There is a massive opportunity for investors to use modern day risk management tools to peer into the future and see where markets are likely headed next. While the future is obviously uncertain, the primary goal of any successful investor (and our investing research) is simple: Be more right than wrong. That's how investors win long term. 

The Hedgeye Macro process is designed to deliver just that: Superior investment ideas.

In the presentation below, we provide an overview of our current market outlook (updated as of 2/8/2021) along with a number of slides on our risk management process. 

CLICK HERE to access our current market outlook

(Below is a 16-minute video featuring Hedgeye CEO Keith McCullough and Senior Macro Analyst Darius Dale digging deep into exactly how we arrive at our unique investment conclusions. In a nutshell, it’s an explanation of our risk management process—from start to finish. We think you’re going to like what you see. Click here to read the transcript and access the accompanying slides.)

Our Growth, Inflation, Policy (GIP) model is “the hallmark of our fundamental research process,” explains Hedgeye Senior Macro analyst Darius Dale in the video below. 

We find two factors to be most consequential in forecasting future financial market returns: economic growth and inflation. We track both on a year-over-year, rate of change basis to better understand the big picture then ask the fundamental question: Is growth and inflation heating up or cooling down?

From there, we get four possible outcomes, each of which is assigned a “quadrant” in our Growth, Inflation, Policy (GIP) model and the typical government response as a result (neutral, hawkish, in-a-box or dovish):

• Growth accelerating, Inflation slowing (QUAD 1);
• Growth accelerating, Inflation accelerating (QUAD 2);
• Growth slowing, Inflation accelerating (QUAD 3);
• Growth slowing, Inflation slowing (QUAD 4)

After building this base of knowledge, we select what we like (and don’t like) based on our historical back-testing of the different asset classes that perform best in each of the four quadrants.

“In QUAD 1, for instance, where growth is accelerating and inflation is slowing, that has historically been really positive for both equity and credit data across all sectors of the U.S. economy,” explains Darius Dale in the video above. “Whereas when you think about QUAD 4, in which growth and inflation are slowing concomitantly, that has historically been quite negative for both equities and credit.”

If this regime-based framework sounds familiar, it’s because billionaire investor and Bridgewater founder Ray Dalio employs a similar risk management process also focused on growth and inflation.

Our primary goal is to help our subscribers avoid getting blown up by the big stuff.

If we can help steer you into our preferred factor exposures on the long and short side, that’s great too. We make this point often, differentiated processes lead to differentiated perspectives and differentiated perspectives help investors generate alpha.

We have created a significant amount of research over the years which remains relevant for investors eager to dig deeper into our research process.

Investing, and life, is all about getting better with each passing day. Learning is key to your personal investing evolution.

We want you to improve the way you think about financial markets. From Hedgeye investing webcasts to long-form interviews with some of the sharpest minds in the business, links to our research archives below should help get you up-to-speed very quickly:

• Hedgeye Webcast Replays: We host deep-dive research investing webcasts with CEO Keith McCullough and our 40+ analyst research team.

• Real Conversations: These interviews feature CEO Keith McCullough discussing markets with some of the smartest minds in finance.

• Podcasts: You can also listen to our webcasts and more in podcast form on our Apple Podcasts page.

We look forward to learning more about financial markets together.

We owe a debt of gratitude to those financial market founding fathers from whom we've learned so much from over the years. In response to overwhelming subscriber demand for our favorite book suggestions we've put together a collection of reading lists for you to check-out.

First things first. We want to highlight three excellent books which come highly recommended by our CEO Keith McCullough. We call these our "Must-Read Process Books."

Also below is a "Top-10 Reading List" – featuring a collection of our favorite ten books covering markets, investing and hard work. (There are a ton of great books that didn't make our top-10 list but still come highly recommended by our team. Click here and here to check out "Hedgeye's Bookshelf" – a list of all the books CEO Keith McCullough has read in both 2019 and 2018.)

We encourage you to check out these reading lists to help you dive deeper into how we approach financial markets.

MUST-READ PROCESS BOOKS

1. The Misbehavior of Markets

By Benoit Mandelbrot

If you're looking for a thoughtful and rewarding read about how to simplify the complexities of financial markets, look no further. We highly recommend you read "The Misbehavior of Markets" by mathematics legend Benoit Mandelbrot.

"This is somewhat of a Bible to me," says Hedgeye CEO Keith McCullough. "I learned a ton from this guy, if only what not to do. It's an alternative to establishment economics. It's certainly an alternative to how people think about markets relative to economic data." Click here to watch Keith's entire book review on "The Misbehavior of Markets."

2. Thinking Fast & Slow

By Daniel Kahneman

Hedgeye CEO Keith McCullough discusses Daniel Kahneman's seminal book, Thinking Fast and Slow. According to McCullough, this must-read book written by the Nobel laureate and founder of behavioral economics has been an invaluable resource in enhancing his approach to investing.

"This book provides a real baseline for understanding, 'What is behavioral finance?'" McCullough says. "What this book does is it teaches why human beings should embrace uncertainty." Click here to watch Keith's entire book review on "Thinking Fast & Slow."

3. Models of My Life

By Herb Simon

Hedgeye CEO Keith McCullough discusses Nobel laureate Herb Simon's autobiography, Models of My Life. "I'd like to thank Mr. Simon for being not only a revolutionary in this space, but for challenging the status quo," McCullough says. "That's a really important component of this book. It contextualizes where we were in economics back in the 1970s and outlines a better path forward." Click here to watch Keith's entire book review on "Models of My Life."

TOP-10 READING LIST

1. A Man For All Markets – by Edward Thorp: The card-counting mathematics professor turned hedge fund manager who taught the world how to beat the dealer and, as one of the first great quantitative investors, beat the market.

2. Principles – by Ray Dalio: The world’s largest hedge fund manager shares the unconventional principles he’s developed, refined, and used over the past forty years to create unique results in both life and business.

3. Deep Work – by Cal Newport: A valuable skill that's becoming increasingly rare, Deep Work is the ability to focus without distraction on a cognitively demanding task. It's a skill that allows you to master complicated information and produce better results in less time.

4. The Undoing Project – by Michael Lewis: Forty years ago, Israeli psychologists Daniel Kahneman and Amos Tversky invented the field of behavioral economics. Michael Lewis shows how their Nobel Prize–winning theory altered our perception of reality.

5. The Most Important Thing – by Howard Marks: The co-founder of Oaktree Capital Management is renowned for his insightful assessments of market opportunity and risk. In The Most Important Thing, Marks breaks down his time-tested, fundamental investing philosophy.

6. The Runaway Species – by Anthony Brandt and David Eagleman: What lies at the heart of humanity’s ability―and drive―to create? But where does our creativity come from, how does it work, and how can we harness it to improve our lives, schools, businesses, and institutions?

7. Scale – by Geoffrey West: A pioneer in the field of complexity science, explains the science of emergent systems and networks. West discusses the underlying simplicity that unites the seemingly complex and diverse phenomena of living systems (in our bodies, cities and businesses).

8. Mastering Fear – by Brandon Webb: A former Navy SEAL turned media CEO, draws on his experiences in combat and business to show how people from all walks of life can stretch and transcend their boundaries, by learning to use their fears as fuel to achieve more than they ever thought possible.

9. Boyd: The Fighter Pilot Who Changed the Art of War – by Robert Coram: John Boyd may be the most remarkable unsung hero in all of American military history. Some remember him as the greatest U.S. fighter pilot ever -- the man who, in simulated air-to-air combat, defeated every challenger in less than forty seconds. Some recall him as the father of our country's most legendary fighter aircraft -- the F-15 and F-16. Still others think of Boyd as the most influential military theorist since Sun Tzu.

10. Superforecasting – by Philip Tetlock and Dan Gardner: Tetlock and Gardner explain how ordinary people—including a filmmaker, a retired pipe installer, and former ballroom dancer—turned out to be astonishingly good forecasters beating prediction markets and the collective judgment of intelligence analysts with access to classified information.

We produced an exclusive 14-minute video hosted by Hedgeye CEO Keith McCullough to help bring you quickly up to speed on our unique Macro process. In the video below, McCullough will walk you through everything from:

• How we model the top 50 economies around the globe
• How our quantitative risk range model helps investors buy low and sell high
• How we help investors beat Wall Street by tracking consensus positioning

We encourage you to watch this primer on our repeatable risk management process.

To learn more, we also created this "Macro Playbook." In it, we share additional details about our research process - how we model global economies, what "risk ranges" are, how we arrive at our investing conclusions and more. We think you'll find it useful. 

CLICK HERE to read our entire "Macro Playbook".

Closely related to the #MovingMonkeys are the traders who chase price momentum. The idea is that a stock that has had a big up-move will continue higher is not unique. It’s been sold to you by bucket shop brokers since the beginning of time and becomes a self-fulfilling prophecy the more people believe it.

Not to be confused with the chart chasers of 2000 or 2007, these are the “Mo Bros” of 2014 vintage. They are all over Twitter. They travel in crowds, and get very sensitive as momentum chasing #bubbles begin to crash.

The Mo Bro is like a surfer: he looks for a wave that’s just right, then tries to ride it all the way in to the shore. While there are many obvious things that can go wrong with any market strategy, we think one of the biggest threats to momentum investing is that old standby of the academic science of Wall Street known as the Greater Fool Theory. 

This Theory states that in order to sell your overpriced stock at a profit, you need to find a buyer who – by definition – is an even greater fool than you. If you buy a stock that has just broken out to a new high, you have to be pretty sharp to be the guy who buys it at the newest, highest price, and then sells it at the newer highest, really much higher than it deserves to be price.

The markets, of course, are full of fools, greater fools, and larger-than-life fools. And then of course there’s the Federal Reserve, the Greater Fool of Last Resort. Mo Bro to the max!

Watch any financial program and sooner or later you will hear about the “the 50-day” or “200-day moving average” signaling something prophetic about markets.

Some “technicians” have gone so far as to slice-and-dice this down to 10, 25, and 150 day moving averages. Forgive us if we point out that this is not an analytical exercise: anyone whose computer can count to 200 can replicate these, and many other such “analytical tools.”

Before there were computers and complexity theory, this type of straight-line analysis was deemed to be very valuable information. On Wall Street 2.0, not so much. That’s why we lovingly call them #MovingMonkeys.

In all seriousness, using simple moving averages gets more dangerous, the closer you study market history. There is no credible back-test that shows it actually works. At momentum chasing market tops, they look genius. In sideways to down markets, the monkeys get eaten. Put differently: these straight-line models have one way to be right, and a near-infinite number of ways to be wrong.

“You gotta be in it to win it!” How often have your heard that? Wall Street has consistently told customers they need to be invested in the US stock market. But investors need to know there are plenty of markets, risks, and asset allocations to think about above and beyond that.

“Success” on Wall Street has traditionally been defined as success for the brokers (in trading commissions), success for the traders (in trading spreads), success for the bankers (in fees), and success for the analysts (who participate in commissions, spreads, and fees).

What about your success?

If you were “in it to win it” at either of the 2000 or 2007 #bubble tops, we think it’s safe to say that your definition of success may vary from theirs. As a result, most have awakened to the fact that Wall Street’s longstanding business model is inherently conflicted, compromised, and constrained.

We call that, the #OldWall.

It’s time you self-direct yourself to do what #OldWall people have never had to do: put your interests first. It’s time for you to be the change you want to see in your wealth management.

Investors spend a ton of time vetting ideas and building their thesis around that idea. But when it comes time to actually put on a trade, most investors don’t have a framework for sizing that position, which is equally critical to the success of that investment.

“I’m going to show you how I do it, and you need to figure out how you do it,” explains CEO Keith McCullough in the video below discussing how he thinks about position sizing.

The video below should not be perceived as guidance for individuals. “Everyone has different risk parameters, different ages, etc. There are a lot of different permutations of what you’re trying to do,” McCullough explains. “But the most important thing is to have a rules-based process. You need a process that lays out what it is you’re trying to do, and why you’re trying to do it. Process is the most important thing.”

Here are some basic portfolio sizing guidelines:

1. Follow your own rules-based process
2. Your longs should always be bigger than your shorts
3. Average into your positions based on conviction

In addition, beta adjust your positions. “Beta adjusted” positioning is adjusting position size based on the volatility of that asset. In other words, a more volatile asset (i.e. higher beta) should generally be a smaller position in your portfolio.

In the video above, McCullough explains how he executes position sizing from both a broader asset allocation perspective and also in constructing a long-short equity portfolio.

Here’s a key takeaway from McCullough: “Think in terms of basis points or percentage of capital at risk when you’re trying to make decisions in both the long-short portfolio, asset allocation or otherwise.”

“I can get long a lot of different things within my asset allocation,” McCullough says. “But again make that decision before you start getting whipped around or transacting in the market. That’s how I do it. How you do it is totally up to you but have a framework.”

Before launching Hedgeye in 2008, Founder & CEO Keith McCullough spent a decade in the hedge fund world. During that time, he consistently refined his risk management model, both in the day-to-day management of his portfolio, and in rigorous back-testing against historical market data.

This risk management model is multi-factor meaning it’s based on the price, volume and volatility of a publicly-traded security. This model is what drives our Real-Time Alerts, throwing off red and green Bullish/Bearish risk management signals throughout the course of the trading day.

PRICE

What does a security’s last price tell you?

The most popular price-based answers to that question are the 50 and 200-day moving averages, based on closing prices of an index or an individual stock. 

Other systems, such as Candlestick Charts, track daily open, high, low and closing prices. But they still work off only a single factor, and thus do not present a full risk management picture. 

Price charting is based on the assumption that forces beyond mere Supply and Demand set the price of goods or securities. We don’t disagree with that. We disagree with how consensus tools contextualize it.

VOLUME

Since most investors care about the price of their holdings, shouldn’t they care about liquidity? 

If the price of your stock goes up, did you make money? The reality is that you only make money when you sell at that higher price, and in order to do that, you need liquidity. If there is not sufficient volume traded, you will not be able to sell at your price – maybe not at all.

Price moves perpetuate TRENDs. Volume either confirms (rising volume) a bullish TREND, or calls it into question (decreasing volume). 

Strong overall volume is generally seen as a sign of health in the markets, though isolated moves in Volume can signal turning points. 

Stocks moving UP on decelerating volume have the potential to create a Liquidity Trap and could signal a coming correction, while an outsized burst of volume on a strong UP move in a stock could signal a breakout to new price levels. 

VOLATILITY

If you are combining VOLUME with PRICE, you’re already well ahead of the single-factor technicians. But you’re not quite there yet. Hedgeye’s Model tracks multiple factors in three categories: Price, Volume, and Volatility.

Does it matter? Immensely. But how many people proactively solve for it?

Many Institutional Investors analyze the relationship between Price and Volume. Analyzing volatility is far less trivial – and for some reason, far less common.

Volatility is the statistical dispersion of prices of a security or index; the variance, or the standard deviation of prices for the security. 

The higher the Volatility, the greater the price uncertainty of a position. That doesn’t mean that Volatility is bad. It means that you have to take it into account if you want to make good buy/sell decisions, across durations, in what we call the Risk Range.

If you don’t incorporate an analysis of volatility in your buy/sell decision making process, you will have to get used to “averaging down” to offset your timing mistakes. And as any seasoned trader can tell you, averaging down presupposes two things, both of which are unreasonable: an endless supply of money, and a stock price that finally goes back up.

Volatility is measured against other positions in your portfolio (relative Beta), and against broad market averages (market Beta). A “high Beta” stock is more volatile than the broad averages and is likely to both fall and rise by a greater percentage than the market does. 

Risk-oriented investors are drawn to Volatility because they generally believe they can get in and out at the right time, and they believe they are better at timing Volatility than most other traders. 

This is often based on a small number of lucky trades, or on forgetting unsuccessful trades. This common psychological trap is called Confirmation Bias. There’s also the adrenaline factor, which is great if you want thrills at a casino, but it has no place in a risk management strategy.

The rise of "quants" – investors who use algorithms and program-based mathematical models to trade markets – has changed the game for investors. Ever-increasing computer processing power and the proliferation of "machine learning" tools will only escalate this arms race.

For "fundamental" investors – investors diligently modelling companies to gain an edge on stock valuation – all is not lost. At Hedgeye, we think investors can gain an edge on Wall Street consensus by marrying both quantitative and fundamental investing.

We call this "quantamental."

What Does A 'Quantamental' Risk Management Process Look Like?

We are obsessed with delivering superior investment ideas. You likely know this by now.

Our hybrid investing approach combines:

1. Proprietary quantitative analysis
2. Bottom-up sector research
3. Top-down macro research with an emphasis on duration

The end result is an intelligent, high-octane suite of products that draws on insights from over 40 research analysts. We cover everything from Global Macro and Retail, to Energy, Restaurants and Washington Policy research.

Our unique research team at Hedgeye is composed of some of the most highly-regarded analysts in the industry. Our quantitative models and fundamental research teams complement one another.

Here's how.

1. QUANTITATIVE RISK RANGES

Our quantitative trading range model was developed by CEO Keith McCullough during his years as a hedge fund manager. It was specifically designed to risk manage the reflexive nature of markets.

This risk range model is utilized throughout the entire suite of Hedgeye research products to augment our 40+ person research team's fundamental views. Think about it. All investors have some basket of core investing ideas (stocks, bonds, ETFs or all of the above). Identifying those investing ideas is tough enough, then you have to deal with the uncertainty of markets.

When McCullough built his proprietary Risk Range model the aim was simple: Create a quantitative risk management tool to help investors actually buy low and sell high.

The model uses three core inputs - price, volume and volatility - to determine the likely daily trading range for any publicly-traded asset class. These risk ranges are dynamic. They are designed to change as the data changes. At its core, you sell at the top end of the range and buy at the low end.

2. BOTTOM-UP SECTOR RESEARCH

Our investment research team is headquartered in Stamford, Connecticut. It is made up of analysts with buy-side and sell-side experience. Our research team based in Washington D.C. is composed of seasoned policy veterans with many decades of experience. They possess high-level experience and contacts having worked in a variety of influential positions over the years.

Together, our team of 40+ research analysts cover 19 different Sectors - from Housing to Industrials to Technology - and have an unparalleled understanding of what's driving specific stocks, sectors, policies, global markets and economies.

Our goal is simple. Since "Day One" more than ten years ago, our focus has been to build the most thoughtful and thorough team on Wall Street. We seek to translate our unique, combined knowledge into successful investment opportunities for all of our subscribers-big and small.

Our collective investment experience includes time at Carlyle Blue-Wave, Ardsley Partners, Buckingham Research, Morgan Stanley, Dawson-Herman Capital, Wells Fargo Securities, to name a few, while our combined policy experience includes time at the U.S. Court of Appeals, U.S. Energy Department, U.S. Office of Defense, U.S. Federal Reserve, U.S. Chamber of Commerce, and more.

3. TOP-DOWN MACRO RESEARCH

In addition to a deep bench of 18 fundamental equity and Washington policy research teams, our Macro team measures and maps economic data for the top 50 economies around the world, covering 90% of global GDP. We run predictive tracking algorithms for both growth and inflation for each of these economies to forecast the likely path for financial markets.

Bottom Line: Our Macro team is focused on generating investable ideas based on this research that combines their deep study of market history, the tracking of Wall Street consensus positioning and the volatility signals embedded in futures and options markets.

(We encourage you to dig deeper by reading our "Macro Playbook.")

Bottom Line

The combined "quantamental" knowledge of 1) proprietary quantitative analysis 2) bottom-up sector research 3) top-down macro research makes your Hedgeye subscription the best bang-for-your-investing-research-buck out there.

There are few concepts more fundamental to our research process than measuring and mapping economic data on a “rate of change” basis. Rigorously tracking year-over-year growth across economic indicators illuminates pivotal inflection points in macro markets.

Now, consider the following chart. That's a sine curve. It represents the rate of change of a particular data set over a given period of time. You’ll hear us referencing this lot.

The mainstream financial media is fond of touting levels – reporting, for instance, that “such and such” indicator “rose to a level not seen since 2008.” Levels are misleading. As CEO Keith McCullough is fond of saying:

“It’s not whether something is good or bad. It’s about knowing whether it’s getting better or worse.”

Rate of change accelerations and decelerations are facts, not opinions, and our process is focused on contextualizing these facts, rather than opining on the validity of absolute levels of growth, inflation, and/or policy. This focus helps us consistently spot inflections in the performance of key factor exposures, across asset classes, 3-6 months ahead of investor consensus.

A LESSON IN "BASE RATES" & WHY IT MATTERS

An important factor to understand in measuring the rate of change in global economic data are "base rates." The base rate is the level one year ago against which the year-over-year growth rate is calculated. Simply put, the comparative base rate is the level above which an economic indicator must surpass to realize any growth in the following year.

Our back-testing of historical data shows that measuring and mapping rate of change data helps us spot key inflection points. Specifically, tracking the base effects helps predict the likely pace of future growth. In the U.S. specifically, 78% of the time the marginal rate of change in the 2-year average Real GDP growth rate in the comparative base period carries the opposite sign of the marginal rate of change of the growth rate over the trailing 10-year period. That same figure is 70% of the time for Headline CPI.

If this sounds confusing just know that it basically boils down to the simple fact that the U.S. economy is inherently cyclical. In other words, measuring and mapping the data reveals track-able accelerations and decelerations along the growth and inflation sine curve.

It's worth noting that as the economy has gotten increasingly more reliant on financial leverage to replace lost organic growth potential both growth and inflation have become decidedly more cyclical throughout the post-crisis era and since commodities took off in the early-2000's, respectively.

• Directional Accuracy of Base Effects for Pre-Crisis Growth: 60%
• Directional Accuracy of Base Effects for Post-Crisis Growth: 81%
• Directional Accuracy of Base Effects for Pre-Commodity Boom Inflation: 63%
• Directional Accuracy of Base Effects for Post-Commodity Boom Inflation: 71%

As the economy has become more prone to booms and busts, there's opportunity for investors in predicting the future path of growth and inflation.

How We Forecast Growth & Inflation

We use two distinct models to forecast the high probability outlook for both growth and inflation based on the near-term momentum in various indicators: 

1. Intraquarter, we use predictive tracking algorithms to adjust the base rate based on the marginal rate of change in various growth and inflation-oriented factors.
2. In out-quarters, where we don't yet have high-frequency reported data, we employ a "Bayesian inference process" that adjusts each of the preceding forecasted base rates inversely and proportionally to the marginal rates of change in the base effects. As mentioned above, the 2-year average growth rate in the comparative base period backtests as having the most forecasting validity.

This model is very effective at identifying pivots in growth and inflation.

Our U.S. GDP model has an intraquarter tracking error of 33bps, an average absolute forecast error of 23bps and an r-squared of 0.87 with a success rate of 88% in terms of projecting the directional outcome. Our U.S. CPI model has an intraquarter tracking error of 33bps, an average absolute forecast error of 21bps and an r-squared of 0.79 with a success rate of 88% in terms of projecting the directional outcome.

Bottom Line

Our research process, anchored in rate-of-change data analysis, is designed to get a lot more right than wrong. Our ultimate goal is to keep you ahead of the big moves in macro. It’s a grind and every day we’re here measuring and mapping the data for you.

To understand how our growth and inflation forecasts impact our market calls check out the section on our "Growth, Inflation, Policy Model."

In the interest of simplifying the complex, Hedgeye CEO Keith McCullough explains the process behind how we select our favorite investing ideas. This process follows a simple risk management checklist you need to follow to effectively execute the Hedgeye Macro playbook. Our ultimate goal is to bring these investing tools to your disposal, so you can develop your own framework for executing the Hedgeye process.

McCullough breaks down the entire risk management process start to finish.

Our proprietary GIP model is designed to separate the economy into four distinct regimes that correspond to marginal rates of change of growth and inflation, which are two of the three principal components of forward-looking asset returns. The third – monetary policy – is accounted for in this analysis by overlaying how central bankers are likely to respond to the implied changes in economic conditions.

From there, we get four possible outcomes, each of which is assigned a “quadrant” in our Growth, Inflation, Policy (GIP) model and the typical government response as a result (neutral, hawkish, in-a-box or dovish):

• Growth accelerating, Inflation slowing (QUAD 1)
• Growth accelerating, Inflation accelerating (QUAD 2)
• Growth slowing, Inflation accelerating (QUAD 3)
• Growth slowing, Inflation slowing (QUAD 4)

“What we’re trying to do is measure and map an economy,” explains CEO Keith McCullough. “So the output of that fundamental research gives us the expected Quad, and we have a playbook based on the back-tests in each of the Quads that tells you what to buy and sell.”

There’s also the Trade/Trend/Tail Risk Range model.

“I have this framework that tells me what I want to do in each of the quadrants, but the question is does the market agree with that?” McCullough explains. “So that’s the second part, which is the tougher part. That’s the market signal. It’s our Trade/Trend/Tail signal based on Price/Volume/Volatility.”

Speaking specifically about the Trade/Trend/Tail signal, core to the Hedgeye process of selecting our preferred macro factor exposures is whether or not that ticker screens well from the perspective of Keith’s proprietary risk management process. This Trade/Trend/Tail risk management model employs price, volume and volatility as discrete factors in the calculus of Risk Range levels that back-test well as critical momentum thresholds.

So back to the Risk Management A/B test. “If an asset is signaling bullish trend [via our Trade/Trend/Tail Risk Ranges] and that asset is one we like in the current Quadrant – take for instance the 3^rd Quadrant you can see that I like Tech, Utilities and REITs – I’ll be buying it aggressively at the low end of the Risk Range.”

But what if you get conflicting signals on the A/B test?

Here’s McCullough again. “Conversely, if we’re in the 3^rd Quadrant, and it’s an asset in that our back-test tells us we shouldn’t like – like Financials – but the Trade/Trend/Tail signal says Financials are in a bullish trend, then that’s telling me it’s not a good time to short Financials.”

Thinking more deeply about disconfirming signals between the GIP model and Trade/Trend/Tail Risk Range signal, it’s really simple. Here’s another example.

“REITs and Biotech both score well in Quad 3, but if REITs are bullish trend and Biotech is bearish trend, why would I buy Biotech when I could buy REITs? The market is already agreeing with the position that I like, so I’d much rather go with the position that’s working for the reasons that the market has decided.”

Why use the risk management A/B test? “This helps me with not only the size of my positions but also assess my conviction,” McCullough says.

Using both the GIP model and Trade/Trend/Tail Risk Ranges together helps us make better investing decisions.

Watch the video above for more of CEO Keith McCullough explaining this process. He even goes a level deeper into “the A/B tests within the A/B test.”

While there are many different Hedgeye tools, understanding the process behind the risk management A/B test is a must-watch.

A lot of Wall Street-types wake up in the morning and try to tell Mr. Market what they think it should be doing. Our Risk Range process is designed to measure and map what the Market is actually doing. This provides investors with a repeatable risk management process which complements our rigorous fundamental research views. 

Our quantitative Risk Range model was designed to incorporate these “reflexive” and behavioral elements of financial markets. Reflecting the uncertainty embedded in financial markets, these immediate-term Risk Ranges are dynamic. In other words, the immediate-term Risk Ranges change as the data changes.

The model uses three core inputs – price, volume and volatility – to determine the likely daily trading range for any publically-traded asset class.

To break it down conceptually, if an asset's price and volume are rising while its volatility is falling, that's bullish. It means investors are buying with conviction. In this scenario, an asset's Risk Range generally narrows as the probable outcome of that asset heading higher goes up.

On the other hand, if an asset's price is falling, while volume and volatility are rising, that's bearish. It means investors are selling with conviction. In this scenario, an asset's Risk Range generally widens as the probable outcome of that asset heading lower goes up. 

This is an overly simplistic explanation but conceptually sound.

At its core, our Risk Ranges model is designed to be intuitive: You sell at the top end of the range and you buy at the low end.

Phase Transitions & Bullish Or Bearish Formations

Hedgeye CEO Keith McCullough’s quantitative Risk Range model was designed specifically to be multi-duration. This means our Risk Ranges dynamically adjusts to suggest critical thresholds – over short-term (Trade), medium-term (Trend) and long-term (Tail) durations – after which, upon breaching these levels, an asset flips from bullish to bearish or vice versa. The idea is to give investors a clear framework for understanding how an asset is trading over short-term, medium-term, and long-term time horizons.

Core to the process of selecting our preferred macro factor exposures is whether or not the ticker screens well from the perspective of McCullough’s Risk Ranges. Assets where last price is greater than all three durations (Trade, Trend and Tail in ascending order) are said to be in a “Bullish Formation” and all dips should be bought, insomuch that assets in the converse “Bearish Formation” should be repeatedly shorted on strength.

This is an important point about our Trend and Tail ranges. If an asset was bullish but fell and were to breach either the Trend line or both Trend and Tail levels, it would signal a major shift in sentiment and momentum from bullish to bearish (according to the model’s measurement of price, volume and volatility). This is called a bullish to bearish “phase transition.”

Make no mistake, when an asset dances around its Trend line, we’re monitoring it closely for confirmation that it either maintains its Trend or we see a sustained breakdown confirmed by the asset’s price, volume and volatility. When an asset confirms a Trend breakdown, you get out!

Changes in financial market sentiment can whipsaw even the sharpest of investors.

Our Macro risk management process is designed to monitor key style and thematic factor performance allowing us to quantitatively map evolving market trends.

The pioneering work of Eugene Fama and Kenneth French identified some of the early style factors – like "quality," "size" and "value." Subsequent research by market practitioners like AQR's Cliff Asness helped propagate additional factors like "momentum." These factors have historically been associated with outperformance for both behavioral and risk reasons.

Here's Hedgeye CEO Keith McCullough:

The video below features Senior Macro analyst Darius Dale explaining why it's important to monitor style factors and Wall Street consensus positioning...

The rise of ETFs has made "factor investing" – a strategy of tilting your portfolio to various style factors in an effort to capture outperformance – more accessible investors. Assets invested in ETFs and ETPs listed globally surpassed $5 trillion by mid-2018. Moreover, BlackRock anticipates ETF/ETP AUM to more than double to $12 trillion over the next 5 years.

Regardless of whether or not you agree with this projection, you have to agree that the proliferation of factor-based index investing and the growth of platform-oriented, market-neutral hedge fund strategies has made financial markets more sensitive to Macro risks than ever before. For example, JPM estimates systematic trading accounts for over 90% of U.S. equity trading volume.

We call this systematic trading "The Machine," as rapid changes in what these systematic trading strategies are buying and selling ruthlessly perpetuates the underperformance and outperformance of different "style factors."

Here's McCullough again:

We help investors gain on edge on Wall Street by tracking style factor performance and utilizing the various inputs of our research process to anticipate changes in "The Machine."

Data as of 1/4/2019

In a word, that’s how we manifest our principles of Transparency, Accountability, and Trust. Everything is time-stamped.

Every signal we’ve issued since founding the firm in 2008 has been #timestamped. We don’t hide our history. When we’re wrong, it’s right there for all to see – every win, loss, and tie.

Every day our CEO, Keith McCullough, puts up his Real-Time Alerts. These are risk management signals indicating immediate-term calls on the stocks and ETFs we follow here at Hedgeye. Every Alert is time stamped, and the entire history of the Alerts resides on our website. Fully #Transparent. Fully #Accountable.

Since risk is non-linear (it happens fast, and slow, and episodically), it makes sense to attempt to contextualize changes in price and volatility across time.

Mainstream “technical” measures consider time/price relationships using a one-factor price momentum model (like a simple moving average). That doesn’t work.

These consensus metrics have become the Received Wisdom of Wall Street. Every “chart” is crystal clear, in hindsight. But these charts tell you nothing about power laws and/or phase transitions. No single-factor linear model does.

Hedgeye’s proprietary system breaks the investment time horizon into three core durations:

• TRADE – the next three weeks or less
• TREND – the next three months or more
• TAIL – the next three years or less

At any given moment, every position in your portfolio will exhibit characteristics in each of these three durations, depending on a broad range of factors ranging from company-specific, to sector-specific, to broad market, to the global macro level.

Trade

The TRADE duration measures risk over the very immediate-term (3 weeks or less), and it shouldn’t surprise you to realize that an awful lot can happen in that time frame. 

TRADE is the point of departure for measuring risk in the immediate term. And TRADE is the first signal you might look at if you are an active short-term trader. 

The TRADE duration keys off of current events and macro correlations. As an example, a good earnings report may drive a lot of buying, causing the stock to look overbought on an immediate-term TRADE basis. Whereas a bad one might signal immediate-term TRADE oversold.

If you are a longer term holder, you can use the immediate-term TRADE duration to help you risk manage (sell some high, so that you can buy more low) your best ideas. 

Trend

The TREND duration in the Hedgeye model measures risk over the intermediate-term (3 months or more) and back-tests as the most manageable in our model.

That shouldn’t surprise you as this is the duration where many investment strategies purport to live. Three-months or more captures Institutional Investors trying to handicap “the quarter.” 

While immediate-term TRADE volatility can present you with buy/sell opportunities, contextualizing TRENDs, and whether the probability that they continue is rising or falling, is the most important skill set within the longer-term risk manager’s game.

Tail

The TAIL duration measures risk over the longer-term (3 years or less). After more than 15 years of trial/error developing this model, we’ve been humbled into submission on this front. It’s very difficult to dynamically risk manage investment ideas beyond that time frame.

Not to be confused with the popular definition of Black Swan “tail risks” that can often be qualitatively defined, we’ve submitted ourselves to Mr. Macro Market on this front and decided that TAIL risks are manageable, if you subject yourself to change and uncertainty.

Across all of our core risk management durations, the fulcrum point in the analysis is the rate of change. This is a critical difference compared to other modeling approaches. The key questions aren’t about whether things are good or bad – they are all about probability weighing whether risk factors are getting relatively better or worse.

Mathematically speaking, we’re talking calculus here (2^nd derivatives). Physically, you can also think about it in thermodynamic terms. What factors are undergoing “phase transitions” (from one state to another)? Because once something has moved from bullish to bearish TREND, it’s often too late.

Put simply, TRADEs often educates us about the stability/fragility of TRENDs, whereas the direction of longer-term TAILs can be shocked when a TREND undergoes a phase transition.

Understanding volatility is an essential tool in your macro toolkit. At Hedgeye, we have a nuanced view about how to incorporate this measure into your portfolio decision-making process.

As our Senior Macro analyst Darius Dale explains in the video below:

In other words, we use volatility to get an edge on consensus in predicting the highest probability outcome for future asset prices.

WHAT IS VOLATILITY?

Volatility is a market-based signal that reveals past or expected price action in a given security. More specifically, it reveals a market’s variation in price or returns. Volatility is an important addition to changes in the price of a security.

In the video above, Dale discusses an important relationship that we track: The important relationship between “realized” and “implied” volatility and why this market signal is critical.

Breaking it down as simply as possible, “realized volatility” is the historical volatility of an asset over some set time period of time. “Implied volatility” gives us the market’s expectations of future volatility for a specific asset based on what’s implied in futures and options markets. More technically, realized volatility measures the variance in a stock’s price. Implied volatility tells us about the market’s forward-looking expectation for price or return variance in a given security.

Now, here’s the critical risk management concept to understand on realized relative to implied volatility: Implied volatility “premiums” and “discounts.” As a very basic example, if implied volatility is 15% and realized volatility is 10%, that’s a 50% implied volatility premium (so 15/10-1= 50%). If implied volatility is 5% and realized volatility is 10%, that’s a -50% implied volatility discount (so 5/10-1= -50%).

What does this mean?

If an implied volatility premium is widening out (getting larger), the market is expecting higher volatility than what has been realized in the past (i.e. more expensive options prices because these insurance premiums are going up). Therefore, a higher volatility assumption will get priced in when investors are nervous about a correction.

Conversely, an implied volatility discount widening out (getting more negative) suggests investors expect lower volatility than what has been realized in the past (i.e. cheaper options prices because these insurance premiums are going down).

Therein lies the contrarian market signal for savvy investors. By taking the pulse of implied relative to realized volatility, we can get a good read on whether investors are becoming more fearful or more complacent.

• Fearful: Expectations of future, implied volatility are in excess of the historical, realized volatility because investors are seeking downside protection on that asset in options markets. That’s called an implied volatility premium.
• Complacent: Expectations of future, implied volatility is below historical, realized volatility because investors are going long that asset in options markets. That’s called an implied volatility discount.

“What we like to do is track the spread between implied and realized volatility over time and recognize the critical pain points to suggest that investors are as bullish or as bearish as they can be,” Dale explains in the video above.

“So let’s say there is a historical range [at the extremes of implied volatility premiums and discounts], when the implied volatility premium hits the top end of the range it suggests investors are about as fearful as they can be and, conversely, when a discount is particularly steep it’s a signal that investors are increasingly complacent relative to the recent past in that asset. To us both of these are an immediate-term signal that investors should consider fading investor expectations in that particular asset or asset class.”

Hedgeye is the change. Our founding principles are Transparency, Accountability, and Trust. Our mission is lift the veil of mystery from the investment process, to educate and empower your decision making.

We provide research and insight for a subscription fee – not against trading commissions, not to participate in banking deals. We don’t manage money, we don’t trade our own account. Our sole focus is to provide guidance for you to risk manage your own portfolio, using the same tools and research we provide to the top professionals in the industry.

While our main objective is to be right, sometimes we aren’t. But we make that trivial for you so that you don’t have to guess. 

We #Timestamp all our calls – research, trade signals, etc. It’s all there for you to see, in real-time.

We also tend to be kind of loud in public places. But that’s ok (the Old Wall guys are pretty loud too!). We want to give you a voice. We want to give you the truth.

Wall Street 2.0 is about the democratization of investment and risk management research. There are no “first calls” or “secret huddles.” 

We play favorites with everyone. For the first time, the individual investor has a fighting chance.

Just as important as vetting the fundamentals of any investing idea is knowing the investment community’s positioning around that idea. Namely, is this a consensus or contrarian trade?

In short, understanding consensus positioning is another essential tool in your investing toolkit since, if Wall Street is too bullish or bearish, you may have already missed the move.

At Hedgeye, we measure and map the CFTC’s Commitments of Traders report, across asset classes, to learn precisely that: What does current investor consensus positioning look like and where can we add the most value with a non-consensus market call?

Due to popular demand for a primer on the topic, we’ve produced another special video as part of our “Understanding” series. Senior Macro analyst Darius Dale breaks down how we interpret Wall Street consensus positioning.

We focus on the CFTC report’s “non-commercial” investors because this group is made up of Wall Street speculators betting on the future direction of the underlying asset class, be it the S&P 500, U.S. Dollars, Treasury bonds, Crude oil or Soybeans. Meanwhile, the “commercial” side of the report is matching say farmers or corporations trying to hedge out business risk with intermediary banks facilitating those transactions.

We also look at “net” contract positioning, so the balance of Wall Street’s contracts to see directionally how consensus is skewing on either the long or short side. Focusing on the speculators within the CFTC report plus their net positioning gives us the best read on how Wall Street is positioning around the asset in question.

“This is a reasonably real-time way to gauge investor sentiment,” Dale explains in the video above. “What we’re effectively trying to do is spot not only is the market positioned long or short a particular security, but how long or short they are relative to the recent past.”

On measuring and mapping current positioning relative to the past, we use the Z-score of this net contract positioning. Z-score is a form of standard deviation that allows different time series to be compared apples to apples. It provides context for where CFTC contract positioning is relative to the measures over say the past one year, three years or other time period.

More technically, it is an indication of how many standard deviations an asset class is from its mean over some specified time period.

Why does this matter?

“It’s not just enough to identify whether a particular asset market is net long or net short,” Dale explains in the video above. “To us, what is really important is how this position has changed over time to identify a particular pain point in factor crowding.”

That’s where the Z-score comes into play. “What you typically see is that when Z-scores get really extended, say 1, 2 or even 3X standard deviations in one direction or another you see big reversals,” Dale explains. “In other words, there are a lot investors crowding into these trades. The fundamental story that got you to this extreme point was really, really exciting.”

“But at the top the dumbest of dumb investors is buying,” Dale explains. “At the same time, the slowest moving and the least informed investors are probably shorting the lows at the other end of the extreme.”

What you want to do is track the CFTC data on a Z-score basis to see when investors are crowding into a trade. “That’s when you want to consider fading or doing the opposite,” Dale says. “Instead of using Old Wall surveys or idea dinners to track sentiment we want you using our quantitative oriented process born out of the CFTC data.”

Watch the video above for Dale’s explanation of how we used CFTC positioning data to make our short call on the Euro in April 2018. As Dale explains, “This was the worst possible time for the market to be net long Euros, which gave us a lot of confidence in making the call to be long Dollars and short Euros.”