Analyst calls

Are we missing the bigger picture; and this is happening globally?

Over the last few quarters, we are increasingly seeing analysts being off the mark on quarterly earnings estimates. This is not only happening in India but also across most other major geographies. Recently, we have also seen analysts going awfully wrong on estimating the trajectory of oil and copper prices. What is the bigger picture that is emerging?

The Goldman Sachs story… 

Recently, Goldman Sachs decided to do a detailed analysis of how it got two recent trades awfully wrong. The first pertained to its call on crude oil prices and the second pertained to its call on copper prices. What was surprising was not that Goldman got the call wrong. Such bad estimates are quite common in markets. The reason Goldman is getting to the bottom of the matter is that analysts had missed out certain very obvious possibilities.

When the OPEC had decided to cut its oil supply by 1.8 million bpd, Goldman was betting on a rise in crude prices. While it did happen initially, crude oil prices retreated sharply afterwards as stockpiles and higher US output bridged the supply gap. Even in case of copper, while Goldman was bullish, the sharp correction was caused by aggressive de-stocking of copper by dealers at higher levels. This sharp crash in copper prices was something that Goldman Sachs had really not bargained for!

Is this becoming a trend? 

While it may be unfair to arrive at broad conclusions, there is definitely a shift as more brokers are getting their asset class views wrong. There are possibly two reasons for the same. Firstly, the global market has become more integrated and therefore it has become more complex. Estimating commodity price is not as straightforward as taking a view on Chinese demand growth. Second is the role of technology. Global business is currently on the cusp of some radical shifts in the use of tech with the emergence of analytics, cloud and Internet of Things (IOT). All these are likely to create shifts in business that are, perhaps, hard to comprehend for the human mind.

So, what is Goldman doing?

Goldman has taken the lead in relying more on robotic solutions. The need of the hour is to evaluate more data points and more permutations in relationships to arrive at a more credible situation. For example, Goldman has reduced the number of dealers from 600 to just 2 on its global trading desk. These jobs will be increasingly given to robots and algos. We could see a similar trend for analysts too. It is, perhaps, too manpower-intensive and the emerging challenges call for more of data handling and lateral analysis. It is just that the world of financial markets is changing. Welcome to High-Tech Markets!  ©

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