Aswath Damodaran: Reliable Investment Valuations Balance Numbers and Narratives
When it comes to valuing stocks, the most reliable valuations come from imaginative number crunchers and disciplined storytellers, says Aswath Damodaran. And too often pure “numbers” people drift off into what he calls “spreadsheet nirvana.” Similarly, investors who focus purely on the narrative of a potential investment run the risk of quickly “veering from reality to fantasy.”
Damodaran, who teaches valuation and corporate finance at the Stern School of Business at New York University (NYU), made these remarks at the CFA Institute Equity Research and Valuation Conference 2014 in Boston, where he urged attendees to bridge the gap between numbers and narratives, insisting that the best valuations are not just “a collection of numbers, but a story connected to numbers.”
Damodaran acknowledged the critical role that numbers play in the valuation process, but he warned that they should be used judiciously. Due to mission creep, he thinks accounting statements have become increasingly difficult to navigate and fair value accounting has become an oxymoron, allowing for bias and the illusion of objectivity in valuations. Similarly, the emergence of Big Data as an input into sophisticated valuation models driven by “Excel Ninjas,” and the accompanying notion that “more is better,” has its limits. Adding an extra decimal place to your model’s projected operating profit margin conveys a false sense of precision with no meaningful improvement in outcomes.
Analysts who focus solely on the numbers are unlikely to convince skeptics or potential investors if they have no compelling narrative. They also risk missing internal inconsistencies (that “spreadsheet nirvanna” where trees grow to the sky and margins expand forever). For Damodaran, every number in an analyst’s model should have a story behind it.
If Benjamin Graham and David Dodd’s Security Analysis is the quintessential playbook for number crunchers, Damodaran suggested that storytellers look to Philip Fisher’s Common Stocks and Uncommon Profits and Other Writings for similar guidance. Humans are wired to be more receptive to stories than numbers, and in investing the ability to make a persuasive case for a stock’s valuation is critically important. “Stories connect with people while numbers don’t,” said Damodaran.
Narratives generally work best with start-up firms but they can also be effective with special situations and turnaround stories. If left unchecked, however, storytellers can quickly wind up in “fantasyland,” according to Damodaran. This happens when a narrative-based valuation is not sufficiently supported by numbers. Without numbers, storytellers also have no way to measure whether the narrative is holding up over time.
Damodaran prescribed a six-step process for bridging the gap between narratives and numbers and generating more reliable valuations.
- Survey the landscape: Understand the company’s business model, the market in which it operates, and its competitors.
- Create a narrative for the future: Develop your storyline by assessing the company’s products and management, the markets in which it operates, and the competitive landscape.
- Check the narrative against history, economic principles, and common sense: Distinguish between what is possible, what is plausible, and what is probable.
- Connect your narrative to key value drivers: Value can come in different forms, including dominant market shares, sustainable competitive advantages, or easy scaling.
- Value the company: The most straightforward valuation incorporates a discounted cash flow model.
- Keep the feedback loop open: Earnings reports, corporate actions, management changes, macroeconomic news, and political developments can impact both numbers and narratives, so vigilance and reassessment is critically important.
In sum, numbers and narratives are essential elements to an effective valuation. And number crunchers and storytellers are both prone to operating in an echo chamber, where their assumptions go unchallenged. Those who manage to bridge the gap between number crunching and storytelling are more apt to find success as investors.
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All posts are the opinion of the author. As such, they should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute or the author’s employer.
Excellent article, David, and thanks for bringing more attention to the equally excellent body of work by Damodaran. While he deals mainly with listed equities, his findings often apply to investments in private equity and other illiquid assets as well. I would recommend two of his papers in particular: The first is “The Value of Transparency and the Cost of Complexity” (http://papers.ssrn.com/sol3/papers.cfm?abstract_id=886836), which points out that “the financial statements of a few firms are designed to obscure rather than reveal information.”
The second is “Marketability and Value: Measuring the Illiquidity Discount” (http://papers.ssrn.com/sol3/papers.cfm?abstract_id=841484), which includes this important caution:
“With publicly traded stocks, we generally use market prices to measure returns and these prices should reflect the consequences of illiquidity directly. In other words, a portfolio manager who invests primarily in less liquid stocks will not gain an advantage over one who invests in more liquid stocks. With private equity and venture capital funds, where the assets are not traded and the valuations are generated internally (by the fund managers), the stated value of a portfolio may be misleading if illiquidity is not explicitly factored into the value. In general, this will lead to returns being overstated at funds with more illiquid investments and the magnitude of the misstatement will be greater in periods of overall market illiquidity (when liquidity commands a greater premium).”
I have often found that the marketing materials for private equity and hedge funds focus on the narrative, either ignoring actual performance data completely or making careful use of false and misleading data. Investors who follow this narrative-only lead have tended to make bad investments.
The supposed illiquidity premium is a wonderful example. Theory suggests (and Damodaran emphasizes) that investors should not be willing to make an investment unless they will be compensated for illiquidity risk–that is, the REQUIRED return is higher for illiquid investments. But the marketing pitch–the narrative with either no data or false data supporting that–turns it into a higher EXPECTED return. Actual performance data do not support the existence of higher realized returns for illiquid assets: that is, the expected return is actually less than the required return. An analysis that, as Damodaran recommends, balanced the narrative with actual data would have caused many PE and hedge fund investors to avoid them.
Brad, Happy New Year.
As before I enjoyed your insightful analysis, in particular the illiquidity premium. I am working on a deal that involves oil and gas assets in the Canadian arctic, so your comments are particularly appropriate to this deal – bit of art and science involved – for example global warming or not, tankers in the arctic or not (in case an environmentalist is reading this please note that I am only the piano player), and so on.
Best wishes for 2015
Savio
Brad,
Thanks for your kind words, and for your thoughtful comments and suggestions. I suspect we’ll never run out of investors who, at their peril, only require a good story.
Dave
Agreed…sigh…
Hello David
That was a particularly enjoyable article – it was fun to read, had lots of insight and I have a lot of respect for the work of Mr. Damodaran.
Best wishes for the season
Savio
Savio,
Thanks for checking in. Glad you enjoyed the article.
-Dave
Good article, and the reasoning is laid out in a compelling way. Too bad Damodaran appears to be making no reference to the fact that DCF is the most popular with academics, valuation professionals and those who want to justify paying an inflated multiple (with their own money or, more commonly, someone else’s).
He correctly notes that it is a garbage in – garbage out process, and concludes that we should not feed models with garbage, or pretend that they have more predictive power than they really do. Fair enough. But he also expresses belief that a DCF model is a part of “the most straightforward” valuation process, which I find controversial. The most straightforward valuation is either based on (adjusted) multiples or, for less mature businesses, a venture capital method (multiples-based terminal valuation discounted using a rule of thumb-based IRR). The consequences are profound as investors seem to rely on multiples a lot more than the academic world.
I’m not sure I understand your criticism, Krzysztof. Any valuation process–whether it’s DCF, or adjusted multiples, or a “venture capital method,” or whatever–can be applied correctly, or it can be applied incorrectly. The controversy shouldn’t be about the valuation approach (the conceptual model) but the valuation practice (the model with values plugged in for key parameters).
Some of Damodaran’s work focuses on the difficulty of identifying good data and avoiding “garbage in.” For example, the first of his papers that I link to above notes that some managers (corporate executives, private equity managers, etc.) encourage investors to overvalue their assets by obfuscating true data–that is, by trying to get them to use “garbage in”–while the second notes that they may encourage investors to overvalue their assets by ignoring the value-destroying effects of illiquidity.
The job of the investor (or analyst) is to uncover the true value by finding the best possible numbers to plug in to the valuation model. But it’s the parameters, not the modeling approach, that separates a good valuation from a bad one.
Brad, I’m a fan of Damodaran’s work and I find his argument *on how the DCF method should be applied* flawless.
My point is related to the choice of the valuation method and comparison of different valuation methods. In David’s account of Damodaran’s remarks, he does refer to that, too (much as you might want to say that the modeling approach is less relevant).
I disagree that the most straightforward valuation will incorporate a DCF model. I also find that investors will often use DCF as an excuse to buy rather than a true decision-making tool, which does not mean that DCF can’t be done right. It is however a reflection on how people deal with the method’s shortcomings (i.e. heavy reliance on assumptions as to future developments) – by giving up on it rather than doing it right. DCF is prone to model error and can instil a false sense of confidence. It’s not a fatal flaw but a flaw nonetheless. It’s like a brilliant car that’s difficult to drive.
Hello Krzysztof
Happy New Year.
I read your comments with great interest since I am asked occasionally to value assets or companies.
In my limited experience I have found that in the absence of a market based comparison (such as the illiquid assets that Brad refers to) DCF is the only method available.
For instance consider a solar power plant installation in a geographical area which does not have a history of solar power production (ground or roof top) at all, where DCF is the only choice.
If I understand your concerns accurately the need to document assumptions so that they can be critically evaluated applies equally to all valuation methods.
For instance, assuming you use a market based multiples approach but do not make adjustments for the reasons for the mergers or acquisitions where in some cases the value paid is mainly to take out the competition or acquire customers.
Anyway, my two cents for the cause.
Best
Savio
Hi all,
I stumbled onto this article while trying to do research for my dissertation on the subject “Reliability vs Defensibility in Business Valuation of Non-publicly Traded Companies”. I’m also a big fan of Damodaran’s work and I hope I could get David Larrabee’s permission to post a link to invite all professionals here to take my dissertation survey that would not take more than 10 mins to complete. Thanks in advance and God bless.
https://www.surveymonkey.com/r/bizvaluation