Random Walk Theory
Random walk theory holds that stock price changes are random and unpredictable, so past price movements cannot reliably be used to forecast future ones.
The idea dates back to Louis Bachelier's 1900 thesis and was popularized by Burton Malkiel's 1973 book A Random Walk Down Wall Street. It argues that each day's price change is independent of previous changes, much like a series of coin flips, because new information arrives unpredictably and is quickly priced in.
If prices follow a random walk, technical analysis based on chart patterns should not consistently beat the market, and the best estimate of tomorrow's price is roughly today's price plus a small long-term drift.
The theory is closely tied to the efficient market hypothesis and supports the case for low-cost index investing. Critics point to evidence of momentum, mean reversion over certain periods, volatility clustering and market bubbles as signs that prices are not perfectly random.
In forecasting, the random walk is widely used as a benchmark. Example: a model predicting next month's price should be compared against simply assuming no change; a model that cannot beat that baseline adds little value.