I believe that a good investment starts with proper valuation.
This should be an uncontroversial statement (how do you know whether or not something is a good deal if you don't know how much it is intrinsically worth?), but from my experience most people don't seem to think this way. Instead, they appear to make investment decisions based on psychological, emotional or social factors - i.e. "the price has dropped", "the price is rising", "other people are recommending it", "it's in a hot industry", "it feels right", etc. If you don't believe me, just spend a few minutes browsing Stocktwits.
I would even categorize relative measures of value ("the PE ratio looks low compared to peers / history") as socially influenced rather than intrinsically warranted, and I've been guilty of this mistake in my past valuations.
So what's the "right" approach to intrinsic valuation? The only one that's conceptually made sense to me, and the one I've now gravitated towards for all my valuations, is a Discounted Cash Flow (DCF) analysis. Basically, what is the present value of all the cash you expect the business to generate, from now until eternity (or, more likely, irrelevancy and bankruptcy)?
Warren Buffett summarizes it well in the following video:
DCF analysis has been around since ancient times, and is the approach taught in business schools and most valuation text books, but, surprisingly, very few people (including professionals) appear to use it in practice. I took an online class in valuation from Aswath Damodaran, one of the most respected figures in valuation, and he says that the biggest mistake professionals (including his former students) make is confusing "pricing" for "valuation".
One critique about DCF is that it is not "flexible" enough in valuing companies, or that it doesn't allow as much nuance in judgement. But I've personally found that it's incredibly versatile, both for valuing startups and for valuing mature companies. A good book that demonstrates DCF's flexibility is Narrative and Numbers by Aswath Damodaran.
Why is it important to have an valuation and valuation process you conceptually believe in? First, it forces you to think more carefully and methodically about your assumptions, instead of being led astray by your first "gut" instinct. Second, without a proper valuation, it's hard to know whether or not a stock is underpriced or overpriced. Valuation gives you a logically consistent internal yardstick - something you can turn to when the stock price fluctuates for no apparent cause, and the market is being driven more by fear and greed than reason.
(That's not to say that all valuations will be correct. In fact, I expect a large proportion of my valuations will be wrong. But, assuming that, on balance, I have more "wins" than "losses" - or even if I'm only right 50% of the time, and the magnitude of my wins outweighs the magnitude of my losses - then consistent valuation work should enable me to have a "repeatable" process for long term investment success)
Key Discounted Cash Flow Inputs
For my DCF valuations, I use a freely available (and slightly modified) "simple" all-in-one template provided by Prof. Damodaran, but he provides a variety of other models on his website. The variety of inputs and sheets seems overwhelming at first, but I've found that I spend most of my time focusing on only four key metrics: Revenue Growth Rate, Operating Margin, Reinvestment Rate and Return on Invested Capital (ROIC).
Revenue Growth Rate and Operating Margin capture the key growth and profit drivers of the business. How quickly is the business growing (or shrinking)? How much money is left over after paying for operating costs?
Reinvestment Rate and Return on Invested Capital capture how efficient this growth is. How much money does the company have to reinvest (i.e. in capital expenditures or acquisitions) to maintain its growth rate? A company that can grow without reinvesting as much into that growth is more efficient and will have a higher return on invested capital (i.e. Buffet's famous See's Candy example)
Each of these numbers are key estimates that greatly affect the ultimate valuation of the company. My goal in any valuation is to estimate them as accurately as possible.
Estimates: "Inside" View
The problem with these estimates is that you don't often know where to begin.
Historical company metrics are often a good start, but may not capture fundamental changes in the business or industry.
Management often provides forecasts and targets, but there is a lot of individual judgement involved in whether or not to believe them. Management targets are also often based on non-traditional (non-GAAP) definitions, which exclude normal business costs (like stock compensation), and which should be approached with a high degree of skepticism.
Ultimately, there is a lot of subjectivity involved in making these estimates. Although I spend a lot of time reading through annual reports, earnings call transcripts and any recent news I can find about the company in question, the end result is likely skewed towards an "inside" view - one that is biased greatly towards my personal experiences and preconceived notions. I think of this as unconsciously looking for data that only confirms my "gut" instinct.
Relying too heavily on the "inside" view is a common mistake in forecasting, and is an easy trap to fall into because it feels "intuitive" and easy. The biggest improvement that I hope I've made this year is to start incorporating the "outside" view into my valuations.
Estimates: "Outside" View
An example of the "inside" vs "outside" view from the perspective of business valuation might help make this distinction clearer.
Inside View - MongoDB (MDB) is a high-flying tech company that has been growing revenue at a remarkable 60% rate every year. The market potential is huge, this is an industry I am familiar with, and their growth seems to be accelerating. Management is also incredibly bullish. Therefore, I might think it reasonable for them to grow at a minimum CAGR of 35% over the next 5-years.
Outside View - MDB had ~$300MM in revenue over the past 12 months. How many other companies, of similar size, have been able to grow at a 35%+ CAGR over a 5-year period? Answer: 2.8%.
The "outside" view is often like a cold splash of water to the face. It doesn't necessarily mean that your initial, intuitive "inside" view is wrong, but it often causes you to think more carefully about your assumptions. And because the "inside" view is often more optimistic, it will often cause you to adjust your estimates closer down to reality.
How do you get the numbers for the outside view?
- Reference The Base Rate Book by Michael Mauboussin. This is an invaluable resource with key historical metrics for various industries, and offers suggestions on how to adjust your estimates to more closely reflect probable reality.
- Try to find independent reports on market size, industry growth, etc. Cross-check estimates with historical trends and competitors. Very similar to the Base Rate Book analysis mentioned above, but sometimes you can get more granular by compiling your own industry specific set of data.
- Compare your estimates with "paragons" of the past. For example, if I'm evaluating a software company, I might compare its projected growth rates and operating margins with Microsoft's during its incredible rise. How likely is it that this new company is another Microsoft, an almost once-in-a-generation company? This is often a good reality check.
By combining the "inside" view with the "outside" view, I can hopefully get more accurate estimates for the key numbers that drive the DCF model.
To summarize, my valuation method is actually pretty simple:
- Use Discounted Cash Flow (DCF) analysis
- Use a simple DCF template provided by a valuation guru (no need to reinvent the wheel)
- Use my "inside" view to forecast key metrics, focusing on: Revenue Growth, Operating Margin, Reinvestment Rate and ROIC.
- Incorporate this "inside" view with the "outside" view, primarily utilizing "base rates"
- Continue updating and refining my valuations when there is material news (i.e. earnings reports)
I will touch more on #5 in a future post, which will focus more generally on forecasting and uncertainty.
Addendum: A Note on Discount Rates
I don't spend a lot of time worrying about what discount rate to use in my analysis, despite the fact that the discount rate can cause large changes in the valuation. Basically, I just take the "Implied Equity Risk Premium" from this page (i.e. 5.04% in August 2019) and add it to the 10-year treasury rate (1.52%) to get a discount rate (6.56%). I update this number every month or so and it flows through to all of my valuations.
Conceptually, I'm viewing the discount rate as my "opportunity cost" of not having my money invested in a "passive" index fund. The "risk-free rate" (10 year treasuries) plus the "equity risk premium" is my best guess of how much stocks will return in the future. The "active" investments I make should be able to beat this threshold.
The reason I use Damodaran's implied equity risk premium (rather than some fixed, arbitrary number like 10%) is that it seems to have the most predictive power (when correlated with actual equity returns over the next 10 years), so it should best represent my opportunity cost, right now. Admittedly, my understanding of his paper is pretty basic, so I'd welcome any feedback or corrections on this approach!