An expression relating estimation precision in the classical linear model to the number of parameters k and the sample size n is illustrated. A rule of thumb for the sample size is suggested.

This article explores the use of information-theoretic explanatory variables in stock price forecasting regressions. Stock price changes, as the dependent variable, is run against traditional explanatory variables such as lags of price changes and lags of the squares of the price changes. The...