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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 ....

Monte Carlo , Mean Reversion , Value At Risk Var , Potential Future Exposure Models Pfe , Risk Management , Original Research , மான்டே கார்லோ , மதிப்பு இல் ஆபத்து வார் , பொடெந்ஶியல் எதிர்கால நேரிடுவது மாதிரிகள் பிபே , ஆபத்து மேலாண்மை , ஒரிஜிநல் ஆராய்ச்சி ,