Below is a recent Early Look written by Senior Macro analyst Darius Dale. Click here to learn more about receiving the Early Look weekday mornings.

Ray Dalio's 2 Most Important Market Risks - 800px Ray Dalio Sept 23 2017 NYC
Source: Grameen America

“I knew which shifts in the economic environment caused asset classes to move around, and I knew that those relationships had remained essentially the same for hundreds of years. There were only two big forces to worry about: growth and inflation.” -Bridgewater Founder Ray Dalio 

Thank you Ray and thank you Keith for discovering these causal relationships. Obviously Hedgeye is no Bridgewater, but I do think a cursory “… and the rest is history” is deserved after 10-plus years of educating, being educated by, and growing alongside our buyside client base. 

Those early days in New Haven were decidedly not glamorous. Despite having graduated from a “good school”, I was dirt poor (still) and especially unsure of my future – not just at Hedgeye (then Research Edge), but also as a new participant in the financial markets. Truth be told, I had no idea what I was doing. 

And could you blame me? Almost nothing I learned in my finance and economics courses @Yale directly related to the discussions we were having in our morning meeting or with clients. Thank God for Google, books, and a genuine drive to no longer be the dumbest person in the room. 

Back to the Global Macro Grind… 

With respect to the aforementioned drivers of the relative and absolute performance of various asset classes:

“… Each could either be rising or falling, so I saw that by finding four different investment strategies – each one of which would do well in a particular environment (rising growth with rising inflation, rising growth with falling inflation, and so on) – I could construct an asset-allocation mix that was balanced to do well over time while being protected against unacceptable losses.” (Dalio, 2017)

Kudos to Ray and his team for approaching the development of their “All Weather” strategy in a much more sophisticated manner than I. I literally built our GIP Model from scratch simply out of the desire to work less. 

Back to those early days in New Haven, Keith would call me into his office daily to help him contextualize economic releases from a rate of change perspective. I would then have to remind him of the GDP and CPI “comps” (comparative base effects) of the given economy(ies). “What was that growth (or inflation) rate one year ago? How about two years ago? Three?” he would ask me as he wrote them on the white board in his office, in stacked fashion, across the various periods.

Of course none of this really made sense to me, but I would subsequently learn that this was the buyside’s shorthand version of implementing differential calculus into their models. That I knew and, from there, it all started to come together, slowly but surely. 

Going back to the white board in Keith’s office, you can probably imagine that having two people contextualize every meaningful economic release out of [then] China, Europe, and the US on a white board with dozens of numbers for each indicator is probably not the most productive way to stay on top of macroeconomic developments in an era of increasingly advanced computing power. Ironically, in an effort to save us both some time, I spent upwards of 18 hours/day for the next 2-3 years learning how to code so I could, at the very least, automate much of that time-consuming white board process.

But even that wasn’t enough. All those “comps” and 2nd derivative accelerations/decelerations across periods is still an awful lot of information to have to communicate to someone who really just wants to know if the economic environment for a particular asset class is getting better or worse and the probability of those trends continuing over some investable time horizon.

I think I first came across some stylized version of Ray’s four-quadrant All Weather model reading Zero-Edge back in 2010. I didn’t really know what to make of it then, but in my subsequent efforts to make my own work life a lot easier, that regime-based framework suddenly became a bastion of communication efficiency.

“Instead of relaying all of this information daily, all I have to do is tell Keith what Quad a particular economy is in and he’ll know what to do from there [in terms of issuing buy or sell signals in related markets]. Then maybe I can finally start to leave the office before dinnertime.” -Me, thinking to myself how I could game the system by working less and accomplishing more, circa 2011-12

And just think, I didn’t even haven to backtest anything then! I didn’t really know if #Quad2 was bad for bonds or if #Quad4 was the death knell for equities and risky credits. Hell, I didn’t even know if our comparative base effect framework was all that predictive. Everything just seemed to work so we went with it. 

Obviously, I’ve spent the last 7-8 years since then learning, building, backtesting, and learning, building, and backtesting some more. It’s a full-time job (and then some) maintaining and iterating highly predictive econometric models for every investable economy in the world. It doesn’t leave much time for marketing, client calls, or responding to inbound email requests, but I find a way to get it done. After all, my job is a lot less stressful than yours! 

It’s certainly a lot less stressful than this morning’s global growth data that incrementally confirms our #Quad4 forecast for the global economy here in 4Q18E: 

  • Cycle-low of 51.3 in the Eurozone’s Composite PMI for DEC
  • 15yr-low of 8.1% YoY in China Retail Sales growth for NOV
  • 10yr-low of 5.1% YoY in China’s Industrial Production growth for NOV 

At 8:30am the Control Group and Headline growth rates for NOV Retail Sales will be released and at 9:15am we get NOV Industrial Production growth. Those are currently the top three factors in our dynamically re-weighting predictive tracking algorithm for domestic economic growth. After peaking at rates just south of 6% in recent months, both the Retail Sales Control Group (#2 factor) and Industrial Production (#1 factor) are highly likely to print their first 3-handle YoY growth rates for the first time since JAN ’18 and JUN ’18, respectively. 

More #Quad4 confirmation is probably not what you want to hear this morning, but we investors are tasked with playing the game that’s in front of us – not the one we wish we were still playing (i.e. the nine consecutive quarters of Quads 1 & 2 that ended in 3Q). You don’t get mad at the weatherman for telling you it’s going to keep raining. You just remember to grab an umbrella on your way out the door instead 

Allegedly “comps” matter and so do rates of change, at least according to the man who built the largest hedge fund ever. Get yourself a white board! 

Keep your head on a swivel,


Darius Dale
Managing Director

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