Technical trading rules use patterns in past prices, such as moving averages and trading-range breakouts, to generate buy and sell signals for predicting future returns. Brock, Lakonishok, and LeBaron's (1992) "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns" tested these rules on Dow Jones Industrial Average data. The full sample contained 25,806 daily observations from 1897 to 1986, and buy signals earned an average daily return of 0.042 percent. Sell signals earned -0.025 percent daily, a pattern not consistent with the random walk, AR(1), GARCH-M, or Exponential GARCH null models.
What the Study Found
Buy signals from the variable-length moving-average rule produced an average daily return of 0.042 percent, about 12 percent annualized, over the full 1897-1986 sample. Sell signals produced an average daily return of -0.025 percent, about -7 percent annualized. Daily standard deviation was 1.34 percent during sell periods versus 0.89 percent during buy periods. Across all 10 variable-length moving-average rules tested, the average buy-sell spread on the full sample was 0.00067. The fixed-length moving-average rule produced a 10-day buy-sell spread of 0.77 percent with no band and 1.09 percent with a one percent band.
Methodology
The study uses daily closing prices of the Dow Jones Industrial Average, a continuous series available since 1897. The full sample contains 25,806 daily observations from the first trading day of 1897 to the last trading day of 1986. Returns following buy and sell signals from variable-length moving average, fixed-length moving average, and trading range break-out rules were tested separately across four nonoverlapping subperiods. Statistical significance was assessed using bootstrap simulations with 500 replications under four null models: the random walk, AR(1), GARCH-M, and Exponential GARCH.
Key Statistics
| Metric | Finding | Context |
|---|---|---|
| VMA buy vs. sell daily return, full sample | 0.042% vs. -0.025% | 1897-1986, variable-length moving average rule |
| VMA buy vs. sell daily standard deviation | 0.89% vs. 1.34% | 1897-1986, variable-length moving average rule |
| Average VMA buy-sell spread (10 rules) | 0.00067 | 1897-1986 full sample, Table II |
| FMA buy-sell spread, no band vs. 1% band | 0.77% vs. 1.09% | 10-day holding return, full sample 1897-1986 |
| TRB average buy-sell return | 0.86% | 10-day holding return, full sample 1897-1986, six rules |
| AR(1) null model | r_t = b + ρr_{t-1} + ε_t | Used in bootstrap simulations against trading rule returns |
| GARCH-M null model | r_t = a + γh_t + bε_{t-1} + ε_t | Used in bootstrap simulations against trading rule returns |
Why This Matters
The persistent gap between returns following buy signals and sell signals challenges the view that past prices carry no information about future returns. Because the pattern held up against four different statistical models of return behavior, it is not easily dismissed as an artifact of one model choice. For risk-based theories of asset pricing, a profitable rule that requires no additional measurable risk is difficult to reconcile with standard models. For practitioners, the results offered early rigorous statistical evidence that simple, widely used technical rules captured a real pattern in historical price data.