Updated 5/5/2023

Fundamental investing can take two paths: “bottom up” or “top down.”

One style of evaluating stocks is not better than the other. In fact, there are different types of both bottom up and top down investing within those main camps.

And finally, there’s nothing stating that an investor needs to be either top down or bottom up. One can be both and, ideally, should incorporate some element of both in their valuations.

In this post, we will cover these sections:

• “Bottom Up” vs “Top Down” Investing
• Using Top Down Investing in Stock Analysis
• Pitfall #1: Recency Bias
• Pitfall #2: Underestimating Powerful Businesses
• Pitfall #3: Overly Optimistic Research Reports
• A Top Down, Bottom Up Hybrid Approach
• Investor Takeaway

Each of the introductory topics and pitfalls really helps us understand the hybrid approach and what components can be most important. Be sure to work through these and maybe bookmark this post to refer back to them.

“Bottom Up” vs “Top Down” Investing

Defining these two definitions of stock market investing requires more of an abstract way of thinking.

You can think of the difference between “top” and “bottom” as similar to “macro” and “micro.”

In other words, are you (1) looking at the big picture (macro) and working your way down to the individual stock?

Or are you (2) starting at the stock and its intricate details (micro) and then determining a main investment approach from there?

Starting with “top down,” this approach can diverge further:

• Observing macroeconomic developments and then picking stocks
• Taking big-picture statistics, and then picking stocks

“Picking stocks” can also refer to asset allocation, such as using ETFs to attain particular industry exposures.

In fact, I’ve noticed that lately, most investors who start with the macro end up buying industry ETFs. They approach the portfolio mostly as asset allocation, adjusting as the macroeconomics change.

A “bottom up” investor starts with the company itself and might evaluate these factors before looking at bigger themes:

• Company financials
• Competitive advantage
• Management quality

Whether you’re talking about top down or bottom up analysis, it’s not to say that one approach focuses exclusively on one with the absence of the other.

Rather, the definitions denoting top or bottom might refer to where the investor chooses to start first in the analysis. It may also refer to how much weight an investor puts on each aspect in the final decision.

Using Top Down Investing in Stock Analysis

The “big picture statistics” style of top down investing is something you might see more in the growth investing camp. Though, that’s not to say you won’t see value investors (like myself) use it too.

The great Professor Damodaran has talked about how hard it is to evaluate early-stage, high-growth stocks. There is simply a lack of historical data on the company or industry.

So, Damodaran recommends a mostly “top down” approach to growth stock valuation. An analyst might project a total addressable market (TAM) for a company and calculate a rational growth path for that company. Using that growth path/potential, an analyst can then estimate a growth rate for a DCF valuation model.

A bottom up approach might look at the history of a stock’s fundamentals to project future growth rates. In contrast, a top down investor might look at the likely growth drivers. It could be based on macroeconomic data, market share, margin improvements, or all of the above and more.

That’s not to say that top down investing means never looking at historical data. In fact, historical data might be the best way to get reasonable estimates whether you’re looking at the big macro picture or the small micro picture.

Pitfall #1: Recency Bias

The fact that the future doesn’t have to line up with the past can be a pitfall for both the top down and bottom up investor. I think Warren Buffett is one of those extreme bottom up investors who says that any look at macroeconomic data is a waste of time.

He had this to say about history:

“In the business world, the rearview mirror is always clearer than the windshield.”

-Warren Buffett

Bottom up investors might get caught up with a company’s past financial data. This includes things like growth rates, ROE, ROIC, or gross and operating margins.

A top down investor might similarly rely on the past to identify “hot” industries or macroeconomic trends.

Cyclical industries can be a great example of this effect on both camps. Recent history tends to skew the valuations of a stock or industry.

When an industry is very sensitive to the cyclicality of the economy, it will see fluctuations throughout the natural business cycle.

It’s a tale that’s as old as time. Because commodities, in their nature, have (generally) no product differentiation, companies have to compete on price to gain business.

Remember the key lesson from Economics 101—price equals supply vs demand.

If demand is constant, then the price will rise when there’s limited supply, and will drop when supply is abundant.

As prices rise and fall, companies tend to invest either in more or less future growth. It can all depend on where the price of the commodity is (and thus how profitable future investment will be). More investment eventually increases supply, which eventually moves prices. It all contributes to the cyclical nature of prices, and thus profits.

In a similar way, commodities driven by the economy are also subject to these types of cyclical swings. As demand wanes with booming or bearish economies, prices increase and decrease. You then have boom and bust profits.

If an investor is evaluating a cyclical industry during a boom or bust period, he/she might project unrealistic future growth rates.

Too much emphasis on the recent past rather than complete business cycle will lead to the worst offenders.

I like Damodaran’s idea for evaluating cyclical industries in his textbook called Valuation. Take normalized earnings over the entire business cycle, in order to come up with an appropriate long term valuation.

Pitfall #2: Underestimating Powerful Businesses

Relying on a formula to calculate averages over big groups of data can also create problems.

For example, the average GDP growth for the U.S. over the past 25 years has been around 4.5% per year.

The reality of that 4.5% average is that there are large variations inside of it. Many companies greatly outperformed that index, posting growth rates of 10%, 15%, or more. At the same time, many companies greatly underperformed the average, or even shrank.

We don’t tend to see a lot of the poor performers over the long term because they tend to be dropped by major indexes such as the S&P 500. They then proceed to continue their destructive path downward.

Including those poor performers in an ETF (or basket of stocks) can really muddy up the overall performance of a top down investing strategy. That happens even if the investor is correct on his/her projections or assumptions.

At the same time, companies have greatly outperformed despite playing in a low or no-growth industry. Sometimes they are able to move horizontally or vertically in their market.

Or, a company might provide a superior product that is so essential that profits continue despite poor outside conditions.

In fact, some of the best businesses throughout the 2010s were companies that perfectly embodied this criteria. These included Google, Facebook, Amazon, Apple, Microsoft, and others.

It seems that everyone in the country uses these services in one way or the other on an almost daily basis. It led these companies to stand the test of time over extremely long time frames, even when other technology peers saw their business models fade away.

Pitfall #3: Overly Optimistic Research Reports

Another way to be led astray is by following overly optimistic projections from “reputable” firms.

This is especially prevalent in tech.

An industry like tech is so innovative and fast-moving. Long-term historical growth data is unreliable because of this. Or, it’s simply not available.

And so, spectacular recent performance can tilt projections impossibly higher. This optimism can build on itself as more and more of the crowd start to believe in the narratives.

I’ll point to the dot com crash of 1999/2000 as a solemn warning of the perils of using bright industry projections to pick sectors or stocks.

This article by CNN Money, posted shortly after much of the market had collapsed, is especially telling. At the time, top research firms such as IDC, Gartner, and Forrester Research had projected very high growth rates for tech companies. These were later discovered to be unrealistic, especially for networking equipment and other internet-related industries.

As impossibly high growth estimates and valuations proved unsustainable, these stocks crashed hard — a full 280 stocks losing a combined $1.755 trillion in value.

A Top Down, Bottom Up Hybrid Approach

Now for the fun stuff. If all of this bad news hasn’t turned you away from the top down approach, then I present to you a practical framework. It will hopefully improve your performance over the long term.

Simply stated, combine a top down approach with a margin of safety on your assumptions. It can help you overcome many of the potential pitfalls associated with fundamental analysis.

I’ll use my current stock research approach to highlight one way you can implement a hybrid approach to this kind of analysis.

First, I don’t limit myself to sourcing ideas either from the top or the bottom.

If I see a macro trend that I want to get in front of, I’ll use that to build a list of candidates for further stock research. At the same time, I’ll regularly run screens of companies and their valuations (“micro data”) to build a candidate list.

Then, I have spreadsheet tools that help me eliminate a lot of the companies which I automatically don’t want. The Value Trap Indicator spreadsheet is one. I also use my own customized version of the IFB Equity Model to check valuation.

Those tools are mostly bottom up.

As I’ve eliminated unfavorable candidates, I’ll start to dive deeper into the companies I’m looking at.

This involves a hybrid “bottom up” and “top down” approach, and I’ll do them simultaneously or without a goal of being one style or the other.

I will read the individual annual reports to understand the business. I’ll build an industry map using annual reports of peers and others in the value chain.

From there, the most conservative approach is to establish a future growth rate estimate based on macroeconomic data. These must be the most prevalent to the company I’m looking at. It protects against industry or company maturation in case the company can’t keep up with its past performance.

If a company has a very strong moat, I might allow for higher growth in relation to industry or macroeconomic averages.

I may use a retention ratio and historical revenue growth as a benchmark.

In that case, I have to be more careful because the margin of safety is reduced. The company in that case can’t hit a maturation stage without seeing a compression in its multiple.

Investor Takeaway

I’m not here to say that my implementation of top down investing is the right approach for everybody, or even the right approach at all.

In fact, it could be misguided, especially for certain companies.

But I hope it provides a good example of how to go about deciding whether you’re going to focus on top down or bottom up analysis, and also give some color on what elements to include and to what degree.

It might sound trivial, but unconscious decisions like these can drive ultimate long term performance.

So try out different aspects of both approaches, and see what fits with your investing temperament. Focus on maintaining a margin of safety, emphasis on the safety… and watch the compounding flourish.

Post updated: 5/05/2023