This investing webcast is an absolute must-watch.
If you’re looking for a practical ‘How To’ guide on using our Macro team’s investment research – covering everything from position sizing to balancing a portfolio of longs and shorts – this one is for you.
Below are some key takeaways, charts and video replay from our recent webcast hosted by CEO Keith McCullough and Senior Macro analyst Darius Dale.
Keith McCullough: Our process is largely built to get you in front of major market moves that are perpetuated by what we call ‘The Machine.’
Whether you like it or not, ‘The Machine’ is perpetuating a lot of different market moves. Close to 90% of U.S. equity trading volume now is systematic. So when the machines start to acknowledge either changes in momentum, style factors, factor exposures, sub-sector exposures, you better have been prepared for that.
This is how you identify those big changes. The two biggest components of my process really are 1) fundamental research to get ahead of big market moves and 2) Quantitative signaling which confirms or denies the fundamental research process.
If you only have one, I think you can be okay at this. If you have both, I think you can be great. What you'll see is that many have neither. There are things like predictive tracking algorithms, machine learning, Artificial Intelligence, things that we use to get better. We're very happy that the Old Wall remains gainfully employed because we need them to take the other side of the trade.
We just had nine consecutive quarters of U.S. growth accelerating. Here’s what the rate of change in growth and inflation tells you. When growth is accelerating you want to be long growth stocks. That's where we had our subscribers for two and a half years, until we started to make the call on #Quad4 in Q4 (i.e. U.S. growth and inflation slowing).
I think of our job, much like forecasting the weather. Knowing the future direction of growth and inflation tells you where to be allocated in the world. #Quad4 has been our call here since September. We called that a hurricane. It's a little different than being prepared for just a little rainstorm.
Being prepared for a hurricane is a dramatically different outcome than when both growth and inflation have been going up at the same time (i.e. #Quad2). Because growth and inflation were accelerating, the Fed is getting hawkish because the data continues to accelerate. They keep raising interest rates, so bond yields are going up. That's when bonds do poorly. That's when Gold does poorly. That’s when the dollar starts going down because people are chasing other country’s currencies. There's a whole host of things to do when you're in #Quad2 which, again, is where the U.S. economy has been over the last five quarters.
You were in #Quad1 or 2 for the last nine quarters. If you're wondering, that nine consecutive quarters of #GrowthAccelerating is a new USA record. The prior record was coming out of the early 1990s.
Now, we think U.S. growth and inflation slows. That’s #Quad4. #Quad4 is where the most amount of people get plowed. But if you're long the dollar and low beta, defensives in #Quad4 and you're short momentum, growth and Technology stocks, you crush it. Just look at our back-test on slide 70.
McCullough: For us, it's not a question of what happens in #Quad4. Those are historical facts. The question is whether or not we're in #Quad4. So what do we do? Every day we get up, put two feet on the floor and the data gives us a refresh on that. We get an opportunity to update our process and update our premise. Every data point we've had so far in the fourth quarter has been #Quad4 data.
The market is already discounting #Quad4. When the S&P 500 or the Russell 2000 goes down 10% you know Mr. Market is figuring this out. What you really don't want to do is buy the damn dip if we're going to remain in #Quad4.
Over the course of the 20 years that I've been on Wall Street, the U.S. stock has crashed two times. Why did that happen? #Quad4.
I don't know why you don't learn this in school. If you don't believe me, question me. I'm going to help you believe it. Now, I really appreciate the audience we have today and I certainly appreciate your questions because I'm accountable to all your questions. The Old Wall is not. Let's do it.
Darius Dale: Absolutely. Alright, let's keep it moving here. The first question here is from Bill. Thanks for joining us. Bill is asking, “Can you run through an example of volatility being ‘episodic’ and ‘clustering’ What happens to markets when we get a cluster of volatility?”
McCullough: I think you should read a foundational book on volatility being episodic and clustering. The book you want to read is by Benoit Mandelbrot called The Misbehavior of Markets. That’s far and away the most cited book in all of my work. He shows you empirically that volatility is always going to catch a lot of investors offsides. He also shows you that you’re way off sides if you're buying the damn dip on an asset that has clustering and episodic volatility.
That’s why I built my three factor model as opposed to looking at a 50-day moving monkey or something nonsensical like that. We're overweighting volatility though because predicting the volatility of volatility, or whether volatility goes from non-trending to trending, is the most important thing.
By the way, Ray Dalio has built one of the biggest asset management firms on the planet by basically observing volatility rules of this nature within what he calls his four quadrant model. Dalio calls it his All-Weather model.
No, I'm not trying to be arrogant in saying I'm Ray Dalio. I'm just trying to help you understand that there's somebody who's got 1,400 people on his research team that have empirically proven the exact same thing that I've proven, which is growth and inflation are the two most causal factors when it comes to the returns in your portfolio, either at the asset class, sub-sector exposure or factor exposure level.
Dale: Exactly. I mean 90% of daily trading and daily volume in the market is systematic. This means everyone is either implicitly or explicitly employing some sort of targeting regime for volatility, whether that be at the asset allocation level or the risk management level in terms of trying to run market neutral. So volatility has increasingly become very important to risk manage and understand for investors to get their security selection and asset allocation right.
What we noticed is that there is a huge opportunity in the market. Not a lot of investors can predict the direction of volatility with any degree of reasonable accuracy. And a lot of that has to do with them not having an accurate forecast for what ultimately impacts volatility, which is grow and inflation.
Here’s another question from a listener. Can you talk a bit on how volume plays into your quantitative models outside of confirming or disconfirming price moves?
McCullough: That's a really important question as well. Let’s break it down really simply. If you have price going up, volumes going up and volatility going down, then that's super bullish. That’s basically what we’ve had for the last two and half year when U.S. growth was accelerating. That’s also why we were so bullish on growth stocks back then. Conversely, if price is going down, volume is going up and volatility is going up, that's bad. It's confirming the bearish quantitative signal in my model.
Why does that matter? The number one way that I've made money over the course of my career is not losing money when Wall Street does, when they're all losing money. We don't want to be part of that crowd, the excuse making crowd, the whining and the political bickering. We want to have capitalize them.
You want to move from ignorance to awareness. Educate yourself to do better. Learn about the overlays of history, math and behavioral psychology versus what Wall Street consensus does which is based on linear economic theory and how the market feels.
I want you to focus your eyes on the math part and the rate of change. Measure and map it along a sine curve. If you don't know what a sine curve is, you’ve definitely got to get up to speed on that. This is what our entire model from a research perspective is built on. When the rate of change slows, that's bad. And when the rate of change accelerates, that's good. That's pretty much it.
