Aswath Damodaran is a Professor of Finance at the Stern School of Business at New York University where he teaches corporate finance and valuation courses in the MBA program. He received his MBA and Ph.D degrees from the University of California at Los Angeles. Mr. Damodaran’s research interests lie in valuation, portfolio management and applied corporate finance. His papers have been published in several of the most prestigious academic journals and he has published 10 acclaimed investment and finance books, including the best-selling Damodaran on Valuation.
InvestingByTheBooks: Thank you for agreeing to talk to us about your latest book Narratives and Numbers. I very much enjoyed reading it and one thing contributing to this was that you seamed to enjoy writing it. Could you start by discussing this personal journey of yours from being a numbers guy to a more balanced position?
Aswath Damodaran: I am a natural number cruncher and when I first starting doing and teaching valuation, I gravitated towards a purely numbers approach. It was a few years into the process that I realized that while I could work through the mechanics of valuation, I had no faith in my own valuations (partly because I knew how easily I could make them move by changing a few numbers). It was then that I started recognizing that my spreadsheets would become valuations only if I attached stories to them. When I started, it was hard work but I have to tell you that it has become easier over time.
IBB: With regards to valuing corporations with a very wide value potential distribution compared to those with a more narrow potential I agree that both are technically possible to value with a DCF. However, while the latter type more rarely gets mispriced, when they occasionally do, you can be relatively more certain about your margin of safety and given our human propensity for over-optimism I’m afraid that a wide distribution simply means a larger outlet for that bias. What is your view on this?
AD: I think that the margin of safety is one of the most over rated concepts in investing. While there is the notion that having a large MOS is somehow costless, it is worth reframing the trade off in using a MOS. In effect, you are trading off one type of error (that you will buy an over valued stock by mistake) for another type of error (that you will not buy an under valued stock). In my view, that trade off starts to cut against you sooner than you think and as your portfolio gets larger. If you are one of those incredible investors who keep finding stocks that go up 40% a year, by all means have a large margin of safety. When For the most part, when I hear an investor boast about having a 40% MOS, my response is that the investor either is mostly invested in cash or that he or she has no concept of value.
IBB: How will we ever persuade sell-side analysts to treat quarterly earnings releases as opportunities to revisit and update their view on the long-term fundamental story instead of playing the “against the consensus-game”?
AD: Why bother? That’s their job. Treat them for what they are… Equity research analysts are traders, not investors, and they play the momentum game. They have only a glancing interest in the value of stocks and have far more incentive to keep track on the mood on a stock. I just wish that they would stop doing their “kabuki” DCFs.
IBB: Daniel Kahneman has when it comes to forecasting been discussing what he calls the inside view and the outside view where the latter relates to the more statistical answer to the question: when others in general have been in the same situation, what on average happened? I read your narrative process as a way to improve on the inside view but aren’t you still missing to factor in the outside view?
AD: My step 5 in converting stories to numbers is, keeping the feedback loop open and it, is just my way of saying that the only way that you will improve your stories is by listening people who think least like you and disagree with you the most. So, listen to others when they tell you that you are wrong, don’t be defensive and don’t be afraid to say those words “I was wrong”.That outside view does not necessarily come from other valuation people or analysts but from the world around you.
IBB: I liked the notion that exactly as stock market stories can create herding and mispricings on the stock markets, quantitative over-usage of the same type of factors can do the same. You mention somewhere in the book that you think that it is those who can remain flexible in their thinking that will succeed. Could you explain further what you mean?
AD: To the extent that we look at the same data and see the same patterns and follow those patterns, big data is going to create its own form of herding. You see this in almost every aspect of life where data has become a big part of decision making. One reason that I trust multi-disciplinary thinkers more is that they use both the data and common sense. Being flexible requires you to be open to information in every form.
IBB: What you call narratives are really the description of the fundamental value creation of the company but how do you prepare your students for the constant cacophony of shorter term stories, rumors, suggestions and emotions on the stock market? Do you for example feel that checklists can help?
AD: I think of your core story as a filing mechanism that allows you to read news about the company as it happens and file into the right folder. In fact, I try to do this with Uber in the book when I explain how I used the hundreds of news stories that came out about Uber between June 2014 and September 2015 to reframe my story.
IBB: I think the concept of blending a going concern valuation with a liquidation valuation is very interesting. How would you go about when thinking about the probability of default given the reportedly shortening life span of companies?
AD: Shortening life span does not necessarily translate into default. Most companies just fade away over time or get acquired as going businesses, rather than come to an abrupt end. What causes default is the addition of a triggering mechanism, usually in the form of debt. And with debt, estimating that probability of default becomes easier since you are looking at the likelihood of a firm not being able to make contractual payments.
IBB: With regards to the limited success rate of macro forecasting I agree fully. Does this mean that investors should simply stay away from stocks where one or two top-down variables determine the stock price or do you have a solution for how to handle them?
GZS: It is not that they should stay away. You can still find a macro stock at a micro moment. For instance, with banking stocks, it is quite clear that the dominant risks now are regulatory changes and interest rate levels, both macro variables. But in October 2016, I valued and bought Deutsche Bank because I felt that there were enough micro variables that I could focus on to make it a good buy.
IBB: Thank you for taking the time and sharing your insights. Lets hope your book unites the two camps of numbers people and storytellers.
InvestingByTheBooks, March 3, 2017