Our Terminology

We’re not your father’s Wall Street research firm. That’s by design—we do things differently here. Because of our unique process and non-consensus approach, there’s a good chance that if you’re new to Hedgeye, you occasionally find yourself wondering what our outspoken CEO or one of our +30 analysts said in a research note, on HedgeyeTV, Twitter, or one of our research products.

We get it. That’s why we went ahead and created this “Terminology” section—to help you clearly understand what we mean when we use terms like “Trade,” “Trend” and “Tail” or (gulp) “”Multi-Duration Model.” The reality? It’s really not that confusing. Take a look below, we’re confident you’ll get up to speed with our way of looking at markets in no time.


Current Market Outlook

Current Market Outlook

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 1/4/2019) along with a number of slides on our risk management process. 

CLICK HERE to access our current market outlook

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Growth, Inflation, Policy (GIP) Model

Growth, Inflation, Policy (GIP) Model

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.

“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 

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.

Growth, Inflation, Policy (GIP) Model - GIP Model Risk Management Overlay

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HedgeyeTV Events (Live & Archives)

HedgeyeTV Events (Live & Archives)

*Once our next HedgeyeTV live show is scheduled you will be able to view it and sign-up for an email reminder here!

HedgeyeTV Archive

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.
  • In the Arena: Our just-launched In the Arena podcast gives you a smart, entertaining glimpse inside our locker room to get to know our team—our wins, our failures, our unique investing process and goals.

We look forward to learning more about financial markets together.

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Macro Process (Overview)

Macro Process (Overview)

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".

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Mo Bros

Mo Bros

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!

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Moving Monkeys

Moving Monkeys

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.

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Old Wall

Old Wall

“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.

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Price, Volume, Volatility (Multi-Factor Model)

Price, Volume, Volatility (Multi-Factor Model)

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.

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Quantamental Risk Management

Quantamental Risk Management

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.

Quantamental Risk Management - research sectorheads 1

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.

Quantamental Risk Management - research processcontent 2

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.

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Rate of Change

Rate of Change

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.

Rate of Change - sine curve

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."

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Risk Ranges

Risk Ranges

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.

Risk Ranges - trade trend tail

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!

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Style Factors

Style Factors

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.

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."

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."

Style Factors - style factors
Data as of 1/4/2019

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Timestamp

Timestamp

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.

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Trade, Trend, Tail (Multi-Duration Model)

Trade, Trend, Tail (Multi-Duration Model)

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 (2nd 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.

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User Guides (Hedgeye Products)

User Guides (Hedgeye Products)

Each Hedgeye investing product is designed with a specific investor in mind. Long-term investors and short-term traders alike can find a Hedgeye product that provides solutions to a common investing problem.

We've produced the following Hedgeye product "User Guides." Each User Guide is designed to explain how to effectively use our products to maximize their potential for subscribers. Take a look by clicking the links below.

  • ETF Pro: This must-have monthly macro strategy note distills our research down to our favorite ETF exposures.
  • Market Edges: A weekly market newsletter contextualizing key economic data within big picture macro trends.
  • The Macro Show: A live daily, online video show offering key market insights and investing implications with Q&A.
  • Real-Time Alerts: Buy, sell and cover stock and ETF signals selected from our analysts’ best stock ideas.
  • Investing Ideas: A weekly newsletter featuring top long-term stock ideas from our 40+ research analysts.
  • Early Look: This morning newsletter distills the most important market developments and delivers practical investing insights.
  • Risk Ranges: Get 20+ daily risk ranges on major asset classes and stocks to help you buy low and sell high.

We hope you find these User Guides helpful.

Thank you for remaining a loyal Hedgeye subscriber!

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Volatility

Volatility

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.

In the video below, Macro analyst and resident volatility guru Ben Ryan explains how we use volatility to get an edge on consensus.

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.

As an added bonus, we’ve included Ben’s response below to a subscriber who wanted to dig a little deeper. Their discussion relates to the relationship between “realized volatility” (i.e. historical volatility of an asset over some set time period of time) and “implied volatility” (i.e. investors’ expectations of future volatility, implied in futures and options markets).

Here’s Ben’s response, laying out our contrarian view on volatility signals, to our inquisitive subscriber:

“Thanks for watching the clip and thanks for the question. We’re always glad to see subs are engaged.

When we talk about “implied volatility premiums” we are comparing implied volatility (forward looking volatility expectations) to realized volatility (backward looking).

So if realized vol is 10% and implied vol is 15%, that’s a 50% implied volatility premium.

We were saying that if the implied volatility premium is widening out (getting larger), the market is saying that the current price action and trading environment will not last. A higher volatility assumption = more expensive options prices (insurance premiums are going up). Therefore a higher volatility assumption will get priced in when investors are nervous about a correction.

We never want to look at a single factor in a box like an implied volatility premium, but we can both agree that as an investor you have to be non-consensus and accurate more often than not. Therefore, if an implied volatility premium is positive and getting larger, it’s very possibly a sign that the market is not ready to correct – volatility is inversely correlated to a market most of the time. Volatility picks up when a market goes down.

Let me know if that makes sense because we want subs to understand our process here. Thanks again for reaching out.”

Volatility - volatility
Data as of 1/4/2019

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Wall Street 2.0

Wall Street 2.0

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 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.

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Wall Street Consensus Positioning (CFTC)

Wall Street Consensus Positioning (CFTC)

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, it’s 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. Macro analyst Ben Ryan breaks down how we interpret Wall Street consensus positioning in this video, “Understanding the CFTC COT Report.” In it, Ryan describes why we focus on the report’s “non-commercial” investors, how to interpret the Z-score of investor positioning and the critical threshold at which, historically, investor positioning tends to be “crowded.”

Wall Street Consensus Positioning (CFTC) - cftc
Data as of 1/4/2019

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