the cost of legal analysts. Speech recognition enables algorithms to extract the meaning from the spoken as well as the written word. News bulletins can be analysed in real time.

‘When Hugo and I started this fund, the data we used was entirely digitalised financial statistics: there was almost nothing else. But over the past couple of years a whole new galaxy of information has come within our reach. Pretty soon all the information in the world – every tiny scrap of knowledge that humans possess, every little thought we’ve ever had that’s been considered worth preserving over thousands of years – all of it will be available digitally. Every road on earth has been mapped. Every building photographed. Everywhere we humans go, whatever we buy, whatever websites we look at, we leave a digital trail as clear as slug-slime. And this data can be read, searched and analysed by computers and value extracted from it in ways we cannot even begin to conceive.

‘Most people are barely aware of what has happened. Why would they be? If you leave this building and go along the street, everything looks pretty much as it’s always looked. A guy from a hundred years ago could walk around this part of Geneva and still feel at home. But behind the physical facade – behind the stone and the brick and the glass – the world has distorted, buckled, shrunk, as if the planet has passed into another dimension. I’ll give you a tiny example. In 2007, the British government lost the records of twenty-five million people – their tax codes, their bank account details, their addresses, their dates of birth. But it wasn’t a couple of trucks they lost: it was just two CDs. And that’s nothing. Google will one day digitalise every book ever published. No need for a library any more. All you’ll need is a screen you can hold in your hand.

‘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 ended in a miscarriage, but easily the longest and by far the most shattering. The hospital had given her an MRI scan when they began to get concerned, which was unusual. Afterwards, rather than stay on her own in Switzerland, she had gone with Alex on a business trip to Oxford. Wandering round a museum while he was interviewing PhDs in the Randolph Hotel, she had come across a 3D model of the structure of penicillin built up on sheets of Perspex in 1944 by Dorothy Hodgkin, the Nobel laureate for chemistry. An idea had stirred in her mind, and when she got home to Geneva, she had tried the same technique on the MRI scan of her womb, which was all she had left of the baby.

It had taken a week of trial and error to work out which of the two hundred cross-sectional images to print off, and how to trace them on to glass, what ink to use and how to stop it smearing. She had sliced her hands repeatedly on the sharp edges of the glass sheets. But the afternoon when she first lined them up and the outline had emerged – the clenched fingers, the curled toes – was a miracle she would never forget. Beyond the window of the apartment where they had lived in those days, the sky had turned black as she worked; brilliant yellow flashes of forked lightning had stabbed down over the mountains. She knew nobody would believe it if she told them. It was too theatrical. It had made her feel as if she were tapping into some elemental force: tampering with the dead. When Alex came home from work and saw the portrait, he had sat stunned for ten minutes.

After that she had become utterly absorbed by the possibilities of marrying science and art to produce images of living forms. Mostly she had acted as her own model, talking the radiographers at the hospital into scanning her from head to toe. The brain was the hardest part of the anatomy to get right. She had to learn which were the best lines to trace – the aqueduct of Sylvius, the cistern of the great cerebral vein, the tentorium cerebellum and the medulla. The simplicity of the form was what appealed to her most, and the paradoxes it carried – clarity and mystery, the impersonal and the intimate, the generic and yet the absolutely unique. Watching Alex going through the CAT scanner that morning had made her want to produce a portrait of him. She wondered if the doctors would let her have his results, or if he would allow her to do it.

She wrapped up the last of the glass sheets tenderly, and then the base, and sealed the cardboard box with thick brown sticky tape. It had been a painful decision to offer this, of all her works, to the exhibition: if someone bought it, she knew she would probably never see it again. And yet it seemed to her an important thing to do: that this was the whole point of creating it in the first place – to give it a separate existence, to let it go out into the world.

She picked up the box and carried it out into the passageway as if it were an offering. On the handles of the doors leading off the corridor, and on the wooden panels, were traces of bluish-white powder where the surfaces had been dusted for fingerprints. In the hall, the blood had been cleaned off the floor. The surface was still damp, showing where Alex had been lying when she discovered him. She carefully skirted the spot. A noise came from inside the study and she felt her skin rise into gooseflesh just as a man’s heavy shape loomed in the doorway. She gave a cry of alarm and almost dropped the box.

She recognised him. It was the security expert, Genoud. He had shown her how to use the alarm system when they first moved in. Another man was with him – heavyset, like a wrestler.

‘Madame Hoffmann, forgive us if we startled you.’ Genoud had a grave professional manner. He introduced the other man. ‘Camille has been sent by your husband to look after you for the rest of the day.’

‘I don’t need looking after…’ began Gabrielle. But she was too shaken to put up much resistance, and found herself allowing the bodyguard to take the box from her hands and carry it out to the waiting Mercedes. She protested that at least she wanted to drive herself to the gallery in her own car. But Genoud was insistent that it was not safe – not until the man who had attacked her husband had been caught – and such was his blunt professional inflexibility that eventually she surrendered again and did as she was told.

‘Bloody brilliant,’ whispered Quarry, catching Hoffmann by the elbow as they left the boardroom.

‘You think? I got the feeling I’d lost them at one point.’

‘They don’t mind being lost, as long as you bring them back eventually to what they really want to see, which is the bottom line. And everyone loves a bit of Greek philosophy.’ He steered Hoffmann ahead of him. ‘My God, old Ezra’s an ugly bugger, but I could give him a kiss for that bit of mental arithmetic at the end.’

The clients were waiting patiently on the edge of the trading floor, all except for young Herxheimer and the Pole, Lukasinski, who had their backs to the others and were talking with quiet animation into their cell phones. Quarry exchanged a look with Hoffmann. Hoffmann shrugged. Even if they were breaking the terms of the non-disclosure agreement, there was not much that could be done. NDAs were bitches to enforce without evidence of breach, by which point it was too late in any case.

‘This way, if you please,’ called Quarry, and with his finger held aloft, tour-guide-style, he led them in a crocodile across the big room. Herxheimer and Lukasinski quickly ended their calls and rejoined the group. Elmira Gulzhan, wearing a large pair of sunglasses, automatically assumed the head of the queue. Clarisse Mussard, in her cardigan and baggy pants, shuffled along in her wake, looking like her maid. Instinctively Hoffmann glanced up at the CNBC ticker to see what was happening on the European markets. The week-long slide seemed to have stopped at last; the FTSE 100 was up by nearly half of one per cent.

They gathered round a trading screen in Execution. One of the quants vacated his desk to give them a better view.

‘So, this is VIXAL-4 in operation,’ said Hoffmann. He stood back to let the investors get closer to the terminal. He decided not to sit: that would have allowed them to see the wound on his scalp. ‘The algorithm selects the trades. They’re on the left of the screen in the pending orders file. On the right are the executed orders.’ He moved a little nearer so that he could read the figures. ‘Here, for instance,’ he began, ‘we have…’ He paused, surprised by the size of the trade; for a moment he thought the decimal point was in the wrong place. ‘Here you see we have one and a half million options to sell Accenture at fifty-two dollars a share.’

‘Whoa,’ said Easterbrook. ‘That’s a heck of a bet on the short side. Do you guys know something about Accenture we don’t?’

‘Fiscal Q2 profits down three per cent,’ rattled off Klein from memory, ‘earnings sixty cents a share: not great, but I don’t get the logic of that position.’

Quarry said, ‘Well, there must be some logic to it, otherwise VIXAL wouldn’t have taken the options. Why don’t you show them another trade, Alex?’

Hoffmann changed the screen. ‘Okay. Here – you see? – here’s another short we’ve just put on this morning: twelve and a half million options to sell Vista Airways at seven euros twenty-eight a share.’

Vista Airways was a low-cost, high-volume European airline, which none of those present would have dreamed of being seen dead on.

‘ Twelve and a half million? ’ repeated Easterbrook. ‘That must be a heck of a chunk of the market. Your machine has got some balls, I’ll give it that.’

‘Really, Bill,’ said Quarry, ‘is it that risky? All airline stocks are fragile these days. I’m perfectly easy with that position.’ But he sounded defensive, and Hoffmann guessed he must have noticed that the European markets were up: if a technical recovery spread across the Atlantic, they might be caught by a rising tide and end up having to sell the options at a loss.

Klein said, ‘Vista Airways had twelve per cent passenger growth in the final quarter and a revised profits forecast up nine per cent. They’ve just taken delivery of a new fleet of aircraft. I don’t get the sense of that position, either.’

‘Wynn Resorts,’ said Hoffmann, reading off the next screen. ‘A million-two short at one hundred and twenty-four.’ He frowned, puzzled. These enormous bets on the down side were unlike VIXAL’s normal complex pattern of hedged trades.

‘Well that one truly is amazing to me,’ said Klein, ‘because they had Q1 growth up from seven-forty million to nine-oh-nine, with a cash dividend of twenty-five cents a share, and they’ve got this great new resort in Macau that’s literally a licence to print money – it turned over twenty billion in table games in Q1 alone. May I?’ Without waiting for permission, he leaned past Hoffmann, seized the mouse and started clicking through the recent trades. His suit smelled like a dry-cleaning store; Hoffmann had to turn away. ‘Procter and Gamble, six million short at sixty-two… Exelon, three million short at forty-one-fifty… plus all the options… Jesus, Hoffmann – is an asteroid about to hit the earth, or what?’

His face was practically pressed against the screen. He produced a notebook from his inside pocket and began scribbling down the figures, but Quarry reached over and deftly plucked it from his hand. ‘Naughty, Ezra,’ he said. ‘You know this is a paperless office.’ He tore out the page, screwed it into a ball and put it in his pocket.

Francois de Gombart-Tonnelle, Elmira’s lover, said, ‘Tell me, Alex, a big short such as any one of these – does the algorithm put it on entirely independently, or does it require human intervention to execute?’

‘Independently,’ replied Hoffmann. He wiped the details of the trades from the screen. ‘First the algorithm determines the stock it wishes to trade. Then it examines the trading pattern of that stock over the past twenty days. Then it executes the order itself in such a way as to avoid alerting the market and affecting the price.’

‘So the whole process is really just fly-by-wire? Your traders are like pilots in a jumbo jet?’

‘That’s it exactly. Our system speaks directly to the executing broker’s system, and then we use their infrastructure to hit the exchange. Nobody telephones a broker any more. Not from this shop.’

Iain Mould said, ‘There must be human supervision at some point, I hope?’

‘Yes, just like there is in the cockpit of a jumbo – there’s constant supervision, but not usually intervention, not unless something starts going wrong. If one of the guys in Execution sees an order going through that worries him, naturally he can put a stop on it until it’s cleared by me or Hugo, or one of our managers.’

‘Has that ever happened?’

‘No. Not with VIXAL-4. Not so far.’

‘How many orders does the system handle a day?’

Quarry took over: ‘About eight hundred.’

‘And they’re all decided algorithmically?’

‘Yes. I can’t remember the last time I did a trade myself.’

‘Your prime broker is AmCor, I assume, given your long relationship?’

‘We have various prime brokers these days, not just AmCor.’

‘More’s the pity,’ said Easterbrook, laughing.

Quarry said, ‘With the greatest respect to Bill, we don’t want one single brokerage firm knowing all our strategies. At the moment we use a mix of big banks and specialist houses: three for equities, three for commodities and five for fixed income. Let’s take a look at the hardware, shall we?’

As the group moved off, Quarry pulled Hoffmann aside. ‘Am I missing something here,’ he said quietly, ‘or are those positions way out of line?’

‘They do look a little more exposed than normal,’ agreed Hoffmann, ‘but nothing to worry about. Now I think of it, LJ mentioned that Gana wanted a meeting of the Risk Committee. I told him to talk to you about it.’

‘Christ, is that what he wanted? I didn’t have time to take his call. Damn it.’ Quarry glanced at his watch, then up at the tickers. The European markets were holding on to their early gains. ‘Okay, let’s grab five minutes while they’re all having coffee. I’ll tell Gana to meet us in my office. You go on ahead and keep them happy.’

The computers were housed in a big windowless room on the opposite side of the trading floor, and this time Hoffmann led the way. He stood in front of the face-recognition camera – only a few were cleared for access to this inner sanctum – and waited for the bolts to click back, then pushed at the door. It was solid, fireproof, with a pane of reinforced glass in the centre and rubber vacuum seals on the sides, so that it made a slight whoosh as it opened, the bottom of the seal skimming the white-tiled floor.

Hoffmann went in first; the others followed. Compared to the relative silence of the trading floor, the busy racket of the computers sounded almost industrial. The arrays were stacked on warehouse shelving, their rows of red and green indicator lights flickering rapidly as they processed data. At the end of the room, in a pair of long Plexiglas cabinets, two IBM TS3500 tape robots patrolled up and down on monorails, shooting with the speed of striking snakes from one end to the other as VIXAL-4 instructed them to store or retrieve data. It was several degrees colder than the rest of the building. The noise of the powerful air-conditioning needed to keep down the temperature of the central processing units, combined with the whir of the fans on the motherboards themselves, made it surprisingly difficult to hear. When everyone was inside, Hoffmann had to raise his voice for the people at the back.

‘In case you think this is impressive, I should point out that it is only four per cent of the capacity of the CPU farm at CERN, where I used to work. But the principle is the same. We have nearly a thousand standard CPUs,’ he said, resting his hand proudly on the shelves, ‘each with two to four cores, exactly the same as those you have at home, except without the casing and repackaged for us by a white box company. We’ve found this to be much more reliable and cost-effective than investing in supercomputers, and easier to upgrade, which we’re doing all the time. I guess you’re familiar with Moore’s Law? This states that the number of transistors that can be placed on an integrated circuit – which basically means memory size and processing speed – will double every eighteen months, and costs will halve. Moore’s Law has held with amazing consistency since 1965, and it still holds. In CERN in the nineties we had a Cray X-MP/48 supercomputer which cost fifteen million dollars and delivered half the power a Microsoft Xbox now gives you for two hundred bucks. You can imagine what that trend means for the future.’

Elmira Gulzhan was clasping her arms and shivering exaggeratedly. ‘Why does it have to be so damn cold in here?’

‘The processors generate a lot of heat. We have to try to keep them cool to stop them breaking down. If we were to shut off the air-conditioning in here, the temperature would rise at a rate of one degree Celsius a minute. Within twenty minutes it would be very uncomfortable. In half an hour we’d have a total shutdown.’

Etienne Mussard said, ‘So what happens if there is a power cut?’

‘For short-term interruptions, we switch to car batteries. After ten minutes of no mains power, diesel generators in the basement would cut in.’

‘What would happen if there was a fire,’ asked Lukasinski, ‘or this place was attacked by terrorists?’

‘We have full system back-up, naturally. We’d trade straight through. But it isn’t going to happen, don’t worry. We’ve invested a lot in security – sprinkler systems, smoke detectors, firewalls, video surveillance, guards, cyber-protection. And remember, this is Switzerland.’

Most people smiled. Lukasinski did not. ‘Is your security in-house, or outsourced?’

‘Outsourced.’ Hoffmann wondered why the Pole was so obsessed with security. The paranoia of the rich, he guessed. ‘Everything is outsourced – security, legal affairs, accountancy, transport, catering, technical support, cleaning. These offices are rented. Even the furniture is rented. We aim to be a company that not only makes money out of the digital age; we want to be digital. That means we try to be as frictionless as possible, with zero inventory.’

‘What about your own personal security?’ persisted Lukasinski. ‘Those stitches – I understand you were attacked in your home last night.’

Hoffmann felt an odd stab of guilt and embarrassment. ‘How do you know about that?’

Lukasinski said, offhand, ‘Someone told me.’

Elmira rested her hand on Hoffmann’s arm; her long brown-red nails were like talons. ‘Oh Alex,’ she said softly, ‘how awful for you.’

‘Who?’ demanded Hoffmann.

‘If I could just say,’ interjected Quarry, who had slipped in unnoticed at the back, ‘what happened to Alex was nothing whatever to do with company business – just some lunatic who I’m sure will be picked up by the police. And to answer your question directly, Mieczyslaw, we have now taken steps to give Alex additional protection until the issue is resolved. Now does anyone have any more questions directly relating to the hardware?’ There was silence. ‘No? Then I suggest we get out of here before we all freeze to death. There’s coffee in the boardroom to warm us up. If you all go ahead, we’ll join you in a couple of minutes. I just need to have a quick word with Alex.’

They were midway across the trading floor and their backs were to the big TV screens when one of the quants gave a loud gasp. In a room where nobody spoke in much above a whisper, the exclamation rang out like a gunshot in a library. Hoffmann halted in his tracks and turned to see half his workforce rising to their feet, drawn out of their seats by the images on Bloomberg and CNBC. The physicist nearest to him put his hand to his mouth.

Both the satellite channels were showing the same footage, obviously filmed on a mobile phone, of a passenger airliner coming in to land at an airport. It was clearly in trouble, descending far too quickly, and at an odd angle, with one wing much higher than the other, smoke streaming out of its side.

Someone grabbed a remote and pumped up the sound.

The jet passed out of sight behind a control tower and then reappeared, skimming the tops of some low sandy-coloured buildings – hangars, perhaps; there were fir trees in the background. It seemed to graze one of the buildings with its underbelly, a caressing gesture almost, and then abruptly it exploded in a vast expanding ball of yellow fire that carried on rolling and rolling. One of the wings with an engine still attached rose out of the spreading inferno and performed graceful cartwheels up into the sky. The lens followed it shakily until it dropped out of shot, and then the sound of the explosion and the shockwave reached the camera. There were tinny screams and frantic shouts in a language Hoffmann could not quite make out – Russian maybe – the picture shook, and then cut to a later, more stable shot of thick black oily smoke, roiled with orange and yellow flames, unfurling itself above the airport.

Over the images the presenter’s voice – American, female – said breathlessly: ‘Okay, so those were the scenes just a few minutes ago when a Vista Airways passenger jet with ninety-eight people on board crashed on its approach to Moscow’s Domodedovo Airport…’

‘Vista Airways?’ said Quarry, wheeling round to confront Hoffmann. ‘Did she just say Vista Airways?’

A dozen muttered conversations broke out simultaneously across the trading floor: ‘My God, we’ve been shorting that stock all morning.’ ‘How weird is that?’ ‘Someone just walked over my grave.’

‘Will you turn that damn thing off?’ called Hoffmann. When nothing happened, he strode between the desks and snatched the remote from the hands of the hapless quant. Already the footage was starting to repeat, as it doubtless would throughout the day until familiarity at last eroded its power to titillate. Finally he found the mute button and the room was quiet again. ‘All right,’ he said. ‘That’s enough. Let’s get on with our work.’

He threw the remote on to the desk and made his way back to the clients. Easterbrook and Klein, hardened veterans of the dealing room, had already lunged for the nearest terminal and were checking the prices. The others were motionless, stunned, like credulous peasants who had just witnessed a supernatural event. Hoffmann could feel their eyes upon him. Clarisse Mussard even made the sign of the cross.

‘My God,’ said Easterbrook, looking round from the trading screen, ‘it only happened five minutes ago and Vista’s stock is down fifteen per cent already. It’s crashing.’

‘Nose-diving,’ added Klein, with a nervous giggle.

‘Save it, guys,’ said Quarry, ‘there are civilians present.’ He addressed the clients: ‘I remember a couple of traders at Goldman who happened to be shorting airline insurance on the morning of 9/11. They did a high-five in the middle of the office when the first plane hit. They weren’t to know. None of us knows. Shit happens.’

Klein’s eyes were still riveted to the market data. ‘Whoa,’ he murmured appreciatively, ‘your little black box is really cleaning up, Alex.’

Hoffmann stared over Klein’s shoulder. The figures in the Execution column were changing rapidly as VIXAL took profits on its options to sell Vista Airways’ stock at the pre-crash price. The P amp;L meter, converted into dollars, was a blur of pure profit.

Easterbrook said, ‘I wonder how much you guys are going to make from this one trade – twenty million, thirty million? Jesus, Hugo, the regulators are going to be swarming over this like ants at a picnic.’

Quarry said, ‘Alex? We should go and take that meeting.’

But Hoffmann, unable to take his eyes from the figures on the trading screen, was not listening. The pressure in his skull was intense. He put his fingers to his wound and traced his stitches. It felt to him as if they were stretched so tight they might split apart.