Never Tell Me The Odds

Han Solo famously discounted the math when telling C3PO off – trusting way more in his innate skills than cold, scientific, robotic numbers coming out of a walking/talking computer. (PS – we had a nice infographic on this back in the day), but we seem to be creeping more and more towards the computerized probability shaped world of the protocol droid, especially when it comes to everyone’s favorite mid-March pastime – the ubiquitous bracket pool.

How much do your trust probabilities? If you were to ask someone in Chicago the probability of no snow in Chicago during the month of January and February, they probably would have told you there’s a 0% chance. Well, for those living in Chicago, that actually happened for the first time in 150 years or so (must be Cubs related). Was it highly, highly unlikely? Yes. Improbable? Yes. But as impossible as a 1.00% chance of happening or 0.010% chance of happening makes most of us feel. Not so much.  Therein lies the problem with probability. You could have taken every bit of data ever collected on Chicago weather patterns, and it would have been a safe assurance, that at least one moment in the winter, it would snow in Chicago. We take a 0.10% chance as near certainty of something not happening. Except it did happen.

Back to March Madness and the proliferation of statistics to measure teams ‘odds’ of advancing through the bracket. The beloved data nerd Nate Silver and his FiveThirtyEight website are out with just these types of probabilities, diving into the depths of the march madness bracket like a Big Short guy analyzing mortgages.  At the end of all their number crunching – a nice round number, like the overall number one seed Villanova having a 15% chance of winning the tournament (no word if that includes a penalty for having won it last year, which counter-intuitively makes it that much harder to do this year).

2017-march-madness

This isn’t FiveThirtyEight’s first go around with sports statistics; we highlighted our skepticism on their World Cup predictions back in 2014. These predictions are made based on what is called the Elo ratings (something FiveThirtyEight uses for all their sports predictions) as well as 5 other computer rankings. This accounts for strength of schedule, travel distance, injuries, strength of conference; the list goes on and on.

But the problem with all this data, never mind the six computing programs, is that it’s just past performance. They’re the odds of it happening IF everything that has happened in the past happened the same way again in the future. That’s a mighty big IF, and can help explain why just this sort of predictive odds were off in the US presidential election. FiveThirtyEight gave Hillary Clinton a 71% of winning on election day. That was obviously calculated from statistical data of registered voters, election turnout data based on weather, population sizes of counties, and people who actually get asked who they will vote for. You get “inside information,” in a way. You get to know how the players are going to play the game before the game is played. Nate Silver’s genius 4 years ago when correctly predicting Obama’s 2nd win was stripping out all the biases and noise in those polls and zeroing in on what the right “inside information” was. But genius or not, he can’t make 71% odds the same thing as a win. There was still a 29% probability of the opposite happening.

And now back to basketball. Analyzing the past performance of a basketball team, and their seed positions, and its players isn’t “inside information.”  It’s past performance. And past performance has a nasty way of being a terrible indicator of future performance, especially when you get 12-13 different people on each team, crashing planes, human referees, lucky bounces, and all the rest. At the very least, that’s 22 degrees of freedom put into the mix. Add in what they ate the day before, how their feeling, whether they got in a fight with their significant other, how the guy their guarding smells, and all of the rest; you’re talking hundreds if not thousands of moving parts.

Why do we care?  Because there’s a whole lot of prediction nonsense in the financial markets that is almost continuously wrong:

 

–          Stock price targets

 

–          End of year Dow or S&P targets

 

–          GDP targets

 

–          Unemployment

 

–          Housing Starts

 

–          Crop Reports

 

–          And the list goes on and on…

 

As Nassim Taleb said, “beware the errors of big data.” But we have all this data to use, and we gotta do something with it. As Freakonmics put it in a podcast a few years ago:

It’s impossible to predict the future, but humans can’t help themselves. From the economy to the presidency to the Super Bowl, educated and intelligent people promise insight and repeatedly fail by wide margins.

Having more information about a market, a stock price, global macro trends, or basketball doesn’t guarantee you know the future. That’s why, as they say, they play the game.  And that bears remembering by all as we move further and further towards a world where Amazon orders you more toilet paper and delivers it to your house before you need it – and hedge funds sell JC Penny stock based on satellite images of their parking lots – and cars drive themselves.  If our whole world starts to rely more and more on data driven probabilities, we humans need to understand them a lot better. Our un-scientific graph of how human’s perceive probabilities versus the actual probability of something happening are as follows:

Perceived Probability of Winnin

And of course, if its your own team or you have some preconceived cognitive bias working up there in between your ears, it might even look more like this:

Print

Anyway, enough math and graphs on the eve of March Madness. These predictions and filling out brackets and all the rest are fun, after all, because unlike other “playoffs,”  there are more chances for upsets and your underdog team seems to have more of a fighting chance. Enjoy the madness ! (just don’t let your march madness bleed into your investment philosophy).

 

Disclaimer
The performance data displayed herein is compiled from various sources, including BarclayHedge, and reports directly from the advisors. These performance figures should not be relied on independent of the individual advisor's disclosure document, which has important information regarding the method of calculation used, whether or not the performance includes proprietary results, and other important footnotes on the advisor's track record.

The programs listed here are a sub-set of the full list of programs able to be accessed by subscribing to the database and reflect programs we currently work with and/or are more familiar with.

Benchmark index performance is for the constituents of that index only, and does not represent the entire universe of possible investments within that asset class. And further, that there can be limitations and biases to indices such as survivorship, self reporting, and instant history. Individuals cannot invest in the index itself, and actual rates of return may be significantly different and more volatile than those of the index.

Managed futures accounts can subject to substantial charges for management and advisory fees. The numbers within this website include all such fees, but it may be necessary for those accounts that are subject to these charges to make substantial trading profits in the future to avoid depletion or exhaustion of their assets.

Investors interested in investing with a managed futures program (excepting those programs which are offered exclusively to qualified eligible persons as that term is defined by CFTC regulation 4.7) will be required to receive and sign off on a disclosure document in compliance with certain CFT rules The disclosure documents contains a complete description of the principal risk factors and each fee to be charged to your account by the CTA, as well as the composite performance of accounts under the CTA's management over at least the most recent five years. Investor interested in investing in any of the programs on this website are urged to carefully read these disclosure documents, including, but not limited to the performance information, before investing in any such programs.

Those investors who are qualified eligible persons as that term is defined by CFTC regulation 4.7 and interested in investing in a program exempt from having to provide a disclosure document and considered by the regulations to be sophisticated enough to understand the risks and be able to interpret the accuracy and completeness of any performance information on their own.

RCM receives a portion of the commodity brokerage commissions you pay in connection with your futures trading and/or a portion of the interest income (if any) earned on an account's assets. The listed manager may also pay RCM a portion of the fees they receive from accounts introduced to them by RCM.

Limitations on RCM Quintile + Star Rankings

The Quintile Rankings and RCM Star Rankings shown here are provided for informational purposes only. RCM does not guarantee the accuracy, timeliness or completeness of this information. The ranking methodology is proprietary and the results have not been audited or verified by an independent third party. Some CTAs may employ trading programs or strategies that are riskier than others. CTAs may manage customer accounts differently than their model results shown or make different trades in actual customer accounts versus their own accounts. Different CTAs are subject to different market conditions and risks that can significantly impact actual results. RCM and its affiliates receive compensation from some of the rated CTAs. Investors should perform their own due diligence before investing with any CTA. This ranking information should not be the sole basis for any investment decision.

See the full terms of use and risk disclaimer here.

logo