The SVB debacle has exposed the hypocrisy of Silicon Valley

US tech innovators have a culture of regarding government as an innovation-blocking nuisance. But when Silicon Valley Bank collapsed, investors screamed for state protection writes John Naughton in The Guardian 

So one day Silicon Valley Bank (SVB) was a bank, and then the next day it was a smoking hulk that looked as though it might bring down a whole segment of the US banking sector. The US government, which is widely regarded by the denizens of Silicon Valley as a lumbering, obsolescent colossus, then magically turned on a dime, ensuring that no depositors would lose even a cent. And over on this side of the pond, regulators arranged that HSBC, another lumbering colossus, would buy the UK subsidiary of SVB for the princely sum of £1.

Panic over, then? We’ll see. In the meantime it’s worth taking a more sardonic look at what went on.

The first thing to understand is that “Silicon Valley” is actually a reality-distortion field inhabited by people who inhale their own fumes and believe they’re living through Renaissance 2.0, with Palo Alto as the new Florence. The prevailing religion is founder worship, and its elders live on Sand Hill Road in San Francisco and are called venture capitalists. These elders decide who is to be elevated to the privileged caste of “founders”.

To achieve this status it is necessary to a) be male; b) have a Big Idea for disrupting something; and c) never have knowingly worn a suit and tie. Once admitted to the priesthood, the elders arrange for a large tipper-truck loaded with $100 bills to arrive at the new member’s door and cover his driveway with cash.

But this presents the new founder with a problem: where to store the loot while he is getting on with the business of disruption? Enter stage left one Gregory Becker, CEO of SVB and famous in the valley for being worshipful of founders and slavishly attentive to their needs. His company would keep their cash safe, help them manage their personal wealth, borrow against their private stock holdings and occasionally even give them mortgages for those $15m dream houses on which they had set what might loosely be called their hearts.
The most striking takeaway was the evidence produced by the crisis of the arrant stupidity of some of those involved

So SVB was awash with money. But, as programmers say, that was a bug not a feature. Traditionally, as Bloomberg’s Matt Levine points out, “the way a bank works is that it takes deposits from people who have money, and makes loans to people who need money”. SVB’s problem was that mostly its customers didn’t need loans. So the bank had all this customer cash and needed to do something with it. Its solution was not to give loans to risky corporate borrowers, but to buy long-dated, ostensibly safe securities like Treasury bonds. So 75% of SVB’s debt portfolio – nominally worth $95bn (£80bn) – was in those “held to maturity” assets. On average, other banks with at least $1bn in assets classified only 6% of their debt in this category at the end of 2022.

There was, however, one fly in this ointment. As every schoolboy (and girl) knows, when interest rates go up, the market value of long-term bonds goes down. And the US Federal Reserve had been raising interest rates to combat inflation. Suddenly, SVB’s long-term hedge started to look like a millstone. Moody’s, the rating agency, noticed and Mr Becker began frantically to search for a solution. Word got out – as word always does – and the elders on Sand Hill Road began to whisper to their esteemed founder proteges that they should pull their deposits out, and the next day they obediently withdrew $42bn. The rest, as they say, is recent history.

What can we infer about the culture of Silicon Valley from this shambles? Well, first up is its pervasive hypocrisy. Palo Alto is the centre of a microculture that regards the state as an innovation-blocking nuisance. But the minute the security of bank deposits greater than the $250,000 limit was in doubt, the screams for state protection were deafening. (In the end, the deposits were protected – by a state agency.) And when people started wondering why SVB wasn’t subjected to the “stress testing” imposed on big banks after the 2008 crash, we discovered that some of the most prominent lobbyists against such measures being applied to SVB-size institutions included that company’s own executives. What came to mind at that point was Samuel Johnson’s observation that “the loudest yelps for liberty” were invariably heard from the drivers of slaves.

But the most striking takeaway of all was the evidence produced by the crisis of the arrant stupidity of some of those involved. The venture capitalists whose whispered advice to their proteges triggered the fatal run must have known what the consequences would be. And how could a bank whose solvency hinged on assumptions about the value of long-term bonds be taken by surprise by the impact of interest-rate increases? All that was needed to model the risk was an intern with a spreadsheet. But apparently no such intern was available. Perhaps s/he was at Stanford doing a thesis on the Renaissance.

The art and science of picking winning teams

In a world of performance data, human judgment is more vital than ever, says former England cricket selector Ed Smith in the FT

The fast bowler Jofra Archer, a brilliant talent new to cricket’s world stage, stands at the top of his run-up, flicking a white cricket ball nonchalantly in his hand. With 30,000 fans in the ground already drunk on drama, and 1.6bn watching around the world, Archer knows what’s coming. The next five minutes, his next six balls — a “Super Over”, the final way to determine a tied cricket match — will decide whether England or New Zealand win the 2019 World Cup. 

“It’s so on a young man,” the TV commentator sighs about the decision to give the 24-year-old Archer the final act. “It’s a big call.” About a hundred yards to Archer’s right, I am watching on with my fellow England selector, as helpless as everyone else in the ground. 

Just before the tournament, right at the eleventh hour, the decision had been made to add Archer to England’s World Cup squad. There had been plenty of public debate about the decision — England, already the top-ranked team without Archer, had been preparing for the World Cup for four years, and a popular player had been dropped to make way for him. Why take the risk? 

Because Archer was exceptional. And we knew with an unusual degree of confidence that he was exceptional. Archer’s early career was unique because he’d played so much cricket in the Indian Premier League (IPL), where every match is televised. And every action in televised cricket leaves a clear data footprint — the precise speed, trajectory, bounce and revolutions of every ball bowled. This is exactly the kind of information decision-makers love to have — an X-ray of the match. And the data from the IPL was unequivocal: Archer not only merited a place in England’s 15-man squad, but also in the best XI. In fact, the data implied he’d be England’s best fast bowler. And he was, taking 20 wickets (an England record) in the tournament. 

But the data only gets you so far. The moments before the Super Over proved that, too. England’s captain, Eoin Morgan, stood alongside Archer — chatting lightly, relaxed, open, a hint of mischief — a moment to enjoy. It was a masterclass in defusing pressure. So what might have been a “big call” turned into an obvious decision — thanks in part to the way Morgan handled things. Archer got his decisions spot on, and England won the World Cup. 

Selection and decision-making are often framed in terms of “art versus science”, with the assumption that, in our digital age, “science” is increasingly marginalising the human factor. But making decisions — and this applies in any area, not just sport — demands weighing and reconciling different kinds of information, and drawing on differing types of intelligence. In the age of data, the question remains: where does the human dimension fit in? 

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The role of England’s chief cricket selector — which I held from 2018 to 2021 — stretches back to 1899. It was once seen as sport’s ultimate establishment position. A sober, grey worsted suit was woven into the job — folded Telegraph in one hand, black umbrella in the other. Cricket persisted with selectors — where football, for example, centralised power in the manager or head coach — partly because formal coaching arrived relatively late in cricket (England’s first head coach was appointed in 1986). Since then, cricket has mostly retained shared responsibility between selectors, coach and captain. 

After all, who is on the field — and here sport is like all industries — has the greatest bearing on winning and losing. That’s why the richest and most advanced sports teams — in football and American sports — have invested heavily in data-informed recruitment, seeking an edge in identifying talent. 

I was 40 when I became England selector; my co-selector, James Taylor, was 28. Our combined age was about the same as some individual England selectors from earlier decades. The impertinence of youth was compounded by the perception that our new selection system leant heavily on data and algorithms. Cricket is a conservative sport. Far from being reassuringly old-fashioned, the new selection panel was often dubbed “left field”. Innovation and tradition rubbed shoulders. That is, of course, a tricky balancing act, with risks on all sides, and while I did not know it at the time, that was probably the attraction. 

Was England cricket now trying to “Moneyball” its selection strategy? Many people thought so. But the analogy is problematic. Moneyball, Michael Lewis’s classic book about the Oakland A’s baseball team, is only partly about data, and significantly about price. One way that Oakland punched above their weight was by buying undervalued players and selling over-valued ones. But for a national sports team, of course, there is no transfer market. You can’t pit your wits against other teams by trading players with, say, the old rival, Australia. England cricket has its talent pool, and that’s that. 

But selectors can — and this is close to the heart of the matter in all professions — diverge from conventional wisdom about where they perceive value. And here, of course, better data is extremely helpful. If you can measure player impact more accurately, then you are getting nearer to identifying “talent that whispers”, not just “talent that shouts” (in the excellent phrasing of Rasmus Ankersen, who was co-director of football at Brentford before moving to Southampton). 

This is not to suggest that data holds all the answers (the theme of many recent sports books) and that human judgment is on the road to oblivion. Yes, sport is in the midst of a data revolution, and you’d be insane not to seek better information to inform decisions. But rather than using data instead of human intelligence, the challenge is using data in tandem with the human dimension. 

And here decisions in sport reflect decisions in life. “What the data says” is too often a convenient way of passing the buck. Better to come out in plain sight: it’s a judgment. 

Risk is the job 

“Creative solutions, please — but nothing that’s too clever by half!” This is a recurrent framing of what people ask for from decision-makers. Wanted: upside outcomes without downside risk. That is impossible. As soon as decisions diverge from consensus, they inevitably come with the threat of a downside. The American investor and thinker Howard Marks has written a superb series of memos on this theme, “Dare to be Great”. 

“By definition, non-consensus ideas that are popular . . . are an oxymoron,” Marks writes. “And in the course of trying to be different and better, they [investors] have to bear the risk of being different and worse.” 

This is the challenge facing strategists in sport. Whenever your decisions diverge from conventional wisdom, you clearly discern value that most people don’t see. So a degree of intellectual loneliness is a necessity. 

One of the most unconventional decisions England cricket made during my time was selecting three spinners and three all-rounders for the 2018 Test series against Sri Lanka. We won the series 3-0. For the next Test match, we also picked an unconventional mix of players in the West Indies and got smashed. “Too clever by half!” 

Perhaps we became more risk-averse after that moment — which I think was a mistake. Because if you stop diverging from consensus, then what are you doing? Someone who makes decisions which merely reflect the average of opinion is not adding any value. 

David Swensen, who headed the Yale endowment fund, said superior decision-making demanded “uninstitutional behaviour from institutions”. The same challenge exists inside sport. Every leading sports organisation is now a huge machine, and that brings its own dangers — diluting a sense of mission, the temptation to keep everyone happy, watering down good ideas and the rush to compromise. 

How can the bureaucracy fight against the risk-averse tendencies of bureaucracies? Even when you’re on the inside, can you retain an outsider’s sense of independence and boldness, before all the compromise gets priced in? That’s central to the task — and inevitably comes with tension. 

 ‘Accepting a negative metric’ 

“Whenever someone innovates in business or in life,” argues the former poker player Caspar Berry, “they almost inevitably do so by accepting a negative metric that other people are unwilling to accept.” 

When the NBA’s Houston Rockets began taking a higher proportion of (long-range) three-point shots, they were accepting the negative metric that they would miss more often. The pay-off was that shots they did convert came with a built-in premium. The trend was initially ridiculed — before being folded into orthodoxy. In 2015-16, only six out of 30 NBA teams took three-pointers in at least a third of their attempts. By 2020-21, 28 teams were doing it. 

Spain’s triumphant football team of 2008-12 sometimes lined up without a striker. Neglecting to select a specialist goalscorer brings risks — as pundits regularly reminded us by imploring Spain to pick a big strong lad up front to bang in the goals. In 2012, Spain preferred the extra midfielder — expanding creative opportunities, while tolerating the negative metric of not selecting a player focused exclusively on scoring. Spain won the final of the 2012 Euros 4-0, their third major title inside four years — revealing a shrewd trade-off. 

In England’s T20 cricket team, we moved towards an ultra-aggressive batting order, with star batsman Jos Buttler moving from the middle order to opening batsman. But didn’t England need Buttler at the end, when the game was on the line? Ideally, yes. But not if it meant restricting Buttler’s ability to shape the contest by keeping him out of the action until it might be too late. 

All these decisions were initially controversial, before they shifted the consensus and became part of a new orthodoxy. That journey is never smooth. So while innovation can draw on data-informed insights, it stands or falls on courage and resilience. There will always be bumps in the road; can you hold the line? Data might illuminate the solution. But it’s going to take personal conviction to get it done. 

Look for ‘Lego’ players 

The NBA player Shane Battier was dubbed “Lego” by his manager because when he was on the court “all the pieces start to fit together”. Battier’s individual stats were moderate, but the team’s overall performance improved. 

Ranked by the team’s win-loss ratio for games in which they played, the three “winningest” England players in the five-day Test matches when I was selector (in order) were Keaton Jennings, Sam Curran and Adil Rashid. All three players faced frequent media pressure about their individual place in the Test team; their contribution to overall success was often overlooked. 

Team success, of course, doesn’t and shouldn’t guarantee an individual’s selection indefinitely, whatever their form and confidence. But collective output should always be part of the mix in assessing an individual. The “Lego” concept is a useful reminder that the ultimate goal is team success. 

 “Choose the best player for every position,” argued Johan Cruyff, “and you’ll end up not with a strong XI, but with XI strong I’s.” Teams that punch above their weight — such as the Premier League football club Brentford FC — consistently recruit players who are undervalued. That skill can be separated into two distinct parts — not only ranking players better (“how good is ‘X’ relative to ‘Y’?”), but also identifying the team’s needs and how to meet them. The way things fit together can be as important as the pieces themselves. 

In assembling the overall puzzle, it helps to have a point of difference. In cricket, left-arm bowlers, for example, outperform their right-arm counter-parts (on average) because they benefit from being unusual. And even the right-arm bowlers in the team benefit, because opposition batsmen have to switch constantly between different angles of attack, increasing the likelihood of being caught off-balance. 

You’re going to have to think, not just compute 

On one level, there is nothing new to be said about the boundaries of rational decision-making. In 1936, the conservative philosopher Michael Oakeshott co-wrote a book about a systematic approach for betting on the Derby, A Guide to the Classics. (The title was a very Cambridge in-joke.) There is a limit, as Oakeshott wrote in another piece, “beyond which there are no precise rules for picking the winner, and . . . some intelligence (not supplied by the rules themselves) [is] necessary”. You’re going to have to think, not just compute. 

Nearly a century later, even after the explosion of a lucrative sports analytics industry, that is loosely the position of Daryl Morey, former general manager of the Houston Rockets, whose innovations have transformed the NBA (and who called Shane Battier “Lego”). “You have to figure out what the model is good and bad at,” Morey argues, “and what humans are good and bad at.” 

No system, in other words, is so good that it can survive without good judgment. You can’t box off a perfect process. Understanding the data can embolden better risk-taking, but it can’t absolve decision-makers from responsibility. 

In the best decision-makers I’ve observed, I’ve sensed they could live with uncertainty and yet still make good (or above-average) decisions. Conversely, an opposite type finds it hard to cope unless they “know for sure”. And yet this second group never can know — so their thinking gets sucked into trying to reduce anxiety rather than searching for better solutions. 

In most interesting aspects of life, there usually is no perfect or complete answer. And yet there is still better and worse. Wise people know this. But admitting it is in danger of falling victim to the craving for convenient certainty — including the expedient use of “what the data says”. Rationality should allow for healthy scepticism about how much can ever be completely known and understood. 

When I started as selector, the optimist in me wanted to believe we could harness data towards “optimising” England selection. In retrospect, I see more clearly that it will always be a highly human challenge founded, above all, on the primacy of judgment. Just as well, too. Because human value lies where things are most unquantifiable and most uncertain.

Every Decision is a Bet : Life is poker not chess - 2

Abridged and adapted from Thinking in Bets by Annie Duke

 

Merriam Webster’s Online Dictionary defines ‘bet’ as ‘a choice made by thinking about what will probably happen’. ‘To risk losing (something) when you try to do or achieve something’ and ‘to make decisions that are based on the belief that something will happen or is true’.

These definitions often overlooked the border aspects of betting: choice, probability, risk, decision, belief. By this definition betting doesn’t have to take place only in a casino or against somebody else.

We routinely decide among alternatives, put resources at risk, assess the likelihood of different outcomes and consider what it is that we value. Every decision commits us to some course of action that, by definition, eliminates acting on other alternatives. All such decisions are bets. Not placing a bet on something is, itself a bet.

Choosing to go to the movies means that we are choosing to not do all other things with our time. If we accept a job offer, we are also choosing to foreclose all other alternatives.  There is always an opportunity cost in choosing one path over others. This is betting in action.

The betting elements of decisions - choice, probability, risk etc. are more obvious in some situations than others. Investments are clearly bets. A decision about a stock (buy, don’t buy, sell, hold..) involves a choice about the best use of our financial resources.

We don’t think of our parenting choices as bets but they are. We want our children to be happy, productive adults when we send them out into the world. Whenever we make a parenting choice (about discipline, nutrition, parenting philosophy, where to live etc.), we are betting that our choice will achieve the future we want for our children.

Job and relocation decisions are bets. Sales negotiations and contracts are bets. Buying a house is a bet. Ordering the chicken instead of vegetables is a bet. Everything is a bet.

Most bets are bets against ourselves

In most of our decisions, we are not betting against another person. We are betting against all the future versions of ourselves that we are not choosing. Whenever we make a choice we are betting on a potential future. We are betting that the future version of us that results from the decisions we make will be better off. At stake in a decision is that the return to us (measured in money, time, happiness, health or whatever we value) will be greater than what we are giving up by betting against the other alternative future versions of us.

But, how can we be sure that we are choosing the alternative that is best for us? What if another alternative would bring us more happiness, satisfaction or money? The answer, of course, is we can’t be sure. Things outside our control (luck) can influence the result. The futures we imagine are merely possible. They haven’t happened yet. We can only make our best guess, given what we know and don’t know, at what the future will look like. When we decide, we are betting whatever we value on one set of possible and uncertain futures. That is where the risk is.

Poker players live in a world where that risk is made explicit. They can get comfortable with uncertainty because they put it up front in their decisions. Ignoring the risk and uncertainty in every decision might make us feel better in the short run, but the cost to the quality of our decision making can be immense. If we can find ways to be more comfortable with uncertainty, we can see the world more accurately and be better for it. 

Inflation: managing the threat to your pension

John Plender in The FT

 
Lenin, the Russian revolutionary leader, is said to have remarked that the best way to destroy the capitalist system was to debauch the currency. 

The Bank of England currently forecasts that inflation in the UK will soon top 10 per cent. This falls short of outright currency debasement. Yet we live in an economy where the capitalists are no longer a tiny group of rentiers and rich business moguls but ordinary people with savings tied up in pension schemes. 

With the general price level rising at the fastest rate since the 1970s there is a serious threat to UK retirement incomes. 

Behind Lenin’s aphorism is an important political truth, namely that inflation brings about a transfer of wealth from creditors to debtors that is unsanctioned by democratic or legal process. 

Because inflation is a monetary phenomenon, the big winners in investment terms tend to be owners of assets that act as a residual sink for the excess money created by central banks. Real assets such as property are an obvious example. So, too, are energy companies and commodities including gold. 

Some argue that crypto assets fall into the same category. Certainly they have been boosted by ultra-loose monetary policy since the 2007-09 financial crisis. But, as I argued here in a piece on the respective investment merits of bitcoin and gold in April, the record of crypto as an inflation hedge is unproven and bitcoin’s performance in recent months has been disastrous in terms of providing a haven against spiralling prices. 

The big losers from inflation are fixed-interest investments such as gilts — a core holding in British pension funds. The capital value and income stream shrink in real terms and tend to underperform equities when price levels are rising fast. 

Debtors who have borrowed on fixed-price contracts enjoy a windfall, notably the government. And since much property is financed by fixed-interest debt, property investors can experience a double win as the value of the asset goes up while the real value of the related debt goes down. 

For savers and pensioners, this underlines the importance of avoiding bonds, and shifting to real assets and value equities which tend to outperform in inflationary times. 

Where possible, it makes sense to fix mortgage rates for longer while nominal interest rates are still at historically low levels and real interest rates will remain negative in the short to medium term. 

The losers from inflation are people on any kind of fixed income — such as annuities — and householders who rent rather than own. 

No perfect answers  

But there are no perfect investment antidotes to inflation and even property is not a foolproof protection, as experience in the late 1970s demonstrated. In my book That’s the Way the Money Goes, published in 1982, I chronicled how many large pension funds incurred huge losses in real estate. The ICI and Unilever pension funds, for example, took devastating hits from their investment in speculative property development in continental Europe, undertaken in both cases in joint ventures with dodgy entrepreneurs who had been severely criticised by Department of Trade inspectors. 

Back then, pension funds were minimally regulated and not required to reveal their finances. Fund managers were panicking as the retail price index reached a year-on-year peak of 26.9 per cent in 1975 and doing inadequate due diligence in their search for havens against the inflationary storm. 

Today, there is greater transparency and funds are so heavily regulated that the risk of such accidents is lower. But management matters. Property does not lift all boats during periods of high inflation. 

Note that there were no index-linked gilts in the 1970s. Yet today, paradoxically, index-linked securities fail to provide any protection against current 7 per cent inflation in the short run. 

This is because they are driven by relative real yields rather than inflation per se. That is, when the yield on nominal gilts rises closer to the rate of inflation the negative real yield falls. So the negative yield on index-linked bonds has to shrink to remain competitive, causing the price to fall. The longer the maturity, the greater potential for loss. Earlier this week the price of the 2068 index linked gilt was down more than 44 per cent since late November — an astonishing plunge. 

Investment returns in the first quarter of this year, when investors came to distrust the central banks’ claim that inflation was transitory, confirm this broad picture around winners and losers. 

According to consultants LCP, fixed-interest gilts delivered a return of minus 12.3 per cent, while index-linked showed minus 6.4 per cent. Overseas equities delivered minus 2.5 per cent, trading under the shadow of rising interest rates and the war in Ukraine. UK equities were positive at 0.5 per cent, no doubt reflecting the energy, commodity and financial services bias of the UK stock market, while commercial property led the field with a positive return of 4.6 per cent. 

Some protection in defined benefit funds 

The impact of inflation on pension scheme members varies according to the nature of the scheme and members’ individual circumstances. Defined benefit schemes, managing £1.9tn of assets at the start of the decade, provide good protection for those still in work because the pension promise is in most schemes related to final pay. 

For defined benefit scheme members their fund’s investment performance is thus of no great importance — unless, that is, the fund is in deficit and the employer is at risk of bankruptcy. If the sponsoring company becomes insolvent and the scheme does not have sufficient assets to meet its pension commitments the official Pension Protection Fund will provide a safety net. But for many the compensation provided by the PPF will fall short of the level they expected. 

Once retirement is reached there is a hierarchy of pension winners and losers. The biggest winners are civil servants and public sector workers whose defined benefit pensions are fully indexed. Where the retail price index is the yardstick they are arguably on a gravy train because the RPI is based on an outdated arithmetic formula (called the Carli index) which official statisticians claim results in systematic overstatement of inflation. 

Where trust deeds permit, pension schemes are now required to change the indexation benchmark to the more realistic consumer price index. But there is a residue of pension scheme members for whom the RPI will continue to deliver an unwarranted bonus, creating inequality within many funds. A further complication is that neither index may be representative of a given individual’s spending patterns. 

Very few private sector defined benefit schemes offer complete indexation of benefits. They usually incorporate an inflation cap, typically up to 5 per cent, so pensioners are dependent on trustees paying discretionary increases to shore up their living standards in a high inflation environment. The ability of trustees to do this is constrained by the high proportion of assets devoted to liability matching which involves pairing the timing of pension outflows with bond cash flows around the same dates. 

The Office for National Statistics estimates that at the end of 2019 nearly 70 per cent of direct investments in private sector schemes were in long- term debt securities of which three-quarters was in gilts. This means that the return-seeking portion of these portfolios, out of which discretionary pension increases can be paid, is limited. That could be a serious impediment to such increases if inflation were to go much higher. 

Defined contribution plans at the mercy of markets 

With defined contribution (DC) or money purchase plans, investment returns are crucial to the level of pension that scheme members receive. The latest pension survey by the ONS noted that there are now 22.4mn people in DC schemes compared with 18.3mn in DB. 

This reflects the closure to new members of countless private sector DB schemes as employers baulked at the cost supporting them. They have thereby shifted the risk of pensions funding to the employees, although they continue to pay contributions into DC schemes. 

Because this switch from DB to DC is relatively recent, gross assets of DC schemes were only £146bn at the end of 2019. So 94 per cent of the total gross assets in occupational pensions in the UK are still held in DB schemes. 

Most DC money is in pooled funds. While members are offered a menu of investments from which to choose, the majority go for a default lifecycle option. For most of an employee’s career this will involve a bias towards growth assets such as equities. Much of this will be in passive funds that match market indices. So for the purpose of beating inflation, scheme members have a binary dependence on market movements and the skills of active asset managers. Then, as retirement approaches, the portfolio is rebalanced towards so-called safe assets such as nominal and index-linked gilts. 

For those in the period between de-risking and retirement this ineptly and misleadingly named de-risking process is a formula for value destruction at a time of rising inflation because interest rates rise and bond prices fall. As mentioned earlier, the scope for capital loss in index-linked gilts is considerable. 

Of course, scheme members who are about to make the shift away from a growth bias today will have the benefit of cheaper bond market valuations after the recent inflation-induced falls in gilt prices. Yet there is a strong likelihood of further falls if gilt market yields revert to anything remotely near historical norms. 

Rather than taking cash or converting their pension pot into an annuity most scheme members taking the default option will end up with a drawdown arrangement where they can take money out of their fund at times of their own choosing to suit their retirement needs. The asset allocation at retirement will usually consist of a mix of equities and bonds. 

The big worry then is whether stagflation — a combination of inflation with low growth — will play havoc with the portfolio because low growth is bad for equities while inflation is bad for bonds. The benefit of portfolio diversification may therefore be lost. 

Central bank policy switch raises big questions 

Today’s DC scheme members are substantially at the mercy of policy driven markets. After years in which asset prices have been artificially inflated by the asset buying programmes of the central banks — quantitative easing — central bankers have changed gear. In the past fortnight the US Federal Reserve and the Bank of England have raised interest rates while the European Central Bank is widely expected to raise rates in July. All three are expected to shrink their balance sheets, withdrawing their buying power from the bond markets. 

Signals from the Fed weigh heavily on global markets including the UK. According to former New York Federal Reserve president Bill Dudley the Fed wants a weaker stock market and higher bond yields to help tighten financial conditions in the face of soaring inflation. 

The move to quantitative tightening will raise a big question as to what level of yields will be needed to attract non-central bank buyers to fund high government spending after the pandemic. 

Another question is how far inflation expectations have become entrenched or “de-anchored” in the jargon. The big lesson from the 1970s was that if central banks do not act fast to curb surging inflation and expectations become unmoored it takes a bigger recession to cure the inflationary disease. Today’s high inflation numbers suggest that they have left remedial action very late. Engineering a soft landing will be an intricate and dangerous balancing act. 

Misery for annuity holders 

That brings us to the bottom category in the hierarchy of pensions winners and losers. This concerns DC scheme members who have converted their pension pot into fixed annuities over the past dozen years. In effect, they have been stiffed twice over by the central banks. First, because quantitative easing led to overblown bond market prices and thus dismally low yields from which to pay annuities. Second, by going slow in their assault on inflation the central banks have further undermined the real value of already low annuity incomes. 

Fortunately, the number of DC annuitants will be very low because so many scheme members have taken the default lifecycle drawdown option. But that will not mitigate the misery of those who, not unreasonably, sought a secure and predictable retirement income. 

However, the scope for accidents among those who have gone the drawdown route is now very high because of the uncertainties created by soaring inflation. Working out the need for cash in retirement is a challenge in non-inflationary times. Now it is even tougher, with the additional worry that a shortage of care home workers could mean that the cost of late life care will rise much faster than consumer price inflation. 

With the cost of living crisis raging, workers’ pension contributions will be harder to keep up. Former pensions minister Sir Steve Webb points out that there is a real risk that cost of living pressures may lead workers aged 55 and over to take advantage of “pension freedoms” legislation to raid their pension pot before they reach retirement age. In a letter to The Times, he says that with a growing number of workers getting no inflation protection from their workplace pension, the role of the state pension will become even more important. So will the need for next year’s state pension increase to properly compensate for inflation. 

Inflation reallocates risk 

To return to Lenin, capitalism is not at risk from today’s inflationary pressures. But the hierarchy of pensions winners and losers demonstrates the random and arbitrary way in which risk is being reallocated within society. With so many DC scheme members putting too little into their pension pots to secure a half decent retirement income even before this burst of inflation occurred, a looming retirement poverty problem will now be exacerbated. That underlines the imperative need to bring inflation back under control.

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Bitcoin: too good to miss or a bubble ready to burst?

Eva Szalay in The FT

The problem with investing in bitcoin is that it instinctively feels too good to be true. 

The largest cryptocurrency by volume is worth 600 per cent more today than a year ago, soaring from about $7,000 per bitcoin to $54,000 this week, along the way becoming one of the best performing financial assets of 2020. Despite including some extreme price swings, the year-long rally has so far defied fears of a repeat of bitcoin’s spectacular price crash of 2018.

Eye-popping returns are making it difficult for even hardened cryptocurrency sceptics not to consider putting money into bitcoin and many long-term doubters are crumbling. Jamie Dimon, chief of US banking giant JPMorgan, is just one prominent crypto bear who turned bullish in recent years. Recently emerged cheerleaders include Tesla chief Elon Musk and a number of billionaire hedge fund managers who are convinced that as the digital equivalent of gold, bitcoin’s exchange rate against conventional currencies has even further to soar.  

So is bitcoin just a big Ponzi scheme or a genuine investment opportunity? Should retail investors give in to the temptation to pile in? FT Money has spoken to finance professionals inside and outside the cryptomarket and found that opinion remains sharply divided. The recent stellar performance has turned some bears into bulls. But hardcore naysayers warn that a bubble that has grown bigger is still a bubble. 

Even ardent crypto fans are reluctant to wager their life savings on an asset associated with hair-raising levels of volatility. Even among these enthusiasts, many limit their investments to 1-2 per cent of their portfolio. 

Regardless of whether cryptocurrencies turn out to be the digital equivalent of gold in the long run, today they are providing fraudsters with a rich hunting ground.  

Is it really different this time? 

Since the start of January, bitcoin’s value has risen by 85 per cent and in mid-April it hit the latest in a series of record highs at $65,000. Companies that operate in the digital currency sector are attracting a flood of money. In a recent (conventional) stock market flotation, investors valued Coinbase, the cryptocurrency exchange launched less than 10 years ago, at $72bn, putting it equal with BNP Paribas, a French bank with roots stretching back to 1848. 

Young people are in the vanguard of investing. In the UK, millennial and Gen Z investors are more likely to buy cryptocurrencies than equities and more than half (51 per cent) of those surveyed had traded digital currencies, research from broker Charles Schwab shows.  

After a year of spiralling prices, bears warn of the growing risk of a 2018-style collapse. Bitcoin bulls argue that the current rally is different from the 2018 bubble burst, when the price collapsed from above $16,000 to just $3,000. Today, they say, it is driven by demand from professional trading firms and institutional investors whose presence brings stability.  

Not everyone agrees. “It’s not different this time. There are no new eras, despite what the promoters tell you,” says David Rosenberg, a Canadian economist and president of Rosenberg Research. “Asset price bubbles come, bubbles go, but none of them correct by going sideways.” 

In contrast with younger investors, those aged 55 or over remain resolutely on the margins with just 8 per cent of survey respondents in this age group trading digital currencies, the Charles Schwab study found.  

They may be right to do so. Investors globally have lost more than $16bn since 2012 in cryptocurrency-related scams and fraud, according to disclosure platform Xangle. The Financial Conduct Authority, the UK’s financial watchdog, warned this year that investors can lose 100 per cent of their money when punting on cryptocurrencies. It has not sought to block cryptocurrency dealings but has forbidden the sale of derivatives on crypto assets to UK retail customers. 

As crypto markets are unregulated, investors have no one to turn to for help if they fall victim to fraud. Exchanges can turn out to be bogus and their founders disappear. A new coin might turn out to be a tissue of lies. 

“There are a lot of scams and criminal operations that target individuals and it’s very important to recognise that in an unregulated market there is no recourse,” says Ian Taylor, the chief executive of lobby group CryptoUK.  

Another concern for investors is the environmental footprint of cryptocurrencies. The carbon emissions associated with bitcoin equal that of Greece, according to research by Bank of America, because the coins are created or “mined”, in vast computing centres, which burn electricity and generate heat. 

What are the ground rules? 

Crypto specialists say the most important rule for investors is to be prepared to lose all their money. 

On April 13, bitcoin began a sharp decline, its exchange rate shedding 23 per cent in less than two weeks. Marcus Swanepoel, chief executive of Luno, a retail-focused cryptocurrency exchange with 5m-plus customers, says that in some cases they were overstretching themselves. Luno surveyed its clients last year and found that 55 per cent had no other investments.  

“Never spend more money than you can afford to lose,” he says. “It’s very risky, there is no doubt about it.” 

Extreme swings in the exchange rate mean cryptocurrency exposure should be kept at a low proportion of a portfolio, say most mainstream investment analysts. 

“I understand if you want to buy it because you believe the price will go up but make sure it’s a very small portion of your portfolio, maybe 1 or 2 per cent,” says Thanos Papasavvas, founder of research group ABP Invest, who has a 20-year background in asset management. 

Borrowing money to pump up trades with leverage amplifies gains but inflates losses. As there are no official rules, trading platforms allow investors to wager multiples of the money they deposit, inflating the amount at stake by as much as a 100 times.  

“Leverage on a crazy asset class is a recipe for disaster,” says Abhishek Sachdev, a derivatives expert and head of Vedanta Hedging. 

Choosing the right coin is also important. There are hundreds of cryptocurrencies; most are worthless and some are plain scams. Bitcoin is the oldest, most liquid, coin and it is the one that enjoys support due to institutions investing due to its limited supply. 

According to its original computer-based design, only 21m bitcoins will ever exist and 99 per cent of these coins will be mined by 2030. Other cryptocurrencies are not limited in this way and the hundreds of available digital coins all have different characteristics. 

It is also the most expensive per unit but since it can be bought in small increments, there is no requirement to splash out $50,000 or so for a full coin.  

Ethereum is the second most traded cryptocurrency and has benefited from the tailwind of bitcoin’s rally. The technology behind ethereum is also used in a nascent market dubbed decentralised finance, making the coin a relatively safe choice. dogecoin and the likes occupy the riskiest and most illiquid end of the spectrum. 

How do I buy cryptocurrencies and what are the risks? 

In the UK the easiest way to access cryptocurrencies is to buy a portion of bitcoin on an established exchange such as Coinbase. Given that exchanges have suffered outages, been hacked or collapsed, this is the safest approach, though it is more expensive than other exchanges. 

Coinbase typically charges a spread of about 0.50 per cent plus a fee depending on the size of purchase and payment method. 

 Fintech companies such as Revolut also offer a way in for bitcoin buyers, but there is no way to transfer bitcoins from the app elsewhere or into other types of coin. Since they may only sell it back within Revolut, investors only nominally own bitcoin via the app.  

In the US, investors are able to buy shares in diversified cryptocurrency funds such as Grayscale, which can then be bought and sold like other mutual holdings. Institutional investors can also buy into exchange traded products but these are inaccessible for retail investors in the UK. It is possible to buy into products that offer exposure to companies active around blockchain — the public, digital ledger than underlies bitcoin — such as Invesco Elwood Global Blockchain UCITS ETF. These are a bet on technology, however, rather than the cryptocurrency.  

Selling cryptocurrencies also has tax implications. Digital assets count as property for accounting purposes and profits may be subject to capital gains tax. 

Scammers are a growing problem. Some ask investors to send their private keys to their crypto holdings, promising to return with a profit. But once done, there is no way to undo a transfer. 

Lihan Lee, co-founder of Xangle, advises potential investors to check the past records of any crypto investment schemes, while CryptoUK’s Taylor warns of posting about cryptocurrency investment on social media or cold callers promising guaranteed returns.  

“If a stranger walks up to you on the street and says they’ll give you £150 if they can borrow £100, you probably wouldn’t give them the money,” he says. “It’s the same with crypto.”  

Why are institutions getting involved? 

“If it’s on the side of a bus it’s time to buy,” screams an advertisement from Luno in London. 

Many seasoned investors say the ad should say the opposite. If everyone is talking about the same thing, it’s a sure-fire sign that prices have reached unsustainable heights and are about to collapse — as they did in 2018.  

But in the past 12 months companies and institutional investors have cautiously dipped their toes into digital assets. Since central banks around the world responded to the coronavirus pandemic with easy money policies, large asset managers and hedge funds have been looking for ways to protect themselves from a return of inflation and the erosion in value of of some currencies, including the dollar. 

“We’ve seen a step change in institutional interest last year,” says James Butterfill, an investment analyst at digital asset specialist Coinshares. He notes that around $54bn of money is invested across 120 cryptocurrency funds. A year ago, the total figure was $3.5bn across 89 funds.  

“Cryptocurrencies are here to stay,” wrote Christian Nolting, global chief investment officer at Deutsche Bank’s international private bank, in a report.  

Central banks are even exploring the idea of issuing digital alternatives for domestic currencies. To some analysts, central bank digital currencies lend legitimacy to the crypto space, while others believe it is an attempt by central banks to wrest back control of the market. 

“Central banks have always thought that they were key for payments,” says Randy Kroszner, professor of economics at the University of Chicago Booth School of Business. “And now they’ve realised they’re not.” 

But that does not mean that the risks of cryptocurrencies are likely to dissipate any time soon. As the unregulated market bounces through its latest price gyrations, it is a long way off from either stability or security.

Jordan Peterson's Guide to Speaking

 

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60 is the new 80 thanks to Corona

 Patti Waldmeir in The FT

“Better be safe than sorry.” I have never believed that. 

I have lived my first 65 years often turning a blind eye to risk. I lived in China for eight years, enduring some of the worst industrial pollution on earth, despite having asthma. I risked damaging the lungs of my then small children by raising them in a place where their school often locked them in air-purified classrooms to protect them from the smog. 

Before that, I lived for 20 years in Africa, refusing to boil water in areas where it needed boiling, eating bushmeat at roadside stalls — not to mention the escapades that I got up to as a young woman in the pre-Aids era. 

But now, as I peer over the precipice into life as a senior citizen, coronavirus has finally introduced me to the concept of risk. Part of it is the whole “60 is the new 80” paradigm that the pandemic has forced on us — but most of it is that, whether I like it or not, I fit squarely in the category of “at risk” for severe illness or death if I catch Covid-19. 

I have diabetes, asthma and am finishing my 65th year. I don’t live in a nursing home, a jail, a monastery or a convent (as does one close friend with Covid-19), but according to the US Centers for Disease Control and Prevention (CDC), I still qualify as high risk because of my underlying conditions and age. 

So what do I — and people like me, I am far from alone — do now that the world is reopening without us? I’ve got some big decisions to make in the next few days. My youngest child is moving back to our flat outside Chicago after a month living elsewhere: does one of us need to be locked in the bedroom? Do I have to eat on the balcony for two weeks? 

There is no shortage of people, not least President Donald Trump, telling me that all this is simple: vulnerable people should just stay home. But what if they live with other people? What if those people have jobs? And what about our dogs? Our two old mutts are overdue for a rabies shot because the vet was only seeing emergencies. Is it safe for me to take them in now? Can my kids go to the dentist, and then come home to live at close quarters with me? 

I asked several medical experts these questions, and they all offered versions of “we haven’t got a clue”. Robert Gabbay, incoming chief scientific and medical officer of the American Diabetes Association, was the most helpful: “Individuals with diabetes are all in the higher-risk category but even within that category, those who are older and with co-morbidities are at more risk — and control of blood glucose seems to matter. 

“You are probably somewhere in the middle” of the high-risk category, he decided. My diabetes is well controlled and I don’t have many other illnesses. “But your age is a factor,” he added. Up to now, I’ve thought I was in the “60 is the new 40 crowd”: now I know there is no such crowd. 

The head of the Illinois Department of Public Health underlined this at the weekend when she gave her personal list of Covid dos and don’ts, including don’t visit a parent who is over 65 with pre-existing conditions for at least a year, or until there is a cure. Dr Ngozi Ezike also said she would not attend a wedding or a dinner party for a year and would avoid indoor restaurants for three months to a year — despite the fact that Chicago’s indoor restaurants reopen on Friday. 

I turned to the CDC, which initially said it would issue new guidance for “at risk” people last week, but didn’t. This would be the same CDC that I trusted when it said not to wear a mask — though 1.3 billion people in China were masking up. Today China, which is 100 times larger by population than my home state of Illinois, has less than three-quarters as many total pandemic deaths. (Yes, I know China has been accused of undercounting cases, but so has the US.) Masks aren’t the only reason; but they are enough of a reason to erode my trust in what the CDC thinks I should do now. 

It doesn’t help that the CDC website lists “moderate to severe asthma” as one of the primary risk factors for poor coronavirus outcomes — while the American Academy of Allergy Asthma and Immunology says “there are no published data to support this determination”, adding that there is “no evidence” that those with asthma are more at risk. Who’s right? 

I need to know: this weekend is the one-year anniversary of the death of my eldest sibling. I’ve chosen not to make the trip to visit his grave in Michigan. Next month, I turn 65, and I want to spend that day with my 89-year-old father: should we rent a camper van, so we don’t infect his household? I thought about a porta potty for the journey, since public toilets are apparently a coronavirus hotspot. When I started searching for “female urination devices” online, I knew it was time to ditch this new “better safe than sorry” persona I’ve assumed under lockdown. 

Maybe it’s time to remind myself of a fact that I once knew: that life is a risky business, and there is only so much I can do about that. I’ll die when it’s my time — probably not a day before or after, coronavirus or no coronavirus.

Volatility: how ‘algos’ changed the rhythm of the market

Critics say high-frequency trading makes markets too fickle amid rising anxiety over the global economy  writes Robin Wigglesworth in The FT

Philippe Jabre was the quintessential swashbuckling trader, slicing his way through markets first at GLG Partners and then an eponymous hedge fund he founded in 2007 — at the time one of the industry’s biggest-ever launches. But in December he fell on his sword, closing Jabre Capital after racking up huge losses. The fault, he said, was machines. 

“The last few years have become particularly difficult for active managers,” he said in his final letter to clients. “Financial markets have significantly evolved over the past decade, driven by new technologies, and the market itself is becoming more difficult to anticipate as traditional participants are imperceptibly replaced by computerised models.” 

Mr Jabre is not alone. There has been recently a flurry of finger-pointing by humbled one-time masters of the universe, who argue that the swelling influence of computer-powered “quantitative”, or quant, investors and high-frequency traders is wreaking havoc on markets and rendering obsolete old-fashioned analysis and common sense. 

Those concerns were exacerbated by the volatility in financial markets in December, when US equities suffered their biggest monthly decline since the financial crisis, despite little fundamental economic news. And with growing anxiety over the strength of the global economy, tightening monetary policy across the world and an escalating trade war between China and the US, these trades are getting more attention. 

Even hedge fund veterans admit the game has changed. “These ‘algos’ have taken all the rhythm out of the market, and have become extremely confusing to me,” Stanley Druckenmiller, a famed investor and hedge fund manager, recently told an industry TV station. 

It is true that markets are evolving. HFTs dominate the market-making once done by humans in trading pits and the bowels of investment banks. Various quant strategies — ranging from simple ones packaged into passive funds to pricey, complex hedge funds — manage at least $1.5tn, according to Morgan Stanley. JPMorgan estimates that only about 10 per cent of US equity trading is now done by traditional investors. Other markets remain more human, yet are slowly but surely being transformed. 

This has made “the algos” a fashionable bugbear whenever markets tremble like they did in December. Torsten Slok, Deutsche Bank’s chief international economist, put them at the top of his list of the 30 biggest risks for markets, and even Steven Mnuchin, the US Treasury secretary who caused market unease with comments on liquidity late last year, has said the government will study whether the evolving market ecosystem fed the recent turmoil. 

But markets have always been tempestuous, and machines make a convenient, faceless bogeyman for fund managers who stumble. Meanwhile, quants point out that they are still only small players compared with the vastness of global markets. 

“It’s insane,” says Clifford Asness, the founder of AQR Capital Management. “People are missing the forest for the trees. That we trade electronically doesn’t change things, we just deliver the same thing more efficiently . . . It’s just used by pundits and fund managers as an excuse.” 

The recent turmoil has unnerved many investors, but two other debacles stand out as having first crystallised the fear that algorithms are making markets more fickle and fragile. 

At 2:32pm on May 6 2010, US equities suddenly and mysteriously careened lower. In just 36 minutes the S&P 500 crashed more than 8 per cent, before rebounding just as powerfully. Dubbed the “flash crash” it put a spotlight on the rise of small ultra-fast, algorithmic trading firms that have elbowed out investment banks as the integral intermediaries of many markets. 

Michael Lewis, author of Flash Boys, fanned the flames with his book by casting HFTs as mysterious, investor-scalping antagonists “rigging” the stock market. What was once an esoteric, little-appreciated evolution in the market’s plumbing suddenly became the topic of a vitriolic mainstream debate. 

“It was a wake-up call,” says Andrei Kirilenko, former chief economist at the Commodity Futures Trading Commission who wrote the US regulator’s report on the 2010 event and now leads Imperial College London’s Centre for Global Finance and Technology. “The flash crash was the first market crash in the era of automated, algorithmic trading.” 

In August 2015, markets were once again abruptly thrown into a tailspin — and this time volatility-sensitive quantitative strategies were identified as the primary culprits. The spark was rising concern over China’s economic slowdown, but on August 24, the S&P 500 crashed on opening, triggering circuit-breakers — implemented in the wake of the flash crash to pause wild trading — nearly 1,300 times. That rippled through a host of exchange traded funds, worsening the dislocations as they briefly became divorced from the value of their underlying holdings. 

Many investors and analysts blamed algorithmic strategies that automatically adjust their market exposure according to volatility for aggravating the 2015 crash. Targeting a specific level of volatility is common among strategies known as “risk parity” — trend-following hedge funds and “managed volatility” products sold by insurance companies. Estimates vary, but there is probably more than $1tn invested in a variety of such funds.

Risk parity, a strategy first pioneered by Ray Dalio’s Bridgewater Associates in the 1990s, often shoulders much of the opprobrium. The theory is that a broad, diversified portfolio of stocks, bonds and other assets balanced by the mathematical risk — in practice, volatility — of each asset class should over time enjoy better returns than traditional portfolios. Bonds are less volatile than equities, so that often means “leveraging” these investments to bring the risk-adjusted allocation up to that of stocks. As volatility goes up, risk parity funds in theory rein in their exposure. 

However, risk parity funds can vary greatly in the details of their approach, and are generally slower moving than the $300bn trend-following hedge fund industry. These funds surf market momentum up and down, and also use volatility metrics to scale their exposure. When markets are calm they buy, and when turbulence spikes they sell. 

This has been a successful strategy over time. But it leaves the funds vulnerable to abrupt reversals — such as the market tumble last February — and means they can accentuate turbulence by selling when markets are already sliding.

Leon Cooperman, the founder of Omega Advisors, has argued that the US Securities and Exchange Commission should investigate and tame the new “wild, wild west environment in the stock market” caused by these volatility-sensitive strategies. 

“I think your next guest ought to be somebody from the SEC to explain why they have sat back calmly, quietly, without saying anything and allowing these algorithmic, trend-following models to wreak havoc with what has, up to now, been the best capital market in the world,” he told CNBC in December. 

Some quants will grudgingly admit that volatility-targeting is inherently pro-cyclical and can at least in theory exacerbate market movements. But they say critics wildly overestimate just how much money is invested in these strategies, how much they trade, and their impact. 

“Risk parity is basically a passive portfolio with some periodic, counter-cyclical rebalancing. Our volatility targets aren’t perfectly static, but they only change over a 10-year window,” says Bob Prince, co-chief investment officer at Bridgewater. Other risk parity strategies may vary, but overall “it's only ever going to be a drop in the ocean”, he adds. 

Markets had been vulnerable to panicky plunges long before trading algorithms emerged, yet fears over machines seem deeply embedded in our psyche. A 2014 University of Pennsylvania paper found evidence of what it dubbed “algorithm aversion”, showing how human test subjects instinctively trusted human forecasters more than algorithmic ones, even after seeing the algo make fewer and less severe forecasting errors. 

And there are plenty of other potential culprits to blame for exacerbating recent turbulence. Many traditional active funds suffered a battering in 2018. That has led to a rise in investor redemption notices and has forced many to sell securities to meet the end-of-year withdrawals. 

Hedge fund flow data come with a lag, but traditional equity funds saw withdrawals rise to nearly $53bn in the seven days up to December 12, according to data provider EPFR — comfortably the biggest one-week outflow on record. That probably both reflected and exacerbated the slide that left the S&P 500 nursing a 6 per cent loss for 2018. 

At the same time, market liquidity— a broad term denoting how easy it is to trade quickly without causing prices to move around too much — tends to weaken in December, when many fund managers become more defensive ahead of the end of the year. Liquidity can be particularly poor in the last weeks of the year, when bank traders ratchet back how much risk they take on to avoid extra regulatory charges. 

“This makes it more expensive for dealers to perform their essential functions: providing liquidity, absorbing shocks and facilitating the transfer and socialisation of risk,” Joshua Younger, a JPMorgan analyst, wrote in a recent note. “These costs are generally passed on to customers in the form of higher rates on short-term loans, thinner markets and the risk — now realised — of spikes in volatility.” 

That markets are undergoing a dramatic, algorithmic evolution is an inescapable fact. Although some humbled hedge fund managers may unfairly castigate “algos” for their own failings, there are real risks in how some of these different factors can interact at times of market stress. 

HFTs are far more efficient market-makers than human pit traders. Yet the entire sector probably has less capital than just one of the major banks, says Charles Himmelberg, head of global markets research at Goldman Sachs. It means that they tend to adjust their bids aggressively when market mayhem breaks out. 

Under those circumstances, even a modest amount of selling could have an outsized impact. This is an issue both for human traders and quants, but quant strategies are programmed, quick and on autopilot, and if they start pounding an increasingly thin market, it can cause dislocations between buy and sell orders that can produce big gains or falls. 

For example, JPMorgan estimates that the depth of the big and normally liquid S&P 500 futures market — as measured by how many contracts trade close to the current price — deteriorated in 2018, and was exceptionally shallow in the last months of the year. In December it was even worse than the levels seen in the financial crisis. 

“While it is incorrect to say that systematic flows are the sole driver of recent market moves, it would be equally incorrect to say that systematic flows don’t have a meaningful impact,” says Marko Kolanovic, head of quantitative strategy at JPMorgan. 

Poor liquidity and market volatility have always been linked, and it is in practice impossible to dissect and diagnose the myriad triggers and drivers of a sell-off. But modern markets do appear more vulnerable to abrupt dislocations. 

The question is whether anything should, or even could, be done to mitigate the risks. Mr Kirilenko cautions that a mix of better understanding and modest tweaks may be the only conclusion. 

“We just have to accept that financial markets are nearly fully automated,” he says, “and try to make sure that things don’t get so technologically complex and inter-connected that it’s dangerous to the financial system.” 

Anxiety inducing: the triggers for market fears 

Although the recent market slide has reawakened the debate about whether modern machine-driven markets can exacerbate the severity of any volatility, the fundamental drivers of the turbulence are more conventional. As 2018 progressed, investors grew concerned at three factors: signs that the global economy is weakening; the impact of tighter monetary policy in the US and the end of quantitative easing in Europe; and the escalating trade war between the US and China. The global economy started last year on a strong footing, but markets are always focused on inflection points. Since the summer the impact of US tax cuts has appeared to fizzle, European growth has slowed, and China’s decelerating economy has been buffeted by the trade dispute. That has led analysts to trim their estimates for corporate profits in 2019. At the same time, the Federal Reserve raised interest rates four times last year, and has kept shrinking its balance sheet of bonds acquired in the wake of the financial crisis. That has lifted short-term ultra-safe Treasury bill yields to a 10-year high, and undermined the long-term argument that “there is no alternative” which has helped sustain market valuations. As a result, Treasury bills beat the returns of almost every major asset class last year. Goldman Sachs says that over the past century there have only been three other periods when Treasury bills have enjoyed such a broad outperformance: when the US ratcheted up interest rates to 20 per cent in the early 1980s to subdue inflation; during the Great Depression; and at the start of the first world war.