We take on three prevalent myths that shroud the complex and multifaceted world of valuation. From the notion of valuation as an objective pursuit to the importance of model complexity, we reveal the realities that lie beneath these deep-seated misconceptions.
As we debunk these myths, we hope to give you a fresh perspective on valuation - revealing it as a process intimately tied to bias, embracing imprecision as a strength rather than a flaw, and championing simplicity over complexity.
Myth #1: A valuation is an objective search for true value
The notion that valuation is an objective quest for true value is actually a myth. In reality, all valuations inherently bear the mark of bias, shaped by factors including the source and size of remuneration. The pivotal queries are not about the existence of bias but rather its extent and its direction. Intriguingly, the degree and orientation of this bias tend to move in tandem with who is financing the valuation and the sum of payment involved. Thus, every valuation subtly mirrors the interests of its financer, puncturing the illusion of objectivity and reinforcing the true nature of valuations as subjective interpretations of worth.
Truth #1
All valuations are biased. The only questions are “how much” and in which direction.
The direction and magnitude of the bias in your valuation is directly proportional to who pays you and how much you are paid.
Myth #2: A good valuation provides a precise estimate of the value
The myth that a good valuation equates to a precise estimate of value obscures the reality of this intricate process. Truth be told, the nature of valuation precludes any claim of absolute precision. Uncertainty and complexity are inherent to the realm of valuation, rendering any notion of unerring precision a chimera. Paradoxically, it is in these instances of the least precision, when the cloak of certainty is pulled back to reveal the chaotic undercurrents of market forces, that valuation yields its greatest rewards. Through this lens, imprecision in valuation is not a drawback but a testament to the nuanced and intricate dance of market dynamics.
Truth #2:
There are no precise valuations.
The payoff to valuation is greatest when valuation is least precise.
Myth #3: The more quantitative a model, the better the valuation
The belief that the degree of a valuation model's complexity corresponds directly to its efficacy is a pervasive myth. Reality dictates that the comprehensibility of a valuation model often diminishes with an increase in the number of its required inputs. In fact, simplicity often triumphs over complexity in this sphere, with more straightforward models consistently outperforming their intricate counterparts. It is a testament to the profound truth that in the realm of valuation, less is often more, and understanding trumps complexity.
Truth #3:
One’s understanding of a valuation model is inversely proportional to the number of inputs required for the model.
Simpler valuation models do much better than complex ones.
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