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What Polarized Politics Teaches Us About Stock Market Uncertainty
Excerpted from Ben Hunt's Epsilon Theory blog,
It’s important to respect the power of econometric models. It’s important to work with econometric models. But I don’t care who you are … whether you’re the leader of the world’s largest central bank or you’re the CIO of an enormous pension fund or you’re the world’s most successful financial advisor … it’s a terrible mistake to trust econometric models. But we all do, because we’ve been convinced by modeling’s henchman, The Central Tendency.
What is the The Central Tendency? It’s the overwhelmingly widespread and enticing idea that there’s a single-peaked probability distribution associated with everything in life, and that more often than not it looks just like this:
It’s our acceptance of The Central Tendency as The Way The World Works that transforms our healthy respect for econometric modeling into an unhealthy trust in econometric modeling. It’s what creates our unhealthy trust in projections of asset price returns. It’s what creates our unhealthy trust in projections of monetary policy impact.
It also creates an unhealthy trust in the mainstream tools we use to project risk and reward in our investment portfolios.
I’m not saying that The Central Tendency is wrong. I’m saying that it is (much) less useful in a world that is polarized by massive debt and the political efforts required to maintain that debt. I’m saying that it is (much) less useful in a market system where exchanges have been transformed into for-profit data centers and liquidity is provided by machines programmed to turn off when profit margins are uncertain.
Polarized Politics
The world is awash in debt, with debt/GDP levels back to 1930 levels and far higher than 2007 levels prior to the Great Recession. What’s different today in 2015 as compared to the beginning of the Great Recession, however, is that governments rather than banks are now the largest owners (and creators!) of that debt.
Governments have more tools and time than corporations, households, or financial institutions when it comes to managing debt loads, but the tools they use to kick the can down the road always result in a more polarized electorate. Why? Because the tools of status quo debt maintenance, particularly as they inflate financial asset prices and perpetuate financial leverage, always exacerbate income and wealth inequality. I’m not saying that’s a good thing or a bad thing. I’m not saying that some alternative debt resolution path like austerity or loss assignment would be more or less injurious to income and wealth equality. I’m just observing that whether you’re talking about the 1930s or the 2010s, whether you’re talking about the US, Europe, or China, greater income and wealth inequality driven by government debt maintenance policy simply IS.
Greater income and wealth inequality reverberates throughout a society in every possible way, but most obviously in polarization of electorate preferences and party structure. Below is a visual representation of increased polarization in the US electorate, courtesy of the Pew Research Center. Other Western nations are worse, many much worse, and no nation is immune.
There’s one inevitable consequence of significant political polarization: the center does not hold. Our expectation that The Central Tendency carries the day will fail, and this failure will occur at all levels of political organization, from your local school board to a congressional caucus to a national political party to the overall electorate. Political outcomes will always surprise in a polarized world, either surprisingly to the left or surprisingly to the right. And all too often, I might add, it’s a surprising outcome pushed by the illiberal left or the illiberal right.
The failure of The Central Tendency occurs in markets, as well.
Below is a chart of 3-month forward VIX expectations in December 2012, as the Fiscal Cliff crisis reared its ugly head, as calculated by Credit Suisse based on open option positions. If you calculated the average expectations of the market (the go-to move of all econometric models based on The Central Tendency), you’d predict a future VIX price of 19 or so.
But that’s actually the least likely price outcome! The Fiscal Cliff outcome might be a policy surprise of government shutdown, resulting in a market bearish equilibrium (high VIX). Or it might be a policy surprise of government cooperation, resulting in a market bullish equilibrium (low VIX).
But I can promise you that there was no possible outcome of the political game of Chicken between the White House and the Republican congressional caucus that would have resulted in a market “meh” equilibrium and a VIX of 19.
If you want to read more about the Epsilon Theory perspective on polarized politics and the use of game theory to understand this dynamic, read “Inherent Vice”, “1914 Is the New Black”, and “The New TVA”.
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Nothing but noise to distract the nationalists into appeasement.
The polarization didn't come from nowhere. As the charts demonstrate, the Left went hard left in a big way, got to enact some of their policies with electoral victories, and the blowback was epic once people had to live with the outcomes.
The language from the left is revealing, the right are neo-reactionaries. They call themselves reactionaries. I'll let you ponder what that means about how they view themselves.
The " what if","could be", shit is getting thick...
WTF?> econometric models----lmfao, Is this how CENTRAL BANKS obfuscate their interventions?
It couldn't be over "$21 trillion, of mis-allocated" money printing over the last 5-6 years???
Back in the old old days there were high priests who called for human sacrifices to appease angry gods. Nobody knew quite why, but clearly they must know better, right? So nobody questioned or opposed them.
In the modern era they all became economists.
-NoDebt (Economist by training but I'm feeling much better now.)
Central tendency says nothing whatsoever about the underlying distribution: it is not predicated on the underlying distribution in any way whatsoever. It is simply a measure (or a set of measures, if you prefer) of the first moment of the distribution.
It's also the crudest moment, which is why it's not surprising that the Excel-experts in most quant shops think of it as rocket science or magic.
This is actually what my PhD was kind-of about, with respect to the forecast distributions of the exogenous variables used to 'close' multi-million-equation CGE models... if you feed a non-bijective, nonlinear model the central tendency of its exogenous variables, you get outcomes for the endogenous set about which you can say literally nothing probabilistic, since E[f(X)] !== f(E[X]) in a non-bijective system of equations. In other words, you cannot perform 'one shot' forecasts... you have to perform stochastic simulations, and do enough of them to characterise the distribution of the endogenous variables (the Jacobian of a non-bijective system is not constant, and may change in unpredictable ways due to constraints in the model going from non-binding to binding).
Anyhow... that shit aside:
Anyone with even the slightest formal training in econometrics (or statistics) knows how to test their data for non-normality - for (excess) skewness, kurtosis, and higher moments (and co-moments, and cumulants) - and to adjsut their view of the relevance of the first moment accordingly.
People with less than the slightest training should at least be able to determine whether the mean (first moment), mode (highest point in the PMF) and median (centre point by count) are aligned, and if not, to treat the first moment sensibly.
And lastly: drawing a picture in Excel of the OI by option strike does not constitute an 'econometric model' - however if you wait until the week before expiration and calculate the price level that causes the largest cumulative value of both calls and put to finish worthless (the 'MaxPain' level), you will seldom be wide of the mark. That would almost count as 'econometrics'.
America finishes at the bottom in OECD adult numeracy tables... just sayin'.
Whole lot of useless drivvle from beyond the fence.
Academics fantasize about lots of models and theories that don't work out in the real world. And they get paid a LOT of money to do so.
Incentives. They are paid to publish a lot; they are not paid to be accurate. Quantity over quality.
Fiscal cliff... government shutdown... what a load of nonsense. Do people not realize the government shuts down every night and weekend. The essential functions of government are designed to continue regardless of a government shutdown and the only way we could default on our debt is if TPTB decide to do so for political reasons. There's little to fear in a government shutdown, the've happened many times in the past and people barely notice unless the media decides to force them to notice.
Folks in Venezeula (and other banana republics) made the same bad assumption -- that government would always be there for them.
Actually, a lot of over-educated people in New Orleans (Katrina) and the New York City area (Sandy) assumed that their government would always be there for them...
OOPS!!!
If I'm broke, what's the point sueing me?
We shall continue suing you until you give up and kill yourself.
--> "If I'm broke, what's the point sueing me?"
Its a choice between paying your welfare check or paying their pension check... but to keep up appearances, the bureaucrats have to convict you of something. Any charge will do, as long as it gives us an excuse to default on past promises without losing face.
Can't have people thinking they are just defaulting on promises outright
OK, so the folks on Wall Street who are betting other people's money, and expect (demand?) a taxpayer bailout when the &*)( hits the fan are super bullish...
The folks who think massive debts will (someday) have to be repaid are terrified that someday isn't so far off, and they are super bearish...
A nice bi-modal distribution, one that doesn't fit the academic models that make MANY unrealistic assumptions (like no commissions, no taxes, no bid/ask spread, continuous hedging... its not just the normal distribution assumption that is wrong).
So what have we learned from this? Thousands of people wasted $70,000 per year in MBA programs learning models that don't work in the real world?