# Keeping score at tennis: a look at investment valuation methods

The hardest part of writing an investing blog is starting it. So when I sat down to pen the first Blog post I actually wrote four separate articles before I realised that I should just get over myself and post something. So, I decided to start on something reasonably fundamental: valuation.

Valuation in investing is much like scorekeeping in tennis: a necessary, but not sufficient skill for success. You can’t play a game of tennis if you don’t know how to score correctly; but you’re not going to improve your game by becoming an exceptional scorekeeper.

Valuation is an art form. It’s imprecise, there isn’t a “right” answer, and it can change quite rapidly. In short: it’s complicated, which can lead people to do one of two things:

Over-simplify in an attempt to stay out of the weeds, or

Over-complicate in an attempt to be as precise as possible (hitting the target, but missing the point)

I believe, as is often the case, an approach between the extremes is the best policy, an approach I’ll flesh out in this post, starting with first principles.

**What is “fair value”?**

The value of any asset is the __present value__ of its __expected__ __future cash flows__. These three components form the first principles of valuation:

Present value – accounts for the time-value/opportunity-cost/risk of receiving cash flows

Expected – I.e. multiple, probability-weighted scenarios

Cash flows – cash flows to the equity investor from either ongoing operations or corporate actions (M&A, spin offs etc)

All valuation methods incorporate these three in one way or another. None of this is particularly contentious, although contention is just around the corner.

The two great churches of valuation (and they house a lot of fanatics) are multiples and DCF. And like many religious denominations within the same faith, they’re pretty much the same. The difference is that DCFs incorporate the three components mentioned above explicitly, while multiples do it implicitly. We’ll come to the relative benefits and pitfalls later on, but first, let’s take a closer look at the first principles of valuation:

**1)** **Present Value:** **meaning we need to account for the time-value of money. Meaning we need a discount rate**

*“you’re not going to add much value as a buyside analyst by calculating the cost of capital more accurately than other analysts”*

Discount rates are reasonably straight forward: they basically say: cash today is worth more than cash tomorrow, because cash today can be invested to earn a return by tomorrow. It can also be viewed as an opportunity cost, or a discount that accounts for the risk of receiving cash flows in the future (i.e. that they might not be what you expect).

A wealth of tomes have been published on the topic of discount rates. Many of them are so dense that light bends around them. The calculation of the cost of capital can be extremely complicated. But what I believe is happening is a case of hitting the target but missing the point. Having studied finance extensively, I have come to the conclusion that you’re not going to add much value as a buyside analyst by calculating the cost of capital more accurately than other analysts. While it’s an interesting intellectual question, it’s not particularly practical.

Instead, I’d advocate selecting something based on the likelihood of receiving future cash flows. So, start at 9% (real) and ratchet up to 14% depending on various factors, including:

The predictability of revenues (i.e. subscription-based vs constant need to win new customers)

Cyclicality of the industry

The competitive intensity

Anything else that makes it more difficult to forecast future cash flows: “I require higher compensation for higher risk investments”

For example, if you were looking at an incumbent with an unassailable competitive advantage and a subscription-based service, a discount rate of 9-10% might be appropriate. If you’re looking at a construction company with a high degree of operating leverage in a challenged industry with intense competition, perhaps the higher end of the spectrum is warranted.

Crucially, select your discount rate ** BEFORE** you perform valuation work. This will stop you being tempted to alter the discount rate to justify a price target.

If the cash flows cannot be forecast, consider whether you should invest. If you can’t forecast the cash flows with some degree of precision, you can’t value the asset. There is one exception: optionality, but that’s a topic for another post.

**2)** **Expected: meaning we need to look at multiple potential futures**

This will be explored in another post on modelling and scenario analysis. Essentially, the future is uncertain, and any number of outcomes are possible. Reflecting three of these (bear / base / bull) and probability-weighting them, helps generate an expected value, and assess downside risk.

**3)** **Cash flows: meaning cash flows to equity investors**

We’ll keep it relatively high level here and leave the detail for another post. Three things drive operating cash flows:

Revenue growth

Margins

Investment (in capex and NWC)

It’s worth noting non-operating cash flows including real options and corporate actions should also be considered – but that’s also a topic for another post.

Having looked at the basics, let’s look at how they fold into the two methods.

**Multiples vs DCF**

They’re the same thing. Multiples are just a shortcut to a DCF. The bridge between the two is shown below. The sensitivity tables show the multiples justified by certain assumptions. It’s a helpful exercise to do in your own time, I certainly found it helped me. All you need to do is set up an extremely simple DCF and play with the assumptions.

Having bridged the two, let’s look at each in isolation.

**Multiples:**

This section could go on forever, but I’ll focus on three topics: forward earnings multiples, historical multiples, and when multiples do and don’t work. Overall, their main benefit is they’re quick and easy. Their main problem is that they oversimplify.

First up: forward P&L multiples (P/E, EV/EBIT etc). They’re usually found adorning the front pages of investment theses and research notes. They’re powerful descriptive tools and help frame the valuation of the company you’re looking at, but they have two limitations: they don’t directly measure cash, and they try to explain a stream of cash flows using a single number (which incorporates a large number of assumptions).

*Not measuring cash directly*

At the risk of sounding like a broken record: all valuation methods are based on the present value of an expected stream of future cash flows. Earnings are not cash, so they always exclude changes in net working capital, capex and various other charges depending on which P&L line item you’re using. This puts you varying degrees of separation away from what you care about (cash flows) and earnings can look extremely different to cash flows.

Let’s use EV/EBIT multiples as an example and assume we’re an equity investor, so care about the value of equity. The denominator is a fair way off cash flow to equity investors, it excludes interest, taxes, changes in net working capital, capex, and non-cash charges. Furthermore, as it’s a creation of accounting, it tends to make things look smoother than they are, meaning timing differences aren’t considered. The numerator also ignores the company’s net debt (and, to keep the sticklers happy, pensions and factoring with recourse).

The problem grows larger with EV/EBITDA multiples, and by the time you’re using EV/Sales, you’re a long way off the cash-flow piste (I’m looking at you early stage tech companies).

*They incorporate a lot of assumptions*

The second challenge is trying to explain a stream of numbers using a single number. Let’s pull up a reasonably simple DCF to help illustrate.

The value of the company is the FCFE stream labelled **A**.

The items label **B** impact **A**. Attempting to apply a multiple to any of the cash flows or earnings metrics in order to describe every single item labelled B is a dangerous over simplification.

This is not to say earnings multiples shouldn’t be used. Just be aware that if you use them, there are limitations and you’re making a lot of assumptions.

**Historical multiples:**

Here I mean the use of “historical average forward multiples” to value companies or assess their cheapness. I believe the practice is deeply flawed.

Let’s start with an example: “Materials Co. X has traded at 8.5 - 9.5x 1-yr forward EBITDA for the past 5 years, it’s currently trading at 11x. Therefore, it is expensive”. This feels like a safe way to assess the value of a company, because it’s consistent with history and if the company diverges from history (say it goes to 15x EBITDA) you can say “the market is crazy”. So this method has many things going for it, many of them to do with ego protection. Unfortunately, none of the things going for it include the ability to meaningful estimate fair value.

Multiples, like all valuation methods, incorporate discount rates and expected future cash flows. Different levels of any of these factors mean a different multiple is justified. Historical multiples reflect a different time period, likely with different levels of:

Competitive intensity

Industry conditions

Inflation

Tax rates

Government stimulus

Monetary policy

Regulation

Stage of the business cycle

Revenue growth

Margins

Investment

And many others

These factors mean different expected cash flows, probably a different discount rate and, therefore, a different justified multiple. Using an historical average multiple to value a company is only accurate if conditions today are exactly the same as they have been over history, a scenario that’s extremely unlikely.

Depending on its prospects, Materials Co. X might be cheap at 11x EBITDA. Let’s say the industry was moving to regionalised monopolies (something which is reasonably common in the construction materials industry), that should mean better pricing power, and higher cash flows in the future, so a higher multiple is justified, maybe even higher than 11x. The point is: the historical multiple is meaningless.

In summary, historical multiples are rarely useful.

**When multiples work (and when they don’t):**

Sometimes they help, sometimes they don’t help, and sometimes they harm. However, they do still have their uses and they’re certainly quicker than the alternatives. Let’s look at four example companies, each with a market cap of 1,000, which we’ll assume is their fair value. Let’s further assume the companies have infinite lives and continue to produce cash flows in perpetuity. We’ll call these companies Straight Line, Steady Growth, Cyclical and Exponential Growth. Let’s start with Straight Line, where multiples are reasonably useful.

Let’s move to Steady Growth. It’s a little more challenging as the company **appears** expensive at the beginning and

**cheaper as you look further into the future. Remember we assumed the market cap of 1,000 was fair value, so all these multiples are correct ways to value the company.**

__appears__In the case of the cyclical company, it **appears** cheap at the peak of the cycle, and

**expensive at the trough. Again, all these multiples are correct ways to value the company.**

__appears__So far, so good, right? The wheels start to fall off in cases of exponential growth or inflection points. The company below trades at a meaningless multiple of next years’ cash flow, looks insanely expensive on year 2’s and “too cheap to ignore” on year 5’s. So what is it? Again, they’re all correct.

Companies with cash flows like the one above attract a lot of headlines. We’ve probably all heard “1,000x P/E is chronically expensive, everyone has lost their minds”. Or the inverse, “5x P/E is too cheap to ignore”. To me, all these scenarios really tell you is: the company isn’t being valued on next year’s earnings.

All this is trying to say is that multiples attempt to describe the value of a company (which is a stream of cash flows) with reference to a single cash flow. Sometimes that’s helpful, sometimes that isn’t. It’s the same problem you see with averages: they’re attempting to describe a collection of data with one number. It can be helpful and it’s certainly faster, but as the distribution of the underlying collection of data increases, the average becomes less meaningful. The same is true for multiples.

**DCF:**

Having waxed lyrical on multiples, it may surprise readers to see the brevity of this section. DCFs are more complicated and you won’t get far if you try to model every single company in your universe – there simply isn’t time.

DCFs are more complicated, and certainly slower, but it exposes the assumptions (revenue, margin, investment, discount rate and perpetuity) required to justify a certain price. This may feel uncomfortable; I’ve certainly felt that way at times. Try not to think of it as guessing an exact number. Instead, treat it as a way of asking and answering questions. For example, “what if margins improve by this much, what if they don’t”.

The perpetuity is usually extremely important. Keep in mind that whatever levels of margin and investment are embedded in the cash flow number you apply the perpetuity calculation to are locked in forever.

A final word on DCFs. Keep an eye on return on invested capital (EBIT / [PPE + NWC + Intangibles]). In most industries, it tends to gravitate towards the cost of capital. If your forecasts see it changing rapidly, ask yourself if your assumptions are reasonable.

**Wrapping it all up:**

In summary, multiples are a shortcut to a DCF. The shortcut is most effective in simple cases and is certainly faster than a DCF. Crucially, both make the same set of assumptions, but multiples hide them, while DCFs expose them. If they’re hidden, you could be unwittingly making assumptions that make no sense for the company being valued, leading to an unreasonable valuation, and poor investment decisions.

DCFs take longer, but make the underlying assumptions clear, meaning things that are clearly wrong show up more easily, leading to better estimates of fair value and better investment decisions. Furthermore, when examining your thesis after an investment decision has been made, you can clearly see if your assumptions were reasonable, or not and modify your investment decision to suit.