A test for the arbitrage pricing theory which employs a multivariate linear regression model is developed. Given a sample of return premiums for a set of N assets which includes a subset of k linearly independent portfolios, the k factor APT hypothesis is accepted if the intercept term is zero in the multivariate regression of the returns on the k portfolios. The test may be carried out simply, by using univariate multiple regression software. The relation of this test to the concept of performance potential and Sharpe's measure of performance is also discussed. If the performance potential of the k portfolios is not significantly less than the performance potential of the complete set of N assets, then the k factor APT hypothesis is accepted.

The marginal performance contribution made by new assets in a portfolio is identified. The maximum change in a portfolio's Sharpe performance from the addition of new assets is a simple function of a generalized Jensen index and the unexplained covariances from a multivariate market model. Deviations from a higher dimension market line may be used to rank the desirability of asset additions to an existing portfolio. Statistical tests for the equality of the performance contributions by new assets is possible.