HIDDEN FACTORS On a day when NOVO’s FLOW data (GLP-1) is rocking the med tech complex ($DVA -19%, $INSP -13%), I thought I’d comment on a concept that I’ve been thinking about a lot for the last 8 years - the concept of hidden factors and how thematic factors seem to be increasingly distorting price discovery in the equity markets Classic Tiger-style investing is the ultimate “long winners, short losers” or “long the future, short the past” approach (vastly simplified). Hedge out ~half your market exposure and your alpha is the materialized expression of your structural views on industries & business models with a slight beta tailwind. The 1995-2021 iteration of Tiger cubs generated loads of alpha from long secular trades (rise of e-commerce, SAAS software, online advertising) and short secular trades (decline of old media, bricks & mortar retail). That “winners vs. losers” concept has been a durable source of alpha generation for decades (with increasingly violent reversals). In my observation, as the world of institutional investing has become more “factor aware”, these naked winners vs. losers trades have become more difficult for many to express as they carry a lot of factor risk (generally long LT Mo and large industry group overhangs). LPs increasingly see factor risk as “beta” for which they prefer to not pay 2% & 20%. So there has been a shift here, certainly I believe influenced by the rise of the multi-managers but I also think due to the scale of some large macro-thematic investors and rise of thematic ETFs. The prevalence of custom baskets from the sell-side and thematic ETFs I believe have made themes easier than ever to express. In the classic 8-15 factor equity risk model, these custom baskets are not captured. I.e. there is no “gen AI” factor nor a “GLP-1” factor - though there could be. The beauty of most equity risk models is that these thematic factors become hidden factors. And in the search for relative value and spread generation, these custom factors can be a large source of prospective spread. I’ll give you an example. $MDT and $ABT at one point had pretty similar factor profiles - size, momentum, dividend yield, etc. And a long $MDT, short $ABT trade was a pretty “high idio” or tight pair - the sort of trade that factor models love. And during many periods in the businesses, the fundamental drivers were similar. However, coming out of COVID, ABT had meaningful COVID testing exposure and MDT had deferred procedure bounce back potential. In that instance, a long MDT, short ABT trade actually would allow the PM to express a meaningful theme without bearing factor risk. The theme has to be correct of course - but catching those thematic trades can be powerful. Fast forward to Gen AI and Ozempic / GLP1s. These are both thematic trades that can be expressed in a tight risk model framework with hedges that have a similar factor profile. Nailing these paired off thematic trades is likely one of largest sources of market-neutral alpha. And it’s one of my top pieces of advice for new pod PMs - identify the hidden factors, the differentiation in business mix or thematic driven fundamental outcomes that look paired off in the risk model. Those are the trades where the spread can be 20-50%+ over a sub-12m period of time, and can make your year in a vol targeted environment because you can size them so large. So what does this mean for broader price discovery? Since these “hidden factors” are so potent, my sense is they are getting more crowded. With more crowding, the likelihood of them overshooting seems higher to me. I’m already hearing from my HC friends that this GLP-1 theme is setting up some epic overshoots, that the prices have way overshot any likely fundamental outcome. My response - welcome to 2023. This didn’t seem to happen at this scale 10 years ago. How to trade it? I’m not sure. But it seems these trades are going longer than historically, but when they reverse it will likely be violent.
