Monthly Letter March 2016

A lot of the work we do is trying to connect the dots between observable data points and then predict what they might mean for the future (mosaic approach). Who will bene t and who will lose. It is about analysing data with an open mind and seeing which dots that will be a ected as the dots deviate further from the ini al star ng point. The real challenge and charm with this par- cular process is that the world keeps on changing. Quite a trivial statement, but the world actually changes not just by technology and new mobile applica ons. Some mes indicators that were very reliable have stopped being just that. Madrague has argued for quite some me that a lower oil price and a stronger USD would be helpful for European growth.

Growth has, however, certainly not been as strong as we would have expected given those tailwinds. You can of course argue that growth would have been even weaker without that support, but we don’t think so. To us, it seems that quite a few old economic rela onships are losing their predictable force. Goldman Sachs and Barclays have in the last couple of months come out with reports with the conclusion that changes  in the oil price doesn’t have the same e ect on global growth as it once did. It didn’t hinder growth as much as we all thought when the price raced all the way up to USD 149 per barrel. Neither did it have the es mated posi ve e ect when the price collapsed to below USD 30 just recently.

The economics team at JP Morgan showed that global PMI (Purchasing Manager Index: an indi- cator for economic ac vity) has overes mated global growth by 0.4% for the last 8 quarters. It seems like it is me to change the econometric models, but the really interes ng ques on is why this is happening. We would argue that we are seeing the nega ve side of low interest rate policies across the western world (we think the term developed is out of sync with reality and should be scrapped or expanded). For us at Madrague it means that we are more careful when interpre ng economic indicators and that we follow closely if there are new models to explain and predict the world from the research houses that we interact with.

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