"Stories without numbers are just fairy tales" — Aswath Damodaran
Agustin Mackinlay | @agumack
— Aswath Damodaran. Narrative and Numbers. The Value of Stories in Business. New York: Columbia Business School, 2017
In my finance courses in Barcelona I call Aswath Damodaran “the Lionel Messi of Finance”. In a recent CNBC interview, the New York University professor was introduced as “the Dean of valuation”. And in a recent podcast with blogger Barry Ritholz, he called himself “the Kim Kardashian of valuation”. Whatever the nickname, one thing is certain: prof. Damodaran is a super-star in the world of finance—particularly in valuation. Although Narrative and Numbers was published in 2017, the recent fall in risky assets has rekindled interest on the book. In particular, the valuation of Amazon presented in chapter 9 has led prof. Damodaran to take a short position in that stock—a tremendously successful trade that has been widely discussed in academic circles and in the financial press.
Storytelling: a double-edged sword
Agustin Mackinlay | @agumack
— Aswath Damodaran. Narrative and Numbers. The Value of Stories in Business. New York: Columbia Business School, 2017
In my finance courses in Barcelona I call Aswath Damodaran “the Lionel Messi of Finance”. In a recent CNBC interview, the New York University professor was introduced as “the Dean of valuation”. And in a recent podcast with blogger Barry Ritholz, he called himself “the Kim Kardashian of valuation”. Whatever the nickname, one thing is certain: prof. Damodaran is a super-star in the world of finance—particularly in valuation. Although Narrative and Numbers was published in 2017, the recent fall in risky assets has rekindled interest on the book. In particular, the valuation of Amazon presented in chapter 9 has led prof. Damodaran to take a short position in that stock—a tremendously successful trade that has been widely discussed in academic circles and in the financial press.
Storytelling: a double-edged sword
With Narrative and Numbers, prof. Damodaran joins a growing list
of authors who emphasize the importance of storytelling skills in
business. The list includes, among others, best-selling authors Peter
Guber, John Hagel, Joshua Glenn and Rob Walker. “A well-told story
connects with listeners in a way that numbers never can”, writes
Damodaran. Good stories help people better understand what you are
saying; they get remembered; they are likely to generate a favorable
response. And they can lead to action.
We often tell in class the story of how Warren Buffet lent $5 billion to Goldman Sachs in the midst of the catastrophic fallout from the Lehman Brothers bankruptcy. That particular trade wasn’t his biggest money-maker; yet it allows us to illustrate the link between risk and reward in quite a dramatic way—something that numbers alone cannot achieve. Good stories, writes the author of Narrative and Numbers, reach our hearts and minds in a way that plain facts are unlikely to do. But there is a dark side to storytelling in business. A recent convert to behavioral finance and to the works of Nobel Prize-winner Daniel Kahnemann, Prof. Damodaran points to the danger of “letting emotions run away from the facts”. He cites the cases of fraudster Bernard Madoff and of blood-testing firm Theranos as illustrations of the risks created by stories that are simply too good to be true. Fraudsters, as it turns out, are oftentimes excellent storytellers.
Numbers to the rescue
We often tell in class the story of how Warren Buffet lent $5 billion to Goldman Sachs in the midst of the catastrophic fallout from the Lehman Brothers bankruptcy. That particular trade wasn’t his biggest money-maker; yet it allows us to illustrate the link between risk and reward in quite a dramatic way—something that numbers alone cannot achieve. Good stories, writes the author of Narrative and Numbers, reach our hearts and minds in a way that plain facts are unlikely to do. But there is a dark side to storytelling in business. A recent convert to behavioral finance and to the works of Nobel Prize-winner Daniel Kahnemann, Prof. Damodaran points to the danger of “letting emotions run away from the facts”. He cites the cases of fraudster Bernard Madoff and of blood-testing firm Theranos as illustrations of the risks created by stories that are simply too good to be true. Fraudsters, as it turns out, are oftentimes excellent storytellers.
Numbers to the rescue
Chapter 7 of Narrative and Number is perhaps the most useful of the
entire book. Equity analysts are provided with rules that enable them to
“test-drive” a narrative. A good story must not only be possible: it
must be plausible and even probable. One example will suffice. In a
simple two-stage growth valuation model, terminal value (TV) —the value
at horizon of all subsequent perpetual cash flows— is the most important
number, often accounting for more than 70% of the valuation. The
formula:
where r is the discount rate and g is the perpetual growth rate of cash flows after horizon, is described by prof. Damodaran as “an equation taught in finance classes around the world and often reproduced with little thought by analysts”. Careless analysts and lecturers regularly throw perpetual growth rates of 10% in a world of near-zero risk-free rates of return (at least in key European currencies). This is plainly absurd: g should be set at or below the nominal risk-free rate, which acts as a proxy to the long term nominal growth rate of GDP—otherwise a company could become larger than the entire economy. I pay a lot of attention to these issues in my valuation courses, and Narrative and Numbers contains a detailed list of cases where numbers can come to the rescue of a narrative gone wild.
TV = cash flow at horizon + 1 / (r – g)
where r is the discount rate and g is the perpetual growth rate of cash flows after horizon, is described by prof. Damodaran as “an equation taught in finance classes around the world and often reproduced with little thought by analysts”. Careless analysts and lecturers regularly throw perpetual growth rates of 10% in a world of near-zero risk-free rates of return (at least in key European currencies). This is plainly absurd: g should be set at or below the nominal risk-free rate, which acts as a proxy to the long term nominal growth rate of GDP—otherwise a company could become larger than the entire economy. I pay a lot of attention to these issues in my valuation courses, and Narrative and Numbers contains a detailed list of cases where numbers can come to the rescue of a narrative gone wild.
More on cash flows, less on discount rates
In Narrative and Numbers prof. Damodaran puts decidedly more
emphasis on projecting cash flows than on calculating discount rates.
Gone are the chapter-long discussions of the Capital Asset Pricing Model
(CAPM) and bottom-up betas that are the hallmark of his previous books.
This is a welcome development. To project the amount of resources that
companies need to invest in order to sustain growth, prof. Damodaran
relies on the sales-to-capital ratio.
Particularly noteworthy are the valuations of Uber, Ferrari and Amazon.
These valuations, based on Free Cash Flow to the Firm (FCFF)
projections, provide useful class material.
The emphasis on the sales-to-capital ratio is particularly interesting, as financial ratios with sales on the numerator are coming back to the forefront of equity valuation thanks to Financial Times contributor Stuart Kirk. Recently, Mr. Kirk has suggested that new technologies like “machine-learning” are destined to forever change our assumptions about valuation, as depreciation is likely to be replaced by appreciation when the availability of massive amounts of data finally yields more precise algorithms and better performance over time. How would prof. Damodaran’s models cope with these new realities?
The emphasis on the sales-to-capital ratio is particularly interesting, as financial ratios with sales on the numerator are coming back to the forefront of equity valuation thanks to Financial Times contributor Stuart Kirk. Recently, Mr. Kirk has suggested that new technologies like “machine-learning” are destined to forever change our assumptions about valuation, as depreciation is likely to be replaced by appreciation when the availability of massive amounts of data finally yields more precise algorithms and better performance over time. How would prof. Damodaran’s models cope with these new realities?
Pretty well, I would suggest. A good narrative, far from being self-contained, should be open-ended—and the FCFF valuation model is flexible enough to accommodate the changes suggested by Mr. Kirk. Until these changes materialize, a good old-fashioned valuation will never cease to entertain and instruct. Having shorted the stock of Amazon at nearly $2,000/share and the stock of Apple when the Cupertino giant was worth a trillion dollars in market capitalization, Prof. Damodaran can attest to the power of the traditional, reliable models that I am keen to introduce to our students.
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