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To be an investor is to live constantly at the intersection of story and uncertainty. We build our mental models, frameworks, and processes to try to accurately price securities and overlay them with a story about the economic, geopolitical, and psychological factors that frame the backdrop to value them. We create data-driven stories to explain our differentiated view of a security that is out of balance within its sector or asset class to justify a variant perception that we think will generate alpha. Sometimes, however, investors might create a framework that seems sound only to discover that the method is actually no better than a system to “win” at Russian Roulette. The key, of course, is to change your framework when the environment changes. Even the most sophisticated quant investors employing hundreds of PhD mathematicians and physicists find that their models can fall short due to the ever-changing topography of the surface area of relevant data.