Meta Risk

In the search for competitive advantage in equity analysis large firms are beginning to search far and wide to gain an edge. Data in all forms is being used to draw connections to potential price movements in equities. Intuitively, the increasing accessibility of big data should cause markets to become more efficient, however we have seen that in practice too much efficiency can in fact cause inefficiency.

A recent article in the Wall Street Journal told the story of money managers who, after buying credit card data, opened a short position in Tailored Brands. The problem was that this was not a unique idea, and many other money managers gained access to the same credit card data. Short interest built and after the lack-luster quarterly report managers went to close their positions; a 40% short squeeze ensued.

This of course is not the first instance of a short squeeze occurring, but in our world of increasing amounts of data I believe short squeezes will become more and more frequent in larger market cap companies. The same principal also applies in the inverse manner when big data can assert that a particular asset is no longer worth holding. When many investors move to sell their positions, the asset price drops.

What happens when we take that logic and apply it to hedging? In the world of quantitative risk management many of the models are mostly based off of the same fundamental theories (while they may have some proprietary alterations). This means that at a given point in time they will all tell a similar story. The significance of this is that many larger asset managers will be looking to hedge in the same assets, crowding these assets and creating risk within the hedge itself, or as I like to call it, Meta Risk.

In a recession or pullback environment when asset managers look to balance out performance by selling off hedge assets, it is extremely likely that many other assets managers will be doing the same thing. The rush to the door to lock in gains from these hedges will cause an abundance of sellers, thus dropping the price of the assets. The consequence is unexpected illiquidity when liquidity is desperately need, which may cause a larger unwind.

Will the volatility that we have seen in crowded assets bear its head in popular hedge-type assets? During the crash of 2008 quantitative modeling was not nearly as prevalent, and from 2008 to the present we have not seen an extremely significant downturn in financial markets. We have hit speed bumps and pullbacks, but none that would merit Meta Risk. It is by no means a certainty that we are at a point where Meta Risk will impact markets, but it is a possibility that we should be cautious of.