Is It Real, or Is It Randomized?: A Financial Turing Test

TL;DR

This study demonstrates that humans can reliably differentiate real financial data from randomized data in an interactive game, challenging the idea that markets are inherently random and highlighting human perceptual abilities.

Contribution

The paper introduces a novel financial Turing test using an online game to assess human ability to distinguish real from randomized financial returns, with evidence of human perceptual skills.

Findings

Subjects can reliably distinguish real from randomized returns (p ≤ 0.5%).

Humans outperform random guessing in the financial Turing test.

Immediate feedback enhances learning and adaptation in the task.

Abstract

We construct a financial "Turing test" to determine whether human subjects can differentiate between actual vs. randomized financial returns. The experiment consists of an online video-game (http://arora.ccs.neu.edu) where players are challenged to distinguish actual financial market returns from random temporal permutations of those returns. We find overwhelming statistical evidence (p-values no greater than 0.5%) that subjects can consistently distinguish between the two types of time series, thereby refuting the widespread belief that financial markets "look random." A key feature of the experiment is that subjects are given immediate feedback regarding the validity of their choices, allowing them to learn and adapt. We suggest that such novel interfaces can harness human capabilities to process and extract information from financial data in ways that computers cannot.