Noise Trading
Noise Trading refers to buying and selling securities based on irrelevant information, sentiment, rumors, or cognitive biases rather than fundamental value analysis, introducing price volatility and deviations from efficient prices that can persist when noise traders are numerous enough to represent a significant portion of market activity.
The concept of noise trading was developed by Fischer Black in his 1986 Presidential Address to the American Finance Association, titled simply 'Noise.' Black distinguished between traders who trade on information (informed traders) and those who trade on noise — signals that they mistakenly believe contain information but in fact do not. Noise traders might be reacting to news that is already priced in, following price trends without underlying fundamental support, or making decisions based on emotions like fear and greed rather than rational analysis.
Noise trading is not synonymous with stupidity or irrationality in a simple sense. Behavioral finance research has demonstrated that even well-educated investors systematically fall prey to cognitive biases. Overconfidence leads investors to trade too frequently. The disposition effect causes investors to sell winners too early and hold losers too long. Herding behavior drives investors to pile into trending assets, amplifying price momentum. Loss aversion causes asymmetric reactions to gains and losses. These patterns aggregate into noise trading that creates temporary but sometimes significant price dislocations.
The critical insight from De Long, Shleifer, Summers, and Waldmann's 1990 paper on noise trader risk is that noise trading can affect prices even in markets populated by rational arbitrageurs. If rational investors cannot be certain when a noise-driven mispricing will correct, they face noise trader risk — the possibility that the mispricing gets worse before it gets better. This risk limits the capital rational traders commit to correcting mispricings, allowing noise-driven deviations to persist longer than pure efficiency theory would predict.
For practical investors, noise trading represents both a risk and an opportunity. As a risk, excessive trading driven by noise destroys returns through transaction costs and taxes. Studies of individual investor brokerage accounts consistently find that the most active traders generate the worst risk-adjusted returns. As an opportunity, disciplined contrarian and value investors can potentially profit from mispricings created by noise trader overreaction — though timing and position sizing require careful judgment about how long and far the mispricing can run before reversing.
Retail-dominated small-cap stocks, meme stocks, and newly listed companies with uncertain fundamentals tend to have higher noise trader representation than large, extensively covered blue chips. Price volatility in these segments often reflects sentiment shifts more than changes in fundamental value.