Bankers predicting football

So the Football World Cup season is upon us, and this means that investment banking analysts are again engaging in the pointless exercise of trying to predict who will win the World Cup. And the funny thing this time is that thanks to MiFiD 2 regulations, which prevent banking analysts from giving out reports for free, these reports aren’t in the public domain.

That means we’ve to rely on media reports of these reports, or on people tweeting insights from them. For example, the New York Times has summarised the banks’ predictions on the winner. And this scatter plot from Goldman Sachs will go straight into my next presentation on spurious correlations:

Different banks have taken different approaches to predict who will win the tournament. UBS has still gone for a classic Monte Carlo simulation  approach, but Goldman Sachs has gone one ahead and used “four different methods in artificial intelligence” to predict (for the third consecutive time) that Brazil will win the tournament.

In fact, Goldman also uses a Monte Carlo simulation, as Business Insider reports.

The firm used machine learning to run 200,000 models, mining data on team and individual player attributes, to help forecast specific match scores. Goldman then simulated 1 million possible variations of the tournament in order to calculate the probability of advancement for each squad.

But an insider in Goldman with access to the report tells me that they don’t use the phrase itself in the report. Maybe it’s a suggestion that “data scientists” have taken over the investment research division at the expense of quants.

I’m also surprised with the reporting on Goldman’s predictions. Everyone simply reports that “Goldman predicts that Brazil will win”, but surely (based on the model they’ve used), that prediction has been made with a certain probability? A better way of reporting would’ve been to say “Goldman predicts Brazil most likely to win, with X% probability” (and the bank’s bets desk in the UK could have placed some money on it).

ING went rather simple with their forecasts – simply took players’ transfer values, and summed them up by teams, and concluded that Spain is most likely to win because their squad is the “most valued”. Now, I have two major questions about this approach – firstly, it ignores the “correlation term” (remember the famous England conundrum of the noughties of fitting  Gerrard and Lampard into the same eleven?), and assumes a set of strong players is a strong team. Secondly, have they accounted for inflation? And if so, how have they accounted for inflation? Player valuation (about which I have a chapter in my book) has simply gone through the roof in the last year, with Mo Salah at £35 million being considered a “bargain buy”.

Nomura also seems to have taken a similar approach, though they have in some ways accounted for the correlation term by including “team momentum” as a factor!

Anyway, I look forward to the football! That it is live on BBC and ITV means I get to watch the tournament from the comfort of my home (a luxury in England!). Also being in England means all matches are at a sane time, so I can watch more of this World Cup than the last one.


The Necktie Index

I’m currently reading Roger Lowenstein’s When Genius Failed – about the rise and fall of the hedge fund LTCM. So when LTCM was in trouble, the employees there came up with a measure called the “necktie index”. I’m not able to find a good link to it, and unfortunately physical books don’t offer an efficient “Ctrl+F” option so I’ll have to paraphrase and put it here.

The necktie index states that the more senior officers of the company wear neckties, and the more the meetings they attend, the more trouble the company is in.

I think this concept is generally true, and applicable more widely and to all companies. The more the number of employees wear neckties (compared to normal business days), the more the trouble the company is in. The indexing to “normal business days” is important because different companies have different normal dress codes, so normalization is required.

On a related note, I read somewhere that sometime in the beginning of this decade, when most other investment banks had a business casual dress policy, Lehman Brothers insisted that all its employees wear suits and ties to office. And you know what happened to the firm.

Now UBS has released a 43 page dress code, insisting its employees wear ties, among other things. It probably gives you an indication of where the company is headed.

On a less related note, I used to work for a startup hedge fund whose first office was a room inside the office of a fairly large BPO/KPO company in Gurgaon. And every week, “inspirational quotes” from the founders of the BPO/KPO would go up on the walls, along with their photos. And this was fairly well correlated with the decline of the stock price of that company.