Book-review: Narrative and Numbers, Damodaran

We either cater to the story telling or numbers crunching profession. Good valuation requires both.

If you prefer to read the pdf version click here. (links may not work, but better readability)

(as in my previous book review I focus more on my learnings/insights/personal summary vs writing style etc.)

We either cater to the story telling or numbers crunching profession. Good valuation requires both.

Based on the first few pages the book is not what I believed it to be. I thought it is about improving valuation process be connecting a strory to our numbers and testing this story with numbers. The first sections were about telling better stories in the sense of promoting a business, ie. as founder/CEO — and the sub-title indicates this: ‘the value of stories in business‘. I was lucky to read on, since the chapters became much better, imo.

Both our stories and numbers are biased. Sensitivity analysis is often performed after the decision and only presented to create a feeling a control, but, we do not control things by merely being able to measure things.

Possible, plausible, probable is a framing from Damodaran I was happy to read about once more. His Uber case (p94) is a good example but in general the lines between possible/plausible/probable are blurry. In such cases thinking in impossible, implausible, and improbable can help.

Our narratives or stories need to be formulated, tested and, ultimately incorporated in our valuation estimates. Damodaran refers to the Valuation Triangle between growth, reinvestment, and risk which needs to be passed for a possible/plausible story. After the Valuation, our narratives can be refined and updated when we receive new information.

Narratives break during market crashes. In general, narratives break less often for mature companies with lower uncertainty. The value-price gap is often wieder for younger companies and here investors might find the best investment opportunities. (how well suited for 2022. Think Peloton, Netflix, etc. Or energy companies a few months down the road during a recession? 🤔)

Earnings reports are mostly viewed for earnings beats or misses, which is more of a trader activity. Long term value investors should rather scan the reports for narrative violations or, less strictly, needed minor narrative tweaks.

Other corporate news are less frequent but can include more meaningful information. Dividend increases or instatements can indicate managers’ higher trust in future profitability and/or less growth opportunities. Buybacks indicate less trust since they more flexible and easier to cancel. Debt indications are similar to dividends. In addition the firm uses tax shields. Acquisitions are of course important news esp. If your story is about a serial acquirer.

Macro stories have to be identified and treated as such. Further, one has to decide on the path one wants to take. No clue (i) and taking market spot/fwd prices or having an opinion (ii). If it is about a commodity company, and one has an opinion, we should do two valuations, and seeing the difference between (ii) and (i) due to our personal view. The important macro variable can be commodity prices, interest rate, or the economic cycle in a particular country/region/global. For emerging market companies it is often a combination of listed factors plus local politics.

His Vale valuations include some lessons: ttm operating income did not reflect downward sloping iron ore prices but were lagging, as was the sovereign rating of Brazil. Here CDS were much fast to incorporate on the ground developments, and thus risk was underestimated as was cost of capital. In addition, political problems usually take a longer time to be solved. A huge debt load magnifies problems.

The corporate life cycle is also a great framework from him that I was more than happy to read about once more. Early in the cycle narrative should drive numbers, and later numbers should drive narrative.

Investor skill sets are different. Old time value investors will make money by number crunching mature businesses and evaluating their moats and competitive advantages (i tend to be here). If one likes uncertainty and big shifts in value, young companies are your hunting ground, if you don’t mind to be terribly wrong.

Investor tool kits contain more detailed DCF models for mature firms built on historical company data delivering reasonable values, whereas models for young companies are lean and allow for quick input changes (due to narrative changes) and start from the total market.

The managerial challenge results from different management requirements during the corporate life cycle. A visionary is needed first, the an opportunistic CEO for profitable growth, but in its declining phase a pragmatic realist is needed who is comfortable shrinking the company.

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