Long-run performance evaluation: Correlation and heteroskedasticity-consistent tests

Although there is an extensive literature that evaluates long-run stock returns, the statistical tests that are commonly used are misspecified when event firms share common characteristics. For example, industry clustering or overlapping returns in the sample contribute to test misspecification. We propose a new test of long-run performance that allows for heteroskedasticity and autocorrelation. Our tests are well-specified in random samples and in samples with industry clustering and with overlapping returns.