WARNING: Physics Envy May Be Hazardous To Your Wealth!

TL;DR

This paper critiques the overreliance on physics-inspired models in economics, proposing a new taxonomy of uncertainty and illustrating its relevance with examples from physics and finance, to improve understanding of market behavior and tail events.

Contribution

It introduces a novel taxonomy of uncertainty for economic modeling and offers an alternative perspective to physics envy in financial analysis.

Findings

Physics-inspired models can mislead economic predictions.

A new uncertainty taxonomy helps better understand market tail events.

Quantitative strategies can benefit from the proposed uncertainty framework.

Abstract

The quantitative aspirations of economists and financial analysts have for many years been based on the belief that it should be possible to build models of economic systems - and financial markets in particular - that are as predictive as those in physics. While this perspective has led to a number of important breakthroughs in economics, "physics envy" has also created a false sense of mathematical precision in some cases. We speculate on the origins of physics envy, and then describe an alternate perspective of economic behavior based on a new taxonomy of uncertainty. We illustrate the relevance of this taxonomy with two concrete examples: the classical harmonic oscillator with some new twists that make physics look more like economics, and a quantitative equity market-neutral strategy. We conclude by offering a new interpretation of tail events, proposing an "uncertainty checklist" with which our taxonomy can be implemented, and considering the role that quants played in the current financial crisis.