A Level Economics 58: Volatile Prices

Volatile prices refer to significant and unpredictable fluctuations in the prices of goods, services, or financial assets over a short period. These fluctuations often occur due to various factors, including changes in supply and demand conditions, geopolitical events, economic shocks, speculation, or other unforeseen events.

Market participants may experience periods of rapid price increases (price spikes) or sharp declines (price crashes), which can create uncertainty and instability in the affected markets. Volatility can be measured using statistical indicators such as standard deviation or volatility indices, which quantify the degree of price variation.

Now, let's examine how volatile prices can contribute to market failures with relevant examples:

1. Market Failure due to Price Uncertainty: Volatile prices can lead to price uncertainty, making it challenging for producers and consumers to plan and make informed decisions. Uncertainty about future prices can create inefficiencies, as economic agents may delay investments or purchases, leading to suboptimal resource allocation.

   Example: In the agricultural sector, price volatility of crops can make it difficult for farmers to predict their incomes accurately. As a result, some farmers may reduce investments in technology or land, leading to lower agricultural productivity and potential food supply disruptions.

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3. Market Failure due to Information Asymmetry: In situations where some market participants have access to better information than others, price volatility can exacerbate information asymmetry. Parties with superior information may exploit price fluctuations to their advantage, leading to adverse outcomes for less informed participants.

   Example: In financial markets, high-frequency traders may have access to real-time market data, allowing them to take advantage of price fluctuations to execute trades before other market participants. This creates information asymmetry, as retail investors may not have the same access, resulting in unequal market conditions.

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5. Market Failure due to Speculative Behavior: Volatile prices can attract speculative behavior, where individuals or institutions buy and sell assets purely for short-term profit, rather than based on the intrinsic value of the asset. Speculation can lead to market bubbles and bursts, resulting in misallocation of resources and financial instability.

   Example: During the housing bubble of the mid-2000s, housing prices experienced significant volatility due to speculative behavior and risky lending practices. The eventual burst of the bubble led to a financial crisis, causing severe economic consequences.

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7. Market Failure due to Price Distortions: In the presence of volatile prices, firms and consumers may make decisions based on short-term fluctuations rather than long-term economic fundamentals. This can lead to inefficient resource allocation and suboptimal production and consumption decisions.

   Example: In the oil industry, volatile oil prices can lead to price distortions, impacting investment decisions in exploration and production. During periods of high prices, investment may increase, leading to excess capacity when prices eventually decline.

While volatile prices themselves may not be a market failure, they can exacerbate existing market failures or contribute to suboptimal outcomes in certain economic sectors. Effective market regulation, transparency, and stability measures can help mitigate the negative impacts of volatile prices and promote more efficient resource allocation in the economy.

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Price Stabilization Mechanism:

Price stabilization is a government intervention or policy aimed at preventing excessive fluctuations in the prices of essential goods and services. The objective is to stabilize prices and ensure affordability for consumers while providing predictable and fair returns to producers. Price stabilization mechanisms are typically used during periods of extreme price volatility or in response to supply shocks to maintain economic stability and protect vulnerable consumers from sudden price spikes or crashes.

Working of a Price Stabilization Mechanism:

A price stabilization mechanism can be implemented through various methods, including price ceilings, buffer stocks, and market interventions:

1. Price Ceilings: Price ceilings, also known as maximum prices, are government-imposed limits on the maximum price that can be charged for a specific good or service. The government sets the price ceiling below the market equilibrium price to prevent prices from rising beyond a certain level.

Example: During a period of soaring food prices, the government may set a price ceiling on staple food items to ensure affordability for consumers.

2. Buffer Stocks: Buffer stocks involve the creation and management of stockpiles of essential goods by the government. These stockpiles act as a reserve to be released into the market during times of shortage to stabilize prices.

Example: The government may establish a buffer stock of grains and other agricultural commodities to be released when there is a sudden decrease in supply due to adverse weather conditions.

3. Market Interventions: In some cases, the government may directly intervene in the market by buying or selling goods to influence prices. These interventions can be temporary measures to stabilize prices during periods of high volatility.

Example: The government may purchase excess supply of perishable goods from farmers at fair prices during times of oversupply to prevent market prices from plummeting.

Benefits and Limitations of Price Stabilization Mechanisms:

Benefits:

• Price stabilization mechanisms help protect consumers from sudden price spikes, making essential goods more affordable and accessible.
• They provide stability and predictability to producers, ensuring they receive fair returns for their goods.
• These mechanisms can reduce market distortions, maintain economic stability, and promote consumer confidence.

Limitations:

• Price stabilization mechanisms may lead to unintended consequences, such as excess demand or supply distortions in the market.
• The cost of implementing and maintaining price stabilization mechanisms can be significant and may strain government resources.
• In some cases, price controls can discourage investment and innovation in the affected industries.

Conclusion:

A price stabilization mechanism is a government intervention designed to stabilize prices and prevent extreme fluctuations in the market. By employing price ceilings, buffer stocks, or market interventions, governments aim to protect consumers from sudden price shocks and ensure stability in essential markets. However, such mechanisms should be carefully designed and managed to avoid unintended consequences and ensure long-term economic sustainability.

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Guaranteed Minimum Price Scheme:

A guaranteed minimum price (GMP) scheme is a government policy that aims to support producers by ensuring that they receive a minimum price for their goods or services, even if the market price falls below that level. The government intervenes to stabilize prices and protect producers from the risks of price volatility and unpredictable market conditions. GMP schemes are often implemented in agricultural sectors to support farmers and provide them with income security.

Working of Guaranteed Minimum Price Scheme:

The working of a guaranteed minimum price scheme involves the following key steps:

Setting the Minimum Price: The government sets a minimum price for a specific agricultural commodity, which acts as a floor price below which the producers' sales are guaranteed.

Market Monitoring: The government continuously monitors the market conditions and the prevailing prices of the commodity. If the market price falls below the minimum price, the GMP scheme is triggered.

Market Intervention: When the market price falls below the minimum price, the government steps in as a buyer of last resort. It purchases the excess supply from producers at the minimum price to stabilize the market and provide support to farmers.

Creating Buffer Stocks: In some cases, the government may create buffer stocks by stockpiling the purchased commodities. These buffer stocks can be used to release supply during times of shortages or to control price fluctuations.

Example of Guaranteed Minimum Price Scheme:

Consider a situation where the government implements a guaranteed minimum price scheme for wheat. The minimum price for a bushel of wheat is set at $10. If the market price falls below $10 due to factors like oversupply or international competition, farmers can sell their wheat to the government at the guaranteed price of $10 per bushel. This ensures that farmers receive a fair and stable income, even during periods of low market prices.

Benefits and Limitations of Guaranteed Minimum Price Scheme:

Benefits: Provides income stability and support to producers, especially small-scale farmers, during times of market volatility or adverse weather conditions.
Encourages farmers to continue production, knowing they have a guaranteed price for their produce.
Helps to prevent sharp declines in farmers' income and mitigates the risks associated with fluctuating market prices.

Limitations: The cost of implementing a guaranteed minimum price scheme can be substantial and may require significant government funding.
The scheme may lead to the accumulation of surplus stocks if market prices remain consistently below the guaranteed price.
Depending on the design and implementation, the scheme may distort market incentives and hinder efficiency.

Conclusion:

A guaranteed minimum price scheme is a government policy aimed at stabilizing incomes for producers in the face of price volatility and market uncertainties. By setting a floor price and intervening when market prices fall below that level, the scheme provides support to farmers and ensures their economic resilience. However, successful implementation requires careful monitoring and management to strike a balance between supporting producers and maintaining market efficiency.

Information can make you sick

Trader turned neuroscientist John Coates in The FT on why economic crises are also medical ones.

As coronavirus infection rates peak in many countries, the markets rally. There is a nagging worry that a second wave of infections might occur once lockdowns are lifted or summer passes. But for anyone immersed in the financial markets there should be a further concern. Volatility created by the pandemic could itself cause a second wave of health problems. Volatility can make you sick, just as a virus can. 

To get an inkling of what this other second wave might look like, it helps to recall what happened after the credit crisis. That event was both a financial and medical disaster. Various epidemiological studies suggest it may be responsible for 260,000 cancer deaths in OECD countries; a 17.8 per cent increase in the Greek mortality rate between 2010-16; and a spike in cardiovascular disease in London for the years 2008-09, with an additional 2,000 deaths due to heart attacks. The current economic crisis may be far worse than 2008-09, so the medical fallout could be as well. 

Why do financial and medical crises go hand in hand? Many of the above studies focused on unemployment and reduced access to healthcare as causes of the adverse health outcomes. But research my colleagues and I have conducted on trading floors for the past 12 years suggest to me that uncertainty itself, regardless of outcome, can have independent and profound effects on physiology and health. 

Our studies were designed initially to test a hunch I had while running a trading desk for Deutsche Bank, that the rollercoaster of physical sensations a person experiences while immersed in the markets alters their risk-taking. After retraining in neuroscience and physiology at Cambridge University, I set up shop on various hedge fund and asset manager trading floors, along with colleagues, mostly medical researchers. Using wearable tech and sampling biochemistry, we tracked the traders’ cardiovascular, endocrine and immune systems.

My goal was to demonstrate how these physiological changes altered trader performance. Increasingly, though, I came to see that a trading floor provides an elegant model for studying occupational health. 

One remarkable thing we found was that traders’ bodies calibrated sensitively to market volatility. For humans, apparently, information is physical. You do not process information dispassionately, as a computer does; rather your brain quietly figures out what movement might ensue from the information, and prepares your body, altering heart rate, adrenaline levels, immune activation and so on. 

Your brain did not evolve to support Platonic thought; it evolved to process movement. Our larger brain controls a more sophisticated set of muscles, giving us an ability to learn new movements unmatched by any other animal — or robot — on the planet. If you want to understand yourself, fellow humans, even the markets, put movement at the very core of what we are. 

Essential to our exquisite motor control is an equally advanced system of fuel injection, one that has been misleadingly termed “the stress response”. Stress connotes something nasty but the stress response is nothing more sinister than a metabolic preparation for movement. Cortisol, the main stress molecule, inhibits bodily systems not needed during movement, such as digestion and reproduction, and marshals glucose and free fatty acids as fuel for our cells. 

The stress response evolved to be short lived, acutely activated for only a few hours or days. Yet during a crisis such as the current one, you can activate the stress response for weeks and months at a time. Then an acute stress response morphs into a chronic one. Your digestive system is inhibited so you become susceptible to gastrointestinal disorders; blood pressure increases so you are prone to hypertension; fatty acids and glucose circulate in your blood but are not used, because you are stuck at home, so your risks increase for cardiovascular disease. Finally, by inhibiting parts of the immune system, stress impairs your ability to recover from diseases such as cancer, and Covid-19. 

So why the connection with uncertainty? The stress response is largely predictive rather than reactive. Just as we try to predict the future location of a tennis ball, so too we predict our metabolic needs. When we encounter situations of novelty and uncertainty, we do not know what to expect, so we marshal a preparatory stress response. The stress response is comparable to revving your engine at a yellow light. Situations of novelty can be described, following Claude Shannon, inventor of information theory, as “information rich”. Conveniently, informational load in the financial markets can be measured by the level of volatility: the more Shannon information flowing into the markets, the higher the volatility. 

In two of our studies we found that traders’ cortisol levels did in fact track bond volatility almost tick for tick. It did not even matter if the traders were making or losing money; just put a human in the presence of information and their metabolism calibrates to it. Take a moment to contemplate that curious result — there are molecules in your blood that track the amount of information you process. 

Today, with historically elevated volatility, there is a good chance cortisol levels are trending higher. Immune systems could also be affected. When your body is attacked by a pathogen, your immune system coordinates a suite of changes known as “sickness behaviour”. You develop a fever, lose your appetite and withdraw socially. You also experience increased risk aversion. 

Central to the immune response is inflammation, the process of eliminating pathogens and initiating tissue repair. However, inflammation can also occur in stressful situations, because cytokines, the molecules triggering inflammation, assist in the recruitment of metabolic reserves. If inflammation becomes systemic and chronic, it contributes to a wide range of health problems. We found that interleukin-1-beta, the first responder of inflammation, tracked volatility as closely as cortisol. 

Recently we have focused on the cardiovascular system. Working with a large and sophisticated fund manager, we have used cutting-edge wearable tech that permits portfolio managers to track their cardiovascular data, physical activity and sleep. The cardiovascular system similarly tracks volatility and risk appetite.

In short, here we may have a mechanism connecting financial and health crises. On the one hand, fluctuating levels of stress and inflammation affect risk-taking. In a lab-based study, we found that chronically elevated cortisol caused a large decrease in risk appetite. Shifting risk presents tricky problems for risk management — and for central banks. Physiology-induced risk aversion can feed a bear market, morphing it into a crash so dangerous that the state has to step in with asset purchases. On the other hand, chronically elevated stress and inflammation are known to contribute to a wide range of health problems. 

We are not accustomed to combining financial and medical data in this way. But corporate and state health programs should start. 

The markets today are living through a period of volatility the likes of which I have never encountered. March was, to put it mildly, information rich. As a result, there is now the very real possibility of a second wave of disease. Viruses can make you sick, but so too can information.

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.

The end of an era of cheap money?

Nicole Bullock, Eric Platt and Alexandra Scaggs in The Financial Time


For more than a decade, Mike Schmanske made a living trading “volatility” — betting on the size and speed of moves in the US stock market. After 2014, the market was calm for so long that he spent much of his time sailing a Swan yacht. He got his adrenalin flowing in a different way: on his first trip from Bermuda to Newport, Rhode Island, he raced a hurricane back to port and made it with 12 hours to spare. 

Now, a new bout of turbulence is pulling him back to Wall Street. A sharp outbreak of volatility has written more than $5tn off the value of global stocks in less than two weeks and Mr Schmanske is talking to his old trading buddies about getting back into the market. 

“This is the most calls I’ve taken in years,” says Mr Schmanske*, a pioneer of some of the first volatility trading products while at Barclays and now a consultant. “Things were slow. I was literally on a boat a few weeks back.” 

The catalyst for the volatility surge came at 8:30am last Friday when the US government employment report showed a surprisingly strong rise in wages, prompting bond yields to shoot upwards and the price of those bonds to fall. Within hours, the losses in the $14tn Treasury market had spread to stocks, setting the stage for Wall Street’s worst week in two years.** By Thursday, US equities had entered what is known as a correction — a fall of at least 10 per cent. Many investors who had piled into esoteric instruments that enable them to bet on continued calm in the market had been wiped out. 

The ructions over the past week have attracted so much attention because they strike at the question that has haunted markets for the past two years — what happens when the economy returns to normal? Since the financial crisis, markets have been boosted by an unprecedented mixture of ultra-low interest rates and asset-buying by central banks in a bid to fend off the threat of deflation. But with global growth robust and inflation beginning to re-appear, central banks are pulling back. 

The question investors are trying to answer is how much of the sharp drop in share prices is due to a technical reaction driven by a much-hyped niche in the market that bets on volatility, versus part of a broader adjustment to a different economic reality. 

“The system has changed,” says Jean Ergas, head strategist at Tigress Partners, who said the market had made more of a “rethink” than a correction. “This is the unwinding of a massive carry trade, in which people borrowed at zero per cent and put money into stocks for a yield of 2 per cent.” 

The year began on a euphoric note as a large cut in US corporate tax prompted investors to mark up their expectations for earnings growth. The economy was already humming around the world for the first time since the financial crisis. 

At its peak on January 26, the market values of S&P 500 companies had surged by $5tn from a year earlier, while global stocks were up by nearly $14tn. The gains lured small investors into the market, with more than $350bn pumped into equity funds in the year, according to fund tracker EPFR Global. 

But cracks had already appeared in the bond market. Investors were starting to make noise and demand higher yields. Bill Gross and Jeffrey Gundlach — two well-known money managers in fixed-income markets — both declared last month a new era after a 36-year “bull market” in bonds, which had seen yields driven steadily lower. 

It was against that backdrop that markets reacted to last Friday’s news of a 2.9 per cent rise in US wages — not dramatic in a different era but still the largest year-on-year rise since the financial crisis. Inflation fears rose. Investors began marking up the odds that the Federal Reserve could tighten policy by a full percentage point this year, more aggressively than previously thought. Robust growth in Europe and Japan also raised the question of when the European Central Bank and Bank of Japan would begin to remove crisis-era stimulus. 

“Inflation fears running back into the market and hitting basically all assets in a market that had run up significantly is a pretty plausible, simple story,” says Clifford Asness, co-founder of AQR Capital Management. “You do not have to go looking for Alger Hiss in this pumpkin.” 

By the end of last Friday, yields on benchmark 10-year US Treasuries had hurdled above 2.8 per cent for the first time in nearly four years. For the year, yields had risen more than 40 basis points, increasing the appeal of bonds relative to stocks. The Dow Jones Industrial Average lost 666 points — an unsettling omen for religiously minded traders. 

“Optimism over synchronised global growth and supportive macro conditions led to outsized gains in equity markets to start the year,” says Craig Burelle, macro strategies research analyst at Loomis Sayles. “But more recently, some investors worried the economic momentum was too much of a good thing, and optimism gave way to concerns about the future path of inflation and interest rates.” 

Before long, the anxiety had gone global. On Sunday evening, many Americans were watching the Philadelphia Eagles upset the New England Patriots in the Super Bowl: at the same time, Asian markets were opening on Monday with a spike in bond yields. 

“On any other Sunday night you might have been more anxious about what you were seeing,” says Matt Cheslock, a trader at Virtu and a 25-year veteran of the New York Stock Exchange. “The game provided a nice distraction.” 

Monday morning in the US added a new source of uncertainty with the swearing in of Jay Powell as the chairman of the Federal Reserve, bringing a relatively little-known face to lead the central bank. For much of the day, Wall Street avoided serious losses. Then, a big drop seemed to come out of nowhere. About an hour before the closing bell, the Dow slumped more than 800 points in 10 minutes. 

“The adrenalin kicks in,” says Mr Cheslock. “Everyone gets sharper. The complacency is long gone.” 

Customers rushed to log into their accounts at Vanguard, TD Ameritrade, T Rowe Price and Charles Schwab, straining websites. Some were unable to place orders. 

“As the volatility picks up and the indices plummet the rumours start to swell,” says Michael Arone, chief investment strategist at State Street Global Advisors. “Folks are wondering the classic Warren Buffett line about when the tide goes out, you see who is not wearing swimming trunks.” 

Over the past week, the investors who have been left most exposed are those who had made bets on subdued volatility. As share prices slumped, Wall Street’s “fear gauge” — the widely watched Cboe Vix volatility index — spiked. 

Trading strategies that profited from the calm in markets during 2017 quickly unravelled. Two exchange-traded products that enabled investors to bet on low volatility lost nearly all their value on Monday. 

After the bell on Monday, the Vix continued to rise and shares in vehicles related to Vix also fell. 

On Tuesday morning, Nomura, the Japanese bank, said in Tokyo that it would pull a product that was pegged to S&P 500 volatility. Within half an hour, the Nikkei 225 had fallen 2.5 per cent, which, in turn, prompted a bout of selling in bitcoin. The digital currency — worth more than $19,000 as recently as December — dropped below $6,000 just after 2:45am in New York, as traders in London and Frankfurt were getting to their desks. Stock markets in both countries would open 3.5 per cent lower. 

As US investors slept, the turbulence continued. At 4am in New York, a number of exchange traded products related to volatility were halted. By 7:11am, more than two hours before the US open, the Vix volatility index shot above 50 — only the second time it has done so since 2010. The turbulence forced bankers to postpone a number of bond sales planned for the day. Then Credit Suisse said it would close an exchange traded note, known by the ticker XIV — which is designed to move in the exact opposite direction to the Vix each day, and had thus collapsed as volatility rose. 

“People had forgotten that stocks don’t just go up,” says Adam Sender, head of Sender Company and Partners, a hedge fund. “Corrections are a normal process. This was inevitable. Interest rates rising was the trigger, but short-volatility was the fuel.” 

The volatility subsided amid a Tuesday afternoon rally in New York, and world stock markets survived much of the next day without incident. But then at 1pm on Wednesday in New York, signs of nervousness re-emerged. Demand at the auction of US Treasury bonds was weak, a signal that investors were worried about inflation and a rising budget deficit, and would therefore only buy at higher yields. Stocks ended the day in the red, and when investors in Tokyo returned on Thursday, prices dropped quickly. Heavier selling ensued on Wall Street. By Friday morning, the main indices in the US, Germany and Japan were all down more than 10 per cent from their January highs. When trading finally closed for the week after another rollercoaster day, US losses were shaved to about 9 per cent. 

For some, the shock created by the collapse of the volatility products has been salutary. “It’s always good to be reminded of these things with accidents that aren’t of systemic importance to the entire economy,” says Victor Haghani, founder of London’s Elm Partners and an alumnus of Long-Term Capital Management. “It’s a gentle reminder from the market.” 

However, many investors believe the questions raised over the past week go well beyond the products connected to the Vix index. “We’ve gone from a market used to playing checkers — rising earnings, low rates equals higher prices — to being forced to compete in grandmaster three-dimensional chess: worries over growth versus rates, equity valuations, and the strength of the dollar, and now market structure concerns,” says Nicholas Colas, cofounder of DataTrek, a New York research group. 

While some investors talked of a buying opportunity, believing that faster economic growth and a modest uptick in inflation represent a positive backdrop for equities, many headed for the exits. Investors pulled more than $30bn from stock funds in the week to Wednesday, the largest week of withdrawals since EPFR began tracking the data at the turn of the century. 

The slump in share prices put the White House on the defensive, given that President Donald Trump has taken pride in the stock gains under his administration. “In the ‘old days,’ when good news was reported, the Stock Market would go up. Today, when good news is reported, the Stock Market goes down,” he tweeted on Wednesday. “Big mistake, and we have so much good (great) news about the economy!” 

Others were less confident. “This is not yet a major earthquake,” said Lawrence Summers, US Treasury secretary under President Bill Clinton. “Whether it’s an early tremor or a random fluctuation remains to be seen. I’m nervous and will stay nervous. [It is] far from clear that good growth and stable finance are compatible.” 

Some strategists expect the recent declines to lead to further selling, as computer-driven funds that target volatility are forced to shed more equities. Analysts put the amount of automatic selling from the recent turmoil at about $200bn, and more could be on the way unless markets simmer down. 

Jonathan Lavine, co-managing partner of Bain Capital, says a drop in share prices was not a surprise in itself. “It was the ferocity of the move, not triggered by any material news and propelled by a small corner of financial markets,” he says. “You have to ask yourself what would happen in the event of real bad news.”