We propose an algorithm which predicts each subsequent time step relative to the previous timestep of intractable short rate model (when adjusted for drift and overall distribution of previous percentile result) and show that the method achieves superior outcomes to the unbiased estimate both on the trained dataset and different validation data.

翻译：我们提出一种算法，该算法在考虑漂移调整及前一分位结果总体分布的情况下，预测难解短期利率模型中每个后续时间步相对于前一时间步的变化，并证明该方法在训练数据集及不同验证数据上均优于无偏估计的结果。