Need to know Our Monte Carlo simulation results indicate that the widely-used least squares estimations of the Vasicek model suffer significant small-sample biases even if the sample length reaches as long as 30 years. Bias-corrected estimators could substantially reduce the small sample biases of the least squares estimations, and further project much more accurate value-at-risk and potential future exposure estimates. Empirical applications to a variety of time series are in general in line with the Monte Carlo simulation results. Abstract We evaluate the usefulness of bias-correction methods in enhancing the Vasicek model for market risk and counterparty risk management practices. The naive bias-corrected estimator, the Tang and Chen bias-corrected estimator and the Bao