The Black Tuesday Attack: how to crash the stock market with adversarial examples to financial forecasting models

TL;DR

This paper explores the potential for adversarial manipulations to cause stock market crashes by deceiving financial forecasting models, highlighting a significant and underrecognized threat to economic stability.

Contribution

It introduces the concept of adversarial attacks on financial models, detailing how minor stock manipulations can trigger self-fulfilling crashes and proposing defense strategies.

Findings

Adversarial examples can induce market crashes without obvious signs.

Such attacks can target individual stocks or entire economies.

The threat is currently underappreciated and warrants urgent research.

Abstract

We investigate and defend the possibility of causing a stock market crash via small manipulations of individual stock values that together realize an adversarial example to financial forecasting models, causing these models to make the self-fulfilling prediction of a crash. Such a crash triggered by an adversarial example would likely be hard to detect, since the model's predictions would be accurate and the interventions that would cause it are minor. This possibility is a major risk to financial stability and an opportunity for hostile actors to cause great economic damage to an adversary. This threat also exists against individual stocks and the corresponding valuation of individual companies. We outline how such an attack might proceed, what its theoretical basis is, how it can be directed towards a whole economy or an individual company, and how one might defend against it. We conclude that this threat is vastly underappreciated and requires urgent research on how to defend against it.