David Ricardo made a fortune buying bonds from the British government four days in advance of the Battle of Waterloo. He was not a military analyst, and even if he were, he had no basis to compute the odds of Napoleon’s defeat or victory, or hard-to-identify ambiguous outcomes. Thus, he was investing in the unknown and the unknowable. Still, he knew that competition was thin, that the seller was eager, and that his windfall pounds should Napoleon lose would be worth much more than the pounds he’d lose should Napoleon win. Ricardo knew a good bet when he saw it.
This essay discusses how to identify good investments when the level of uncertainty is well beyond that considered in traditional models of finance. Many of the investments considered here are one-time only, implying that past data will be a poor guide. In addition, the essay will highlight investments, such as real estate development, that require complementary skills. Most readers will not have such skills, but many will know others who do. When possible, it is often wise to make investments alongside them.
Though investments are the ultimate interest, the focus of the analysis is how to deal with the unknown and unknowable, hereafter abbreviated UU. Hence, I will sometimes discuss salient problems outside of finance, such as terrorist attacks, which are also unknown and unknowable.
This essay takes no derivatives, and runs no regressions. In short, it eschews the normal tools of my profession. It represents a blend of insights derived from reading academic works and from trying to teach their insights to others, and from lessons learned from direct and at-a-distance experiences with a number of successful investors in the UU world. To reassure my academic audience, I use footnotes where possible, though many refer to accessible internet articles in preference to journals and books. Throughout this essay, you will find speculations and maxims, as seems called for by the topic. They will be labeled in sequence.
Full PDF here: InvestinginUnknownandUnknowable
Via: hks.harvard.edu
