black swans

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NEW YORK — After seven straight draws, we’ve finally witnessed a decisive result at the World Chess Championship.

Sergey Karjakin of Russia, the challenger, claimed the first full-point on Monday against titleholder Magnus Carlsen of Norway.

Game 8 was dense and difficult, and with the white pieces, Carlsen may have pressed too hard beyond what at one juncture looked like another draw.

The opening was a fairly staid and initially symmetrical Queen’s Pawn game — nothing surprising for Carlsen, who has in the WCC so far adopted a strategy of boring openings, aiming to test Karjakin in the middle and endgames.

Carlsen had dodged a few bullets in previous games, but his approach caught up with him in Game 8. Karjakin barely made the so-called “time control,” executing the first 40 moves in 100 minutes with just ten seconds to spare.

Perhaps sensing the challenger’s stress, Carlsen pressed on past several drawing chances, but blunders on both sides made for a tense spectacle until Carlsen’s commitment to the win with white became his undoing on move 52.

Here’s the decisive position:

Carlsen Karjakin Game 8

There’s simply too much for Carlsen to cover: the incoming potential knight check of the white king on g4, the black pawn on a2 tying down the white queen because that pawn threatens to put a second black queen on the board, and the black queen locking down the g1 square.

It’s the definition of a hopeless position and evidence of how a draw can swing to win very quickly at this level. FM Mike Klein and GM Robert Hess break the whole thing down in far more authoritative detail than I can at

Carlsen has real trouble now, and he knows it. He stormed out of the postgame press conference when Karjakin was delayed. With only four games remaining, Carlsen must win one to tie and another to retain his title, without going to tiebreaks. This is the big risk of racking up a lot of draws — the pressure is on the player who’s behind to catch up, with games running out.

It was looking as if they 2016 World Chess Champion would be a drawfest. But just like that, it’s a whole new ball game. Karjakin now leads 4.5-3.5. Luckily for Carlsen, Tuesday is a rest day, with play to resume Wednesday at 2PM ET.

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Like everyone else today, I’m reading Katherine Burton’s amazing inside look at Renaissance Technologies, the greatest hedge fund in history.

Among their secrets – hiring non-finance people with science and math backgrounds, avoiding contact with Wall Street at all costs, constantly developing new edges as old ones grow stale – their ability to stick to what they know works is probably a key one. How did they learn this lesson? By “losing” a billion dollars in a few days, how else?

When rivals and former investors are asked how Renaissance can continue to make such mind-blowing returns, the response is unanimous: They run faster than anyone else. Yet all that running hasn’t always kept them on their feet when everyone else stumbled.

In August 2007, rising mortgage defaults sent several of the largest quant hedge funds, including a $30 billion giant run by Goldman Sachs, into a tailspin. Managers at these firms were forced to cut positions, worsening the carnage. Insiders say the rout cost Medallion almost $1 billion—around one-fifth of the fund—in a matter of days. Renaissance executives, wary that continued chaos would wipe out their own fund, braced to turn down their own risk dial and begin selling positions. They were on the verge of capitulating when the market rebounded; over the remainder of the year, Medallion made up the losses and more, ending 2007 with an 85.9 percent gain. The Renaissance executives had learned an important lesson: Don’t mess with the models.

Sudden, sharp drawdowns will frequently have us second-guessing our portfolios. This is only natural – in the heat of the moment, it always looks like something is wrong or that action must be taken. One of the worst things an investor (or advisor) can do is throw away the playbook in response to temporary volatility or unexpected events.

Renaissance is using leverage in their Medallion fund, so they’ve got considerations beyond performance to consider – like the survival of the company. For most investors, this is not the case, so capitulation is always a wrong move.

Don’t mess with the models.

But, although Renaissance has been around for quite some time and weathered a number of storms, you still have to remember Long Term Capital Management, who were brought down by leverage.

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It’s the bread and butter of pundits to speculate what the world might look like after a relatively improbable but potentially disruptive event, like the U.K.’s exit from the European Union or a Donald Trump victory in the U.S. presidential election. The perceived probability of these “black swan” events is pretty high, after all, and contingency plans may be in  order.

It’s useful, however, to remember how the author of “The Black Swan,” Nassim Taleb, framed it in his 2007 book:

“There are two varieties of rare events: a) the narrated Black Swans, those that are present in the current discourse and that you are likely to hear about on television, and b) those nobody talks about, since they escape  models — those that you would feel ashamed discussing in public because they do not seem plausible. I can safely say that it is entirely compatible with human nature that the incidences of Black Swans would be overestimated in the first case, but severely underestimated in the second one.”

Taleb linked this observation to the research of Daniel Kahneman and Amos Tversky showing that people ascribe a greater probability to unlikely events that are discussed with them. The more a person thinks about a scenario, the less impossible it begins to appear.

Recently, journalists, investors and political scientists have discussed a number of “narrated black swans.” In September 2014, it was the possibility of Scotland seceding from the U.K. after an independence referendum. At the end of July 2014, some statistical modelssuggested an almost 50 percent probability of secession. Less than a month later, the same models put it at 5 percent.

A year ago, the exit of Greece from the European Union was the hot subject. The probability of the momentous event reached 50 percent after Greeks voted in a referendum to reject the EU’s reform proposals linked to further aid. By the time the Greek government capitulated and it was clear that the referendum had been just an ineffective bargaining tool, the probability slipped below 10 percent.

Now, the hot topics are the U.K. withdrawal from the EU and a Trump win. The Bookmaker Ladbrokes puts the chances of the U.K. leaving the EU at 31 percent. PredictIt, a political market, cites a 39 percent probability of Trump in the White House. Unless you’re a gambler, these are extremely high odds for two events that are, in fact, highly unlikely.

A popular vote in an established democracy — or a concerted diplomatic effort, as in the case of the Greek exit — is more likely to lead to a reasonable, relatively conservative outcome than to a wild, disruptive one. It’s difficult to recall a true “black swan” election in Europe or in the U.S. in this century, notwithstanding populists’ strong gains in recent years. There have been some upsets and some public opinion swings, but no candidate resembling Trump has won a majority anywhere, and no country voted to break up or leave a major economic alliance. Most people in democratic nations desire stability and will only take their protests so far. It’s basic sanity that makes these countries successful democracies, after all.

Real “black swans” don’t emerge in areas where much public argument and discussion is involved or even useful. Leicester City’s win in the English Premier League, despite initial odds of 1/5,000, was a true “black swan.” The Ukrainian revolution of late 2013-early 2014 was another. President Vladimir Putin’s invasion of Crimea in 2014 was a third. These were events that “you would feel ashamed discussing in public” until they started happening because they were considered too implausible.

News outlets have an interest in assigning higher probabilities to unlikely disruptive events: It makes for better copy. It’s possible that by weighing in with the warnings and the dystopian scenarios, media help keep societies sane and reduce the probability of “narrated black swans.” They may be another safeguard against bad decisions by the public.

Taleb himself  has a low opinion of media and of safe outcomes. In March, he published the following on Facebook:

“The ‘establishment’ composed of journos, BS-Vending talking heads with well-formulated verbs, bureaucrato-cronies, lobbyists-in training, New Yorker-reading semi-intellectuals, image-conscious empty suits, Washington rent-seekers and other ‘well thinking’ members of the vocal elites are not getting the point about what is happening and the sterility of their arguments. People are not voting for Trump (or Sanders). People are just voting, finally, to destroy the establishment.”

That, however, doesn’t fit in with the argument in the book. The probability of this “narrated black swan” is likely overestimated, if only because everybody’s talking about it.

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I will add a position in VRX. Beaten down, hated, maybe it comes back.

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I haven’t had much time to write about economic theory in a couple of years, but this snippet is worth a response.

“People work in order to convert their time into a unit of account,” he said. “We call that money, and it’s an invention that allows us to store time.” Most people have stored little or none. So when they receive money, they quickly purchase necessities; food, shelter, health care. “People who are able to save money inevitably purchase real estate, stocks, bonds – all of which are alternative vehicles for storing time.” One share of Google stores 30 hours of work for the average American, or 30 minutes of copying-and-pasting formation documents for the average hedge fund attorney. “Bill Gates has stored enough time to fund a 1bln person army for 20 years.”

As the gulf between people’s income has grown, the amount of stored time has accumulated in fewer hands. “Wealthy people convert their hours into financial assets so that they can accumulate excess hours relative to their fellow man. But the average worker is simply thinking how to exchange hours for dollars and then exchange those for food.” Central banks face a different problem altogether. They need to get people who’ve saved time to exchange it for something other than clever inventions that store it. They’ve largely failed. So now, everything that stores time is extremely expensive and offers little or negative return, while the pace of economic activity slows. “The problem that we face now is that there is simply too much time that’s been saved. Another way of saying it is that there’s too much capital in the world, in too few hands.”

To restart the system, capital needs to exchange hands or be destroyed, spurring people to rebuild their store of time, rather than just save it. “It is an elemental truth that at some point, through inflation, war, or confiscation and redistribution, this imbalance will correct, and the system will then restart.”

The quote addresses ‘time preferences’. It addresses the choices available to any individual who is involved in an exchange of property rights. This is only addressed tangentially. Property rights are exchanged and stored as ‘money’. This rather begs the question, what exactly is money?

An individual can: [i] exchange money directly, [ii] hold money as cash, [iii] save [invest] money. These are all time preferences.

Investing requires free market interest rates. We do not currently have these as the Central Banks around to world seek to hold nominal interest rates low. There is still however the ‘natural rate of interest’.

In paragraph three, the author asserts that capital needs to be destroyed or change hands. Capital will likely be destroyed, but these are mal-investments.

Mal-investments  are predicated by artificially low nominal interest rates, which, we currently have and have had for quite some time, since the late 1980’s when Greenspan took over the Fed Chair.

Currently we are reaching the end game of artificial rates.

Of course should ZIRP/NIRP end, all business that exists because of these artificial rates, the mal-investments, will likely collapse, which is the destruction of capital that the author refers to.

This would almost certainly lead to a major bear market, which is the bear case. We saw a taste of it in 2008. The unemployment shot through the roof. There are not many ‘depression proof’ industries, the pain is felt everywhere.

Currently, the next internet/housing bubble is most apparent in social media, which relies on advertising revenue for almost 100% of its revenues. This is a problem and is a major destination of current mal-investments.

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In his 2007 book “The Black Swan: The Impact of the Highly Improbable,” finance writer Nassim Nicholas Taleb attempted to educate the public about the danger of rare, unusual events. This is obviously important in the world of finance — asset market crashes come infrequently, but have an enormous impact on investors’ wealth, and potentially on the economy. Taleb implies that human beings underestimate the risk of these so-called black swans — in fact, he started one hedge fund (which closed in 2005), and advised another, based on this thesis. But how often do people low ball the odds of catastrophe? And is it possible that we might do the opposite, overestimating the risk of things like stock-market crashes, pandemics and wars?

The problem with rare events is that they’re almost impossible to predict by looking at the past. Usually, when we want to determine how likely something is, we rely on some variation of a basic, classic procedure. We take the frequency that the thing has happened in the past, and this becomes our guess of how likely it is to happen in the future. If Atlanta has had sunny days 74 percent of the time during the past 50 years, then our best guess for the probability of a sunny day in Atlanta is 74 percent. Usually, we bring in other data, like recent global weather patterns or seasonal variations, to help improve the estimate.

But those guesses come with a lot of uncertainty. The rarer something is — a volcanic eruption or an asteroid strike — the more hazy our projection about its probability becomes. If we only have a short period of history with which to formulate our guesses, the problem is even worse — imagine trying to predict the likelihood of a hurricane hitting Houston based only on the weather report from the previous week. And if we have no good underlying theory of why something happens — for example, nobody really knows what causes stock-market crashes — then our job of estimating the probability is basically hopeless.

This is a very big problem in investing. There are lots of rare events that matter a huge amount — market crashes, regime shifts and bond defaults. We don’t have good theories for why most of these things happen. So statistical analysis, though it can help a little bit, isn’t very effective in assessing the risk of disastrous financial-market events.

What do we do when we have to make a forecast, but the past offers little guidance? We rely on other things — our hunches, gut reactions and untested theories.


In 2007, Harvard economist Martin Weitzman showed how this could explain the high returns we’ve seen in the U.S. stock market during the past few decades. The phenomenon of mysteriously high investment returns, called the equity premium puzzle, has been studied by financial economists for many years, but Weitzman’s explanation is probably the most compelling. When people have only vague notions about the underlying forces driving the stock market, they will change these ideas frequently as events unfold. Those changing guesses represent a kind of risk, which lowers stock prices today, causing them to have a higher return in the future. Essentially, people avoid stocks because they’re afraid they don’t understand what’s going on in the market.

Weitzman shows how people can act like they believe in black swans even if no black swans are actually present. But his model also implies that even if black swans do exist, people will act as if these unusual events occur much more than the historical record indicates.

In other words, Taleb might be wrong — people might beoverestimating, rather than underestimating, the risk of market crashes.

Some recent survey evidence indicates that this might be true. William Goetzmann, Dasol Kim and the Nobel-winning economist Robert Shiller looked at 26 years of survey data, and found that people consistently say they expect things like stock-market crashes and earthquakes to happen more frequently than they really do. This is exactly the opposite of what Taleb might predict.

Of course, survey research like this has to come with a caveat — people are probably not able to precisely report their own guesses about probabilities. But surveys have proven increasingly useful in predicting investor sentiment, so this evidence shouldn’t be discounted.

So what does this mean for investors? It says that simply betting that the market is understating the probability of a crash is unlikely to yield market-beating returns. People following the opposite advice — buying and holding stocks for long periods of time — have done much better over the long run than people who think stocks are consistently overvalued. Maybe the way to make money is acting as if black swans don’t exist, even if they do show up from time to time.

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The mythical Black Swans.

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