In this paper we investigate the empirical performance of an alternative beta risk estimator, which is designed to be superior to its conventional counterparts in situations of extreme thin trading. The estimator used is based on the sample selectivity model. The study compares the resultant selectivity-corrected beta to the OLS beta and Dimson Betas. We demonstrate the empirical behaviour of the selectivity corrected beta estimator using a sample of stocks in seven countries from Latin America. The results indicate that the selectivity-corrected beta does correct the downward bias of the OLS estimates and is likely to better estimate stock risk.