In a broad analytical context, noise refers to information or activity that confuses or misrepresents genuine underlying trends.  


Used in the context of equities, noise signifies stock market activity caused by program trading, dividend payments or other phenomena that is not reflective of overall market sentiment. In this context, it is also known as "market noise." The concept of noise was formally introduced in a landmark 1986 paper by economist Fischer Black, where he stated that "noise" ought to be distinguished from "information" and that a disproportionate amount of trading occurred on the basis of noise rather than evidence.

All trading is somewhat speculative, but noise traders are considered to be particularly reactionary, relying on trending news, apparent surges or declines in prices or word of mouth rather than the fundamental analysis engaged in by more experienced traders. In general, the shorter the time frame, the more difficult it is to separate the meaningful market movements from the noise. The price of a security will vary widely throughout a given day, but almost none of this movement represents a fundamental change in the perceived value of the security. Some noise traders attempt to take advantage of market noise by entering buy and sell transactions without the use of fundamental data.  

If most market fluctuation is noise, however, then most traders are noise traders. Only hindsight provides assurance of the credibility of information, and when buying and selling stocks at a rapid pace, it is difficult to distinguish "information" from "noise." However, there are some fairly predictable market fluctuations that are known to be unreliable as indicators. It is almost always a bad idea to make trades based on information you've received only that day: the price of a security will fluctuate wildly within a day, and much of this price movement is deliberately manipulated by professional traders to manufacture market advantages.

Furthermore, much of this trading is actually program trading, which means that a large investment institution has programmed computers to make trades when prices reach a certain level. It's also advisable to be on the lookout for artificial bubbles, which are often created when many noise traders congregate their purchases around a single company or industry, and for corrections, reverse movements of more than 10% of the value of a security which occur as adjustments to a significant overvaluation of the security.

Most effective traders have personal standards or processes which they use to make trading decisions: they know how much they'll risk on a trade and they know, with some precision, what will constitute a wise move for their current position. Generally, people who do not have a process for arriving at a decision are more susceptible to noise trading. Making decisions based on personal standards doesn't remove susceptibility to misinformation, but traders who know what they're looking for are far less likely to be swayed by noise than traders who rely on news or other fluctuations.