Raoul Pal: Why Bank Research is Watered Down

Wadhwa:You touched on this a little bit with the bias and sensationalism you see, but in your opinion, what’s wrong with bank research and why?

Pal: Having come from that business myself and understanding what it’s like, bank research is very cautious in how it is written. The inherent bias in bank research is that they don’t really want to be negative because it doesn’t play well to investment banking customers, where a lot of their revenue comes from. You can’t really say things that you mean.  You have to be very cautious of the vested interests, particularly out of the M&A business. So what you end up with is research that doesn’t really play its purpose, which is to get the smartest people in the bank to tell you what’s going on in the world.  It tends to get slightly watered down. And so there’s an opportunity, which is why I have an independent research publication called Macro Investor.  I can speak differently in a different way and I can be free in my thoughts.

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Wadhwa:You’ve talked before about your frustration with the poor forecasting records by the Fed and Wall Street economists. What do you think they are doing wrong and how can they improve?

Pal: People within the industry are incredibly concerned about the Fed using economic models that don’t work in the real world. Model based economics is proven not to work. It’s one of the reasons we got in trouble with the financial crisis.

It’s one of the reasons we have this enormous balance sheet that the central bank has, one of the reasons why rates went negative, it’s all theoretical model based economics. And the real solution I believe is with the advent of big data and the development of behavioral economics, we could be much better in truly understanding how economies actually work by looking at the data and not models. That’s a big shift that needs to come. Aside from that, the other key thing the Federal Reserve forgets is that there is a business cycle. Economies do ebb and flow, and their models never forecast that which is why they are always wrong.