You know you love something when when you have the ill of following the trail of unanswered questions. It can't be defined as an obsession because you are not on its trail every single second. Sometimes, you put down the hunt, and you take a break that might last a decade.
Time erases everything else, and you don't even remember what was erased. They become leaves in the wind. However, no matter how windy, some questions remain crisp.
In my case, I always had a serious issue with some Finance models. I felt I had to be a very credulous person to believe the outcome. These models fall in the trap of similarity to reality gets confused with the real world.
In Finance, a lot of predictions are based on inputs like the Beta of a stock (the basis of CAPM). This is an amazing description of the risk / reward equation. Their visionaries earned the Nobel prize of economics for this discovery. And it is an amazing model to explain so many unanswered questions. Not only they found the ultimate pattern from where a lot of the chaos spawns, they proved it with models and comparing to actual historical samples.
At the end, if everyone accepts the mathematical model by principle, the model becomes reality until the model breaks. If everyone agrees on it, then it works. However, most analysts get the valuations wrong. Besides a hand full of people, they missed the financial collapse. Greenspan continued to mention the subprime crisis in his Congress hearings. There wwas talk about risks, but even in 2008, most analysts predicted a surge in stock prices, and the market drop a serious number: 38%.
After the crisis, CEOs mentioned how their toxic assets were correctly priced using their models while their prices were crumbling just outside the window. They were at peace justified by their models even though their companies were free falling. Then there was a call for the elimination of mark to market. Even though there is some Truth about not pricing a security in a distress market situation, the elimination of mark to market has a darker side: the implicit assumption that the model is correct and the market is wrong from that point on.
With access to the same information, the field of Finance and Accounting deliver two complete different answers.
Under US GAAP, the finding of the "Value" of an item needs to rely on a hierarchy of the truthfulness of inputs. They range from level 1 to level 3. It is simply the Law. Level 1 is considered the value of identical assets or liabilities traded on the active market with the highest volume. Level II are valuations based on secondary inputs. Level 2 contains the the valuation based on inputs like the Beta of a stock. The Level 3 in the hierarchy is management's predictions of the value of things.
You cannot use the beta of a stock to valuate a security when there is an actively traded market with the highest volume. You cannot rely on the earnings call when the securities are being actively traded at high volumes. Meanwhile, Finance models are taught under the solid assumption that results derived from secondaries values produce a more "realistic" value of the asset.
This is the beauty of liability. Science without the fear of burning on the stake becomes conjecture. Without liability, science ends in the hypothesis stage forgetting the feedback when we were wrong.
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On a side note, its application on portfolio management is without a doubt of unparalleled necessity.
