Discounted cash flow models are a psyop

Introduction

A defining trait of systematic traders and investors is a preference for methods and heuristics that are testable and quantifiable. Generally speaking, this preference is perfectly defensible; most retail market participants underperform by succumbing to cognitive and emotional biases that follow from discretionary or non-systematic approaches.

However, even when following a systematic approach, it is worth questioning whether the chosen methods are actually conducive towards achieving superior returns. Left unchecked, our bias towards quantitative methods can be highly counterproductive - not only can their results lull us into a false sense of security, but they can also obfuscate where our advantages as small players truly lie. A textbook example is over-relying on Discounted Cash Flow (DCF) models.

In this article, we will outline the main flaws in using DCF models to estimate a company’s intrinsic value and we will make a case for why we don’t need them.

The basics

Warren Buffett describes intrinsic value as follows: “Intrinsic value is an all-important concept that offers the only logical approach to evaluating the relative attractiveness of investments and businesses. Intrinsic value can be defined simply: It is the discounted value of the cash that can be taken out of a business during its remaining life.”

Based on this understanding, in principle, using a DCF model makes sense - it seeks to estimate a company’s intrinsic value by discounting the expected cashflows generated over its life at a risk-adjusted discount rate:

Cashflows are normally projected for a “growth period” (typically consisting of 5-10 years) before calculating the “terminal value” component to capture the company’s value at the end of this period growing at a lower, perpetual growth rate. It could signify the assumed cash flow for all future years beyond the forecast period or the total value of the investment or company if it were sold at the end of the forecast period.

The formula to calculate terminal value is:

[FCF x (1 + g)]/(d - g)

Where:

• FCF = free cash flow for the last forecast period

• g = terminal growth rate

• d = discount rate (which is usually the weighted average cost of capital)

DCF models are an effective valuation method for assets generating highly consistent and predictable cash flows. Some examples may include well-established and stable companies with consistent cashflows and real estate investments.

The main limitations of a DCF Analysis

Performing a DCF analysis comes with its own set of challenges, which should be taken into consideration. It involves the collection of substantial data and relies on assumptions that may, in certain instances, prove to be incorrect.

Outlined below are the primary drawbacks or limitations associated with a discounted cash flow analysis.

Complexity and data requirements

Conducting a discounted cash flow analysis necessitates a significant amount of financial data, including forecasts for cash flow and capital expenditure spanning multiple years. Obtaining the required data can be challenging and very time-consuming.

Dependence on quality of projections

Ultimately, the effectiveness of a DCF analysis relies heavily on the quality of the estimates and the degree of confidence in the projections it employs. When dealing with uncertainties and difficulties in projecting cash flows, the applicability of DCF becomes questionable - DCF models falter when cash flows are irregular or highly unpredictable. This is especially the case for early stage companies with unclear future cash flows, tech companies and highly cyclical companies.

High sensitivity to small changes in the model

Slight tweaks in several parameters of the model used, including the discount rate and the long-term growth rate, can often translate to substantial differences in the calculated intrinsic value. These same parameters are also very difficult to accurately estimate with any reasonable confidence. For instance, consider a terminal cash flow of $100M, a perpetual growth rate of 5% and a discount rate of 10%. The resulting terminal value is $2.1B. If we just apply a 200 basis point error range i.e. 9% -11% for the discount rate and 4% - 6% for the growth rate, the terminal value will range from $1.5B to $3.5B, which is a huge range relative to the small changes to the model’s inputs.

Fostering overconfidence

Detailed data and projections used in a DCF analysis can lead to an unwarranted level of confidence in the resulting valuation. By substituting process for thinking, investors lull themselves into a fall sense of security because it feels like they “put in the work”.

The terminal value - the main determinant of the final intrinsic value

The terminal value constitutes a significant portion (often 70%-90%) of the total value derived from the DCF formula. In principle, there’s nothing wrong with this feature. It makes sense, given that the bulk of returns from stocks are typically generated from the appreciation of the stock price, not the shareholder yield.

The complication with terminal values is that their estimates are often predicated on the assumption that the company analysed will continue to thrive even 10, 20, 30 years in the future. Realistically, this is only a reliable assumption for companies benefitting from a very substantial and sustainable competitive advantage.

Companies exhibiting these rare characteristics are more easily valued through a DCF analysis and therefore present safer investment opportunities as long-term compounders. This is a finding that reduces the universe of stocks to choose from by >99% and is consistent with the conventional wisdom of investing exclusively in companies with wide moats.

Why DCF analysis is kind of pointless

The greatest criticism levelled against DCF analysis is that it is heavily reliant and sensitive to projections that are very difficult to make with any warranted confidence. Common measures to mitigate these issues include making very conservative assumptions and applying a wide margin of safety to the final calculated intrinsic value. The irony, however, is that employing such measures would only make a stock result as investable if it was immediately obvious at face value or through a very simple back of the envelope calculation, thereby invalidating the need for a complex DCF model in the first place. In short, outside of an educational context, DCF analysis is of little to no practical utility.

I would make the case that DCF analysis is of very little value regardless of your investing style. For instance, if your investments are focused on high quality compounders with a long time horizon, then the stock price’s compounded annual growth rate will converge to the sustained returns on capital. Ensuring the stock price is trading at a reasonable multiple of normalised earnings is sufficient for the quantitative analysis side of valuation. Qualitative analysis of the business’s sustainability and longevity of its returns on capital given its scale, competitive advantage and industry trends is far more important than what any spreadsheet will tell you. By the same token, if you are focused on asset or deep value plays with price to normalised free cash flows in the low single digits, the quantitative side of valuation is obvious and does not require complex modelling - you can expect to make a return on your investment within a few years solely from the shareholder yield, so you don’t even have to rely on the highly uncertain terminal value to justify your decision to invest.

It is surprising to see so many self-proclaimed value investors relying so heavily on these models, with some amassing even hundreds of thousands of followers or subscribers on social media. These are the same people who will often idolise the likes of Warren Buffett and Charlie Munger but will conveniently or ignorantly not heed their own words on the uselessness of such complex analysis:

Why call it a psyop?

Seeing many retail investors relying very heavily on and promoting the use of DCF models reminds me of Marshall McLuhan’s iconic phrase “The medium is the message”. The medium's content delivers a message that is often readily understood, while the medium's character conveys another message that often goes unnoticed. In a similar vein, the assumptions underlying a DCF model and its resulting calculated intrinsic value are very clear. But what often goes unnoticed is that by merely having to rely on a complex DCF analysis, retail investors are playing into the hands of institutional market participants with more expertise and resources.

As retail investors, we have to recognise where our advantages and disadvantages lie. Given the ferocious competition in the markets, it is unreasonable to expect an informational or analytical edge that will allow us to compile more accurate DCF models to deliver market-beating returns. Our greatest and extremely valuable advantage lies in having a far greater universe of investable stocks. The vast majority of stocks (think small cap and many foreign market stocks) are inaccessible to large funds either due to liquidity or mandate constraints.

Warren Buffett famously said: “The trick in investing is just to sit there and watch pitch after pitch go by and wait for the one right in your sweet spot. And if people are yelling, ‘Swing, you bum!,’ ignore them.” Obviously the more pitches (stocks) you can entertain (consider investing in), the more selective you can be in choosing when to swing (investing in only very obvious opportunities).

Lastly, to drive home the point of a retail investor’s size advantage, I again defer to Warren Buffett: "If I was running $1 million today, or $10 million for that matter, I'd be fully invested. Anyone who says that size does not hurt investment performance is selling. The highest rates of return I've ever achieved were in the 1950s. I killed the Dow. You ought to see the numbers. But I was investing peanuts then. It's a huge structural advantage not to have a lot of money. I think I could make you 50% a year on $1 million. No, I know I could. I guarantee that."

Relying on DCF analysis can not only lull us into an unwarranted sense of security, but also make us lose sight of how to invest in the market in ways that play to our strengths as retail investors. As a litmus test, if you ever feel the need to use a spreadsheet to make any calculation to base your decision to invest or not, you’re playing the game wrong.