This month we speak to the narratives that pervade the investment ecosystem. Skimming through Damodaran’s “tribes” (storytellers and number crunchers) humorously reminds one of Twain’s “lies, damned lies, and statistics”. Yet the narrative plays an important part in a manager’s communication with clients and potential clients; after all, written commentary with supporting statistics can be pretty dry to fully digest. But what of the poor allocator drowning in a sea of narratives? They must recognize the stories, admit their attraction to them, and design a disciplined way to analyze and react to them.
“If you don’t like what’s being said, change the conversation.”
Don Draper, Mad Men
Aswath Damodaran’s Narrative and Numbers is required reading for those who analyze companies. In it, he references two tribes of investment people — the number crunchers and the storytellers — but makes a persuasive case that valuing a company well (and communicating your views effectively) requires using both sets of skills.
Throughout the book, Damodaran offers several frameworks to use, starting with the steps of “the story-to-numbers process”: 1) develop a narrative for the business you are valuing; 2) test the narrative to see if it is possible, plausible, and probable; 3) convert the narrative into drivers of value; 4) connect the drivers of value to a valuation; and 5) keep the feedback loop open. He then uses a number of case studies of well-known companies and the actual valuations that he had prepared over the years to illustrate those five steps.
This framework leads to the realization that there are two sides to asset management – the need for asset management firms to craft an “effective and truthful” message and, conversely, the main job of the asset allocator to crack that narrative.
In his recently-released book Narrative Economics, Robert Shiller argues that investors should pay attention to viral stories and the impact they have on economic behavior. The human brain is naturally attuned to narratives, whether factual or not. Fake news! He refers to President Trump as a master of the narrative; inspirational for some, a source of alarm for others. But the market impact is unmistakeable – just follow his tweets around US/China negotiations and the impact on market price.
To deviate from the narrative is very hard. First, the analyst typically has an unwieldy data set: in short, too many companies to follow in too little time. Next, we’re biased to suspending disbelief while listening to stories in order to be entertained. And finally, we’re vulnerable to what NasimTaleb calls the narrative fallacy – looking backward and creating a pattern to fit events and constructing a story that explains what happened along with what caused it to happen.
Unfortunately, due diligence in the investment process has become too much of a standardized documentation process. Rather than investigative discovery, analysts tend to check boxes by going to lunches and listening to company executives and IR professionals provide corporate spin. The most important part of due diligence – ferreting out new information – may be overlooked.
We like to think that we carefully gather and evaluate facts and data before coming to a conclusion. Instead, we tend to suffer from confirmation bias and thus reach a conclusion first. Only thereafter do we gather facts and see those facts in such a way as to support our pre-conceived conclusion. Perhaps most significantly, we inherently prefer narrative to data — often oblivious to the fact that organizational structure and not past performance, is likely to predict long-run future performance.
And what of the investment allocator? Their conundrum was perhaps best summed up by Rusty Guinn’s note in Epsilon Theory: Do I invest on the basis of reality, meaning the fact that wage inflation is, in fact, picking up in a remarkably steady fashion in the real economy? Or do I invest on the basis of Narrative abstractions that I can anticipate being presented and represented to markets at regularly scheduled moments of theater? Because the investment strategy for the one is almost diametrically opposed to the investment strategy for the other.
We find managing a small data set – great businesses held for the very long term – skirts the mainstream narrative. It focuses our attention on organizational structure –management and business strategy – and allows us time to investigate, conceptualize, and better understand the framework by which a great investment will thrive.
