Posts Tagged ‘Quants’
Thursday, July 12th, 2012
Guest contribution by Ivan Hoff, Ivanhoff Capital
I’ve heard from many traders that they often take decisions based on instincts. Actually, all non-quants use intuition in some form or another. If you are not using a program that takes all signals that your system produces, how do you decide between several equally good looking trading setups with similar risk to reward? Do you take them all or do you concentrate on only a few? The odds are that you are doing the latter and your ultimate choice for capital allocation is subconscious.
Even though we are defined by our decisions, we are often completely unaware of what’s happening inside our heads during the decision-making process.
Feelings are often an accurate shortcut, a concise expression of decades’ worth of experience.
The process of thinking requires feeling, for feelings are what let us understand all the information that we can’t directly comprehend. Reason without emotion is impotent.
This is an essential aspect of decision-making. If we can’t incorporate the lessons of the past into our future decisions, then we’re destined to endlessly repeat our mistakes.
Nothing can replace personal experience:
Unless you experience the unpleasant symptoms of being wrong, your brain will never revise its models. Before your neurons can succeed, they must repeatedly fail. There are no shortcuts for this painstaking process.
This insight doesn’t apply only to fifth-graders solving puzzles; it applies to everyone. Over time, the brain’s flexible cells become the source of expertise. Although we tend to think of experts as being weighed down by information, their intelligence dependent on a vast amount of explicit knowledge, experts are actually profoundly intuitive. When an expert evaluates a situation, he doesn’t systematically compare all the available options or consciously analyze the relevant information. He doesn’t rely on elaborate spreadsheets or long lists of pros and cons. Instead, the expert naturally depends on the emotions generated by his dopamine neurons. His prediction errors have been translated into useful knowledge, which allows him to tap into a set of accurate feelings he can’t begin to explain.
The best experts embrace this intuitive style of thinking. Bill Robertie makes difficult backgammon decisions by just “looking” at the board. Thanks to his rigorous practice techniques, he’s confident that his mind has already internalized the ideal moves. Garry Kasparov, the chess grand master, obsessively studied his past matches, looking for the slightest imperfection, but when it came time to play a chess game, he said he played by instinct, “by smell, by feel.”
Our decision making depends on our expectations. Our expectations are defined by our experience, our memories in a similar situation. Intuition helps only if you have enough experience. The quantity of practice is certainly important, but the quality matters even more. The most effective way to get better at anything is to focus on your mistakes and learn from them. In other words, you need to consciously consider the errors being internalized by your dopamine neurons. This needs to become an ongoing process of constant reminding, because most of what we learn lives in our short-term memory, which by definition doesn’t last long.
WE CAN NOW begin to understand the surprising wisdom of our emotions. The activity of our dopamine neurons demonstrates that feelings aren’t simply reflections of hard-wired animal instincts. Those wild horses aren’t acting on a whim. Instead, human emotions are rooted in the predictions of highly flexible brain cells, which are constantly adjusting their connections to reflect reality. Every time you make a mistake or encounter something new, your brain cells are busy changing themselves. Our emotions are deeply empirical.
This doesn’t mean that people can coast on these cellular emotions. Dopamine neurons need to be continually trained and retrained, or else their predictive accuracy declines. Trusting one’s emotions requires constant vigilance; intelligent intuition is the result of deliberate practice. What Cervantes said about proverbs—”They are short sentences drawn from long experience”—also applies to brain cells, but only if we use them properly.
Source: Lehrer, Jonah; How We Decide – Houghton Mifflin Harcourt. Kindle Edition.
Copyright © Ivanhoff Capital
Tags: Capital Allocation, Concise Expression, Decision Making Process, Emotion, Explicit Knowledge, Fifth Graders, Flexible Cells, Hoff, Instincts, Intuition, Ivan, Knowledge Experts, Neurons, Personal Experience, Puzzles, Quants, Signals, Spreadsheets, There Are No Shortcuts, Unpleasant Symptoms
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Friday, July 6th, 2012
Courtesy of the author, here is the last excerpt from the excellent Dark Pools: High-Speed Traders, AI Bandits, and the Threat to the Global Financial System, by Scott Patterson, author of The Quants. To read the previous excerpts, see here and here.
Haim Bodek rushed out the front door of his home, jumped in his all-black Mini Cooper, and sped to the train station in downtown Stamford, thrash metal pounding from the car’s speakers.
It was the morning of March 25, 2011, his last day on the payroll of Trading Machines. Bodek was scheduled to give a speech later that afternoon at Princeton University, at a conference called “Quant Trading: From the Flash Crash to Financial Reform.”
He was running late. He hadn’t written his speech yet, so he banged it out on his laptop on the train to Princeton.
It was hard. He wasn’t sure what to say. He’d grown so cynical about the market that he’d become convinced that massive reform was required. But he didn’t know if he should be the one to spearhead changing the rules of the game. He worried about his career, whether the new elite at the high-speed firms and exchanges who’d built the market’s digital plumbing in the past decade would attack him and make it hard if not impossible for him to build another trading operation. He had a wife and three young children to support, and he was out of a job. The role of market-reform gadfly wasn’t high on his list of priorities. But his creeping belief that the market had been hijacked kept bugging him, like a bee buzzing in his face. And it wouldn’t go away.
In his talk, Bodek went halfway in calling for major changes. He spoke about the structural issues facing the options market, the evolution of algorithmic trading, and the negative impact stock market structure changes were having on the options industry. There was no mention of toxic order types or 0+ scalping strategies. He wasn’t ready to take on the whole system—yet.
Bodek knew his complaints sounded like excuses for failure. Critics would say he couldn’t take the heat. But he was convinced there was more to it. Exchanges and high-frequency firms had been working hand in glove to design a system that gave an advantage to the speedsters. The speed traders had been working closely with the electronic pools for more than a decade, from Island to BRUT to Archipelago. They’d pushed for more speed, for more information, for new exotic order types. And the pools complied willingly.
It all added up.
In Bodek’s eyes, there was nothing implicitly wrong with what had happened—at least at first. The relationship between high-speed firms and exchanges was in ways beneficial for all investors, he thought. The Bots pushed for better execution. That made the markets better for everyone.
But a problem developed. High-frequency trading became so competitive that on a truly level playing field no one could make money operating at high volumes. Starting in 2008, there had been a frantic rush into the high-frequency gold mine at a time when nearly every other investment strategy on Wall Street was imploding. That competition was making it very hard for the firms to make a profit without using methods that Bodek viewed as seedy at best.
And so a complex system evolved to pick winners and losers. It was done through speed and exotic order types. If you didn’t know which orders to use, and when to use them, you lost nearly every time.
To Bodek, it was fundamentally unfair—it was rigged. There were too many conflicts of interest, too many shared benefits between exchanges and the traders they catered to. Only the biggest, most sophisticated, connected firms in the world could win this race.
One apparent consequence of this hypercompetitive market was its fragility. Because high-speed traders were now competing for wafer-thin profits, they’d grown incredibly pain-averse. The slightest loss was unacceptable. Better to cut and run and trade another day. The result, of course, was the Flash Crash. It was an algorithmic tragedy of the commons, in which all players, acting in their self-interest, had spawned a systemically dangerous market that could threaten the global economy.
Bodek knew he’d made mistakes. He’d wasted months trying to hunt for a bug in the code of the Machine, when the problem was actually abusive order types.
Then he’d started using the order types himself to protect his firm from the abuses. But it felt dirty. He’d become one of the bad guys. One of the tipped-off insiders. Kill or be killed. He didn’t like it, but it had become a matter of survival.
It was not how the market should work. Investors should be re- warded for their intelligence, for being able to make accurate pre- dictions and take risk—not for knowing the location of secret holes inside the plumbing (or, worse, creating the holes).
That was Bodek’s biggest complaint: The Plumbers had won.
Finally, Bodek became determined to reveal what he believed was a corrupt insiders’ game that came at the expense of everyday investors. Was it outright collusion? He didn’t have enough hard information to know for certain. But he believed the exchanges were locked in cutthroat competition, not only with one another but with the dark pools and the internalizers like Citadel and Knight. It was a dynamic that went all the way back to the late 1990s when Island, Archipelago, Instinet, and other electronic networks were engaged in a kill-or-be-killed Darwinian struggle. That struggle led to massive innovation and changes and, to be sure, benefits for nearly all investors.
But something else had changed along the way. The competition had become toxic. The exchanges’ backs were against the wall, and they’d made a deal with the devil at the expense of regular investors.
And so in the summer of 2011, he decided to explain it all to federal regulators. He hired a major law firm to help him use his understanding of toxic order types he’d gained from his exchange contacts while at Trading Machines, combined with the details of his understanding of high-frequency strategies he’d learned from the 0+ Scalping Strategy document, to lay out a road map. The road map detailed his argument that high-speed traders and exchanges had created an unfair market that was hurting nearly all investors.
Were the regulators listening?
Tags: Bandits, Dark Pool, Dark Pools, Digital Plumbing, Excerpt From, Gadfly, Global Financial System, March 25, Market Structure, Mini Cooper, Negative Impact, Options Market, Princeton University, Quant Trading, Quants, Rules Of The Game, Scott Patterson, Stock Market, Structure Changes, Train Station
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Monday, July 2nd, 2012
Courtesy of the author, we present to our readers the following excerpt from Dark Pools: High-Speed Traders, AI Bandits, and the Threat to the Global Financial System, by Scott Patterson, author of The Quants.
In early December 2009, Haim Bodek finally solved the riddle of the stock-trading problem that was killing Trading Machines, the high-frequency firm he’d help launch in 2007. The former Goldman Sachs and UBS trader was attending a party in New York City sponsored by a computer-driven trading venue. He’d been complaining for months to the venue about all the bad trades—the runaway prices, the fees—that were bleeding his firm dry. But he’d gotten little help.
At the bar, he cornered a representative of the firm and pushed for answers. The rep asked Bodek what order types he’d been using to buy and sell stocks. Bodek told him Trading Machines used limit orders.
The rep smirked and took a sip of his drink. “You can’t use those,” he told Bodek.
“You have to use other orders. Those limit orders are going to get run over.”
“But that’s what everyone uses,” Bodek said, incredulous. “That’s what Schwab uses.”
“I know. You shouldn’t.”
As the rep started to explain undocumented features about how limit orders were treated inside the venue’s matching engine, Bodek started to scribble an order on a napkin, detailing how it worked. “You’re fucked in that case?” he said, shoving the napkin at the guy.
He scribbled another. “You’re f*-ked in that case?” “Yeah.”
“Are you telling me you’re f*-ked in every case?” “Yeah.”
“Why are you telling me this?”
“We want you to turn us back on again,” the rep replied. “You see, you don’t have a bug.”
Bodek’s jaw dropped. He’d suspected something was going on in- side the market that was killing his trades, that it wasn’t a bug, but it had been only a vague suspicion with little proof.
“I’ll show you how it works.”
The rep told Bodek about the kind of orders he should use— orders that wouldn’t get abused like the plain vanilla limit orders; orders that seemed to Bodek specifically designed to abuse the limit orders by exploiting complex loopholes in the market’s plumbing. The orders Bodek had been using were child’s play, simple declarative sentences sent to exchanges such as “Buy up to $20.” These new order types were compound sentences, with multiple clauses, virtually Faulknerian in their rambling complexity.
The end result, however, was simple: Everyday investors and even sophisticated firms like Trading Machines were buying stocks for a slightly higher price than they should, and selling for a slightly lower price and paying billions in “take” fees along the way.
The special order types that gave Bodek the most trouble—the kind the trading-venue rep told him about—allowed high-frequency traders to post orders that remained hidden at a specific price point at the front of the trading queue when the market was moving, while at the same time pushing other traders back. Even as the market ticked up and down, the order wouldn’t move. It was locked and hidden. It was dark. This got around the problem of reshuffling and rerouting. The sitting-duck limit orders, meanwhile, lost their priority in the queue when the market shifted, even as the special orders maintained their priority.
Why would the high-speed firms wish to do this? Maker-taker fees that generate billions in revenue for the speed Bots every year. By staying at the front of the queue and hidden as the market shifted, the firm could place orders that, time and again, were paid the fee. Other traders had no way of knowing that the orders were there. Over and over again, their orders stepped on the hidden trades, which acted effectively as an invisible trap that made other firms pay the “take” fee.
It was fiendishly complex. The order types were pinned to a specific price, such as $20.05, and were hidden from the rest of the market until the stock hit that price. As the orders shifted around in the queue, the trap was set and the orders pounced. In ways, the venue had created a dark pool inside the lit pool.
“You’re totally screwed unless you do that,” the rep at the bar said. Bodek was astonished—and outraged. He’d been complaining for months about the bad executions he’d been getting, and had been told nothing about the hidden properties of the order types until he’d punished the it by reducing the flow he send to it. He was certain they’d known the answer all along. But they couldn’t tell everyone—because if everyone started using the abusive order types, no one would use limit orders, the food the new order types fed on.
Bodek felt sick to his stomach. “How can you do that?” he said.
The rep laughed. “If we changed things, the high-frequency traders wouldn’t send us their orders,” he said.
* * *
Tags: Bad Trades, Bandits, Dark Pool, Dark Pools, Excerpt From, Global Financial System, Goldman Sachs, High Frequency, Ked, Launch, Quants, Riddle, Runaway Prices, Schwab, Scott Patterson, Sip, Stock Market, Stock Trading, Suspicion, Ubs, Undocumented Features
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Wednesday, August 17th, 2011
`by Chris Brightman, Research Affiliates
Oliver Wendell Holmes’ 1858 poem “The Deacon’s Masterpiece”1 describes a perfected one-horse “shay,” a highly engineered carriage designed so that the failure of a single part could not cause an untimely breakdown. By eliminating the weakest links, the carriage performs flawlessly, at first. But the shay does not have a happy ending. It suddenly disintegrates with all the parts failing at once, leaving its rider dazed atop a pile of rubble. Holmes—the father of the eminent U.S. Supreme Court Justice— mocked the pseudo-scientific efforts of the overeducated Deacons of his day to engineer impractical structures.
In our domain, the Deacons are quants (financial engineers) and their Masterpiece is an overly complex quantitative investment strategy. The second week in August marks the four-year anniversary of the quant meltdown of 2007. While the events of 2008, including nationalization of Fannie Mae and Freddie Mac, the failure of Lehman, the bailout of AIG, creation of TARP, etc., have rightly received more scrutiny, August 2007 foreshadowed the global financial crisis and deserves more attention by today’s investors. Analyzing the underlying causes of the quant meltdown helps reveal the perils of complex quantitative strategies and highlights the difference between transparent and rules-based alternative beta strategies such as the Fundamental Index® methodology and newer optimized approaches.
The Quant Meltdown
During the week of August 6, 2007, many large and previously successful hedge funds were forced to de-lever their portfolios and liquidate commonly held securities, resulting in
simultaneous drawdowns of 30%, 50%, or worse. To make matters worse, these investments had been sold as risk-controlled and uncorrelated to the market. Khandani and Lo concluded that a “… deadly feedback loop of coordinated forced liquidations leading to deterioration of collateral value took hold during the second week of August 2007, ultimately resulting in the collapse of a number of quantitative equity market-neutral managers, and double-digit losses for many others.”2 Quantitatively managed enhanced index funds experienced similar simultaneous traumas, though the magnitude of losses was lower due to the lack of leverage.
None could have forecast the precise timing of the sudden liquidation of a large trading desk that catalyzed the quant meltdown.3 But should we have been surprised that those funds failed catastrophically? After all, the quant funds of 2007 shared the same structural flaws as the highly engineered financial trading strategies that caused the stock market crash in 1987 and the implosion of Long-Term Capital Management in 1998.4
Inside the Black Box
To help avoid future meltdowns in our portfolios, we need to look inside the black box of quant strategies. Simply put, quants use advanced statistical methods and high frequency data to create complex financial models. With experience, skill, and some luck, a few of these models successfully forecast future security price changes. In the short term, these strategies provide consistent trading profits and gather assets into associated funds. Consistent profits can hide inherent risks, however. Most complex quant strategies have proven to be unstable. Markets evolve in response to the creation and adoption of these strategies. At first, the identified predictability in security price movements is reinforced as funds using the quant model, along with similar funds using similar models, begin buying and selling the same securities. Early success and clever marketing attracts large flows into the funds, which, in turn, drives the prices of securities held by these funds to unsustainable extremes. The result is a brittle price structure awaiting the inevitable crisis.
Leverage creates an even more toxic brew. In the years leading up to the quant meltdown in August 2007, the same models used to manage enhanced index funds (with relatively low tracking errors and high information ratios) were increasingly employed to create levered absolute return-oriented long/short funds. To facilitate the use of leverage, risk models were used to minimize country, sector, and other common factor risks. With all the risk seemingly wrung out of the strategy, ever more capital and leverage were applied.
Paradoxically, quantitative risk management was part of the problem. While risk models are useful tools for measuring risk, using models to tightly control risk is misguided and dangerous. Because no model is, or ever can be, a complete description of the complex dynamic system that is a market, all risk models fail to capture some risk. By eliminating all of the risks measured by their models, the quants transferred the risk in their funds into the areas their models could not measure and they did not understand.
Quant strategies produce remarkable profits in the early stages. But inevitably, the process becomes unstable and often ends with violent illiquidity events, such as the stock market crash of 1987, the Long-Term Capital Management-induced crisis in September 1998, and the quant meltdown in August 2007. The largest losses in those episodes were suffered by the most recent investors who were attracted by dazzling early performance records. Instead of consistent profits, the later investors were stuck with shocking losses realized during fund liquidation as investors fled from the imploding strategies.
As Harry Markowitz stated in the middle of the crisis, “…the layers of financially engineered products… combined with the high levels of leverage, proved to be too much of a good thing.”5
Fundamental not Quant Only four years after the last quant meltdown, over-engineered quantitative investment strategies are back. The latest incarnation is complexly optimized alternative betas. Such strategies attempt to engineer indices with the lowest possible volatility, the highest possible Sharpe ratio, or the maximum possible diversification. The more complex the engineering, the better the model performs in the backtest. As investors begin to adopt such narrow indices, early performance may be rewarding. Fund inflows will create buying and selling pressure on the same narrow set of securities. This pattern will create a brittle price structure resembling the Deacon’s Masterpiece and will set the stage for the next wreck.
Recognizing the trouble with quants, should we eschew quantitative study of security price movements and abandon risk models? Of course not! Advanced statistical methods are invaluable tools to help us understand securities markets. Likewise, risk models help us measure, monitor, and decompose the risks in our portfolios. For example, with regard to the Fundamental Index methodology, we use quantitative methods to demonstrate how and why companies with low market prices relative to fundamental measures of company size provide higher returns than companies with high market prices relative to fundamentals. We use risk models to examine whether and how value priced companies have different risk characteristics than other companies.
The Fundamental Index methodology is far less complex and therefore less risky than a highly engineered quant model. Fundamental weights are simple, logical, and stable. Fundamental Index portfolios are transparently constructed and broadly diversified. The Fundamental Index strategy uses the time-tested technique of systematic rebalancing to capture the long-term return premium offered by the market’s excess volatility.
The following passage from Holmes’ poem descries the end of the one-horse shay. But it could easily be a fitting narrative to the quant strategies during that fateful week in August 2007.
“…it went to pieces all at once, —
All at once, and nothing first, —
Just as bubbles do when they burst.
End of the wonderful one-hoss shay.
Logic is logic. That’s all I say.”
The performance of Fundamental Index strategies may break down occasionally over the long winding road to investment success, just as traditional index funds can create some nasty surprises. However, these setbacks are just that and eventually the Fundamental Index strategy’s simple and stable rebalancing process puts the portfolio back on track. That’s our logic. What do you say?
1. Oliver Wendell Holmes, 1890, The Deacon’s Masterpiece or The Wonderful “One-Hoss Shay”: A Logical Story, New York: Houghton, Mifflin and Company. Illustrations by Howard Pyle.
2. Amir E. Khandani and Andrew W. Lo, 2007, “What Happened to the Quants in August 2007?” Journal of Investment Management, vol. 5, Fourth Quarter
3. Khandani and Lo, 2007.
4. Richard Bookstaber, 2007, A Demon of Our Own Design: Markets, Hedge Funds, and the Perils of Financial Innovation, New York: Wiley.
5. Harry Markowitz, 2008 “The Father of Portfolio Theory on the Crisis,” Wall Street Journal, November 3. http://online.wsj.com/article/SB122567428153591981.html?mod=djemEditorialPage
Copyright © Research Affiliates
Tags: Bailout, Collateral Value, Deacons, Fannie Mae, Fannie Mae And Freddie Mac, Feedback Loop, Financial Engineers, Global Financial Crisis, Hedge Funds, Index Methodology, Investment Strategy, Liquidations, Meltdown, Nationalization, Oliver Wendell Holmes, Quantitative Investment, Quants, Research Affiliates, Shay, Supreme Court Justice
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Thursday, March 5th, 2009
This post is a guest contribution by Niels Jensen*, chief executive partner of London-based Absolute Return Partners.
Many of today’s policy proposals start from the view that “greed” and “incompetence” and “poor risk assessment” are the ultimate source of what went wrong. In fact, they were not the true cause at all. Moreover, even if they had been, it is fatuous to think that we will now create a post-crash generation of bankers and traders who are not greedy, much less a new generation of quants who will be able to assess and manage risks much better than “the idiots” who have brought us to the current abyss. Greed cannot be exorcised. Nor can the inherent inability of any quants to determine the “true” probability distributions of all-important events whose true probabilities of occurrence can never be assessed in the first place.”
Woody Brock, SED Profile, December 2008
Policy mistakes “en masse”
The last few weeks have had a profound effect on my view of politicians (as if it wasn’t already dented). All this talk about capping salaries for senior bank executives is quite frankly ridiculous. It is Neanderthal politics performed by populist leaders. That Gordon Brown has fallen for it is hardly surprising but I am disappointed to see that Barack Obama couldn’t resist the temptation. The mob wants blood and our leaders are delivering in spades. The stark reality is that we are all guilty of the mess we are now in. For a while we were allowed to live out our dreams and who was there to stop us? Policy mistakes – very grave mistakes – permitted the situation to spin out of control. From the U.S. Federal Reserve Bank under the stewardship of Alan Greenspan being far too generous on interest rates to the British Chancellor of the Exchequer – who now happens to be our Prime Minister – advocating ‘Regulation Light’.
Policing must improve
If you really want to prevent a banking crisis of this magnitude from ever happening again, the focus should be on the way banks operate and not on how much they pay their staff. And, within that context, any discussion must start and end with how much leverage should be permitted. The French have actually caught onto that, but their narrow-mindedness has driven them to focus on hedge funds’ use of leverage which is only a tiny part of the problem. It is the gung ho strategy of banks which brought us down and which must be better policed. And guess what; if banks were better policed – and leverage restricted – then profits, even at the best of times, would be much smaller and there would be no need to regulate bankers’ compensation packages.
It is pathetic to watch our prime minister attacking the bonus arrangements of our banks when the UK Treasury, on his watch, spent £27 million pounds on bonuses last year as reward for delivering a public spending deficit of 4.5% of GDP at the peak of the economic cycle. Even my old mother understands that governments must deliver budget surpluses in good times, allowing them more flexibility to stimulate when the economy hits the wall. What Gordon Brown has done to UK public finances in recent years is nothing short of criminal.
So, with that in mind, let’s take a closer look at the European banking industry. The following is not pretty reading. I have rarely, if ever, felt this apprehensive about the outlook. So, if the crisis has made you depressed already, don’t read any further. What is about to come, will make your heart sink.
More leverage in Europe
Let’s begin our journey by pointing out a regulatory ‘anomaly’ which has allowed European banks to take on much more leverage than their American colleagues and which now makes them far more vulnerable. In Europe, unlike in the US, it is only risk-weighted assets which matter to the regulators, not the total leverage ratio. European banks can therefore apply a lot more leverage than their US counterparties, provided they load their balance sheets with higher rated assets, and that is precisely what they have been doing.
That is fine as long as you buy what it says on the tin. But AAA is not always AAA as we have learned over the past 18 months. Asset securitisations such as CLOs proved very popular amongst European banks, partly because they offered very attractive returns and partly because Standard & Poors and Moodys were kind enough to rate many of them AAA despite the questionable quality of the underlying assets.
Now, as long as the economy chugs along, everything is dandy and the AAA-rated assets turn out to be precisely that. But we are not in dandy territory. Many asset securitisation programmes are in horse manure to their necks, so don’t be at all surprised if European banks have to swallow further losses once the full effect of the recession is felt across Europe. The two largest sources of asset securitisation programmes are corporate loans and credit cards. Senior secured loans are still marked at or close to par on many balance sheets despite the fact they trade around 70 in the markets. The credit card cycle is only beginning to turn now with significant losses expected later this year and in 2010-11.
Not much of a cushion left
Citibank has calculated that it would only take a cumulative increase in bad debts of 3.8% in 2009-10 to take the core equity tier 1 ratio of the European banking industry down to the bare minimum of 4.5%. By comparison, bad debts rose by a cumulative 7% in Japan in 1997-98. One can only conclude that European banks are very poorly equipped to withstand a severe recession. Seeing the writing on the wall, they are left with no option but to shrink their balance sheets. Despite talking the talk, banks will use every trick at their disposal to reduce the loan book. No prize for guessing what that will do to economic activity.
The wheels are coming off
But that is not the whole story. It is not even the most worrying part of the story. For the true horror to emerge, we need to turn to Eastern Europe for a minute or two. Nowhere has the credit boom been more pronounced than in Eastern Europe. And nowhere is the pain felt more now that credit has all but dried up. One measure of the credit fuelled bonanza is the deterioration of the current account across the region. Credit Suisse has calculated that in four short years, from 2004 to 2008, Eastern Europe’s current account went from +6% to -6% of GDP. That is a frightening development and is likely to cause all sorts of problems over the next few years.
Meanwhile Western European banks, eager to milk the opportunities in the East after the iron curtain came down, have acquired many of the region’s banks (see chart 1). Now, with many Eastern European countries in free fall, ownership could prove disastrous for an already weakened banking industry in the West.
Chart 1: Western European Ownership of Eastern European Banks
The problem is widespread
To make matters worse, the problems in the East are beginning to look systemic. Credit Suisse has produced an interesting scorecard where they rank a number of countries around the world on factors usually taken into consideration when assessing the credit quality of sovereign debt (see chart 2). At the top of the tree (i.e. the worst credit score) you find Iceland – hardly surprising considering their current predicament. More importantly though, of the next 14 countries on the list, 8 are Eastern European – not what you want to hear if you are an already undercapitalised European bank with huge exposure to Eastern Europe.
Swedish banks are already reeling from their exposure to the Baltic countries. Austrian banks are in even worse shape, having been the most acquisitive of any European banks. Some Italian banks could be dragged under by their Eastern European exposure and even the conservative banking sector in Switzerland doesn’t look like it can escape the mayhem.
Worst of all, the problems in the East are just about to unfold at a point in time where the European banking industry is bleeding heavily from massive losses already incurred in other areas. With no access to private funding, banks find it virtually impossible to re-build their capital base with anything but tax payers’ money.
US banks are in less of a pickle. Unlike the subprime debacle which hit both the US and the European banks hard, US banks have little exposure to Eastern Europe. To prove my point, according to the IMF, European banks have 75% as much exposure to US toxic debt as American banks, but 90% of all cross border loans to Eastern Europe originate from Western European banks. And, to add insult to injury, European banks have been much slower than US banks in terms of recognising their losses. Write-offs now total about $750 billion in the US and only about $325 billion in Europe.
Chart 2: Country Vulnerability Scorecard
Click here for a larger image.
The great mortgage show
The problems in Eastern Europe begin and end with their large external debts. In recent years, ordinary people all over the region have converted their traditional mortgages to EUR- or CHF-denominated mortgages. Some have even switched to JPY mortgages. Who can possibly resist 3% mortgages? Didn’t anyone inform them of the risk? As currencies across the region have fallen out of bed in recent months, these mortgages have suddenly become 30-50% more expensive. No wonder the local economy is suddenly tanking.
Chart 3: Eastern Europe’s Net Foreign Liabilities as % of GDP
Credit Suisse has calculated that net foreign liabilities (as a % of GDP) have risen from 47% to 65% in recent months as a direct result of the loss of local currency values (see chart 3 – and don’t ask me why Credit Suisse has included South Africa in Eastern Europe!).
Chart 4: Eastern European versus Asian Crisis
Source: Wall Street Journal
Back in 1997-98 Asia went through a similar currency crisis. However, as you can see from chart 4, Asian current account deficits were much smaller than Eastern European deficits are now. So were debt levels. Despite that, the Asian crisis did enormous damage to the local economy. Eventually Asia came good, primarily because the devalued currencies allowed the Asian countries to export more. Eastern Europe does not share this luxury. With over 90% of the world’s GDP in recession, who are they going to export to anytime soon?
Austria is in greatest trouble
According to the latest estimates from BIS, Eastern European countries currently borrow $1,656 billion from abroad, three times more than in 2005 and mostly denominated in foreign currencies (ouch!). 90% of that can be traced to Western European banks. About $350 billion must be repaid or rolled over this year. Not an easy task in these markets. Austrian banks alone have lent about $300 billion to the region, equivalent to 68% of its GDP according to the Financial Times. A default rate of 10% on its Eastern European loans is considered enough to wipe out the entire Austrian banking system. EBRD has gone on record stating that defaults in Eastern Europe could end up as high as 20%.
An extra $250 billion to the IMF
Hungary, Latvia and Ukraine have already received emergency loans from the IMF and both Serbia and Romania are reportedly considering asking for help. Meanwhile the IMF’s coffers are draining quickly and it has asked leading industrial nations for new funding. At their summit a week ago, EU leaders coughed up an extra $250 billion but nobody said where the money is going to come from. Even if they find the money, it is likely to prove hopelessly inadequate. Our leaders must grow up. Measuring everything in billions is so yesterday. Trillions are the new billions, like it or not.
On the 11th February the Daily Telegraph’s Brussels correspondent Bruno Waterfield wrote an article under the header: “European banks may need £16.3 trillion bail out, EC document warns.” In the article, the reporter revealed that he has seen a secret document produced by the EU Commission which briefed the union’s finance ministers on the true extent of the banking crisis. Less than 24 hours later, the article’s header was changed to “European bank bail-out could push EU into crisis” and two paragraphs had mysteriously disappeared. Here they are:
“European Commission officials have estimated that “impaired assets” may amount to 44pc of EU bank balance sheets. The Commission estimates that so-called financial instruments in the ‘trading book’ total £12.3 trillion (13.7 trillion euros), equivalent to about 33pc of EU bank balance sheets.
In addition, so-called ‘available for sale instruments’ worth £4trillion (4.5 trillion euros), or 11pc of balance sheets, are also added by the Commission to arrive at the headline figure of £16.3 trillion.”
Do yourself a favour – read those two paragraphs again. Newspaper editors do not change content light-heartedly. Did the Telegraph editor receive a call from Downing Street? Or Brussels? Did he have second thoughts about the avalanche that he could possibly instigate? I don’t know and I probably never will. But one thing is certain. If the EU Commission’s estimate of £16.3 trillion of impaired assets is correct, then the crisis is far worse than any of us could ever imagine. Not only would we have to get used to the prospects of a systemic meltdown of our banking system, but entire nations may go down as well.
Public debt to rise and rise
Even if actual losses prove to be much, much smaller (and I sincerely hope so), the banking sector cannot, in the current environment at least, raise sufficient capital to stay afloat, so more, possibly a lot more, tax payers’ money will have to be put forward. This can only mean one thing. Public debt will rise and rise. The official estimate for the UK for next year is already approaching 10% of GDP, an estimate which will almost certainly rise further. We probably have to get used to running 10-15% deficits for a few years, a fact which seriously undermines the notion of government bonds being next to risk-free.
BCA Research has calculated the effect on public debt in a number of countries, as a result of further bank losses being underwritten by tax payers. Obviously, those countries with the largest banking industries (as a % of GDP) will be hit the hardest (see charts 5a and 5b).
Chart 5a & 5b: Eastern Europe’s Net Foreign Liabilities as % of GDP
For that very reason, and as pointed out in last month’s Absolute Return Letter, there is a real risk that investors will demand much higher risk premiums on government debt. Only a few days ago, Ireland issued 3-year bonds at almost 250 basis points over corresponding Bunds. As more and more debt is transferred to sovereign balance sheets, we will likely see the spreads between good and bad paper rise further but we will also witness increasingly desperate measures being applied by the men in power. If they could prohibit short-selling of banks on the stock exchange (which didn’t work), why wouldn’t they consider prohibiting short-selling of government bonds? Not that it would necessarily work any better, but desperate people do desperate things.
Can Germany rescue us?
Most investors remain convinced that Germany will come to the rescue – in my opinion not as simple a solution as widely perceived given the enormity of the crisis. One possible solution which has been mentioned frequently in recent weeks is for all the eurozone nations to get together and start issuing joint bonds. This would undoubtedly help the weaker nations, but the idea was shot down by the German Finance Minister only a few days ago when he said that closer economic harmony across the eurozone would be needed before Germany would be prepared to entertain such an idea.
The most obvious trick left in the book, therefore, is to inflate us out of this mess. With the enormous amounts of public debt being created at the moment, years of deflation a la Japan would be catastrophic. You will never get a central banker to admit to it, but a healthy dose of inflation is probably our best prospect of surviving this crisis. Given this outlook, do you really want to be long euros?
* Niels Jensen has 24 years of investment banking, private banking and asset management experience. He founded Absolute Return Partners LLP and is its chief executive partner.
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