基于Vasicek和CIR模型的利率预测：一种分割方法
Forecasting interest rates through Vasicek and CIR models: a partitioning approach
摘要：
本文的目的是提出一种新的方法，允许预测，通过Vasicek和CIR模型，未来的预期利率（每个到期日）的基础上，从观察到的金融市场数据滚动窗口。新颖之处，除了使用这些模型不定价，但在一个给定的到期日的预期利率预测，包括在一个适当的划分的数据样本。这可以捕捉所有统计上显著的时间变化的利率波动，从而给出了一个帐户的跳跃在市场动态。新方法的性能进行了不同的期限结构，并测试两个模型。它示出了所提出的方法如何克服通常的挑战（例如，模拟状态转换，波动率聚集，倾斜的尾巴等）。以及当前以低利率至负利率为特征的市场环境所增加的新风险。
英文摘要：
The aim of this paper is to propose a new methodology that allows forecasting, through Vasicek and CIR models, of future expected interest rates (for each maturity) based on rolling windows from observed financial market data. The novelty, apart from the use of those models not for pricing but for forecasting the expected rates at a given maturity, consists in an appropriate partitioning of the data sample. This allows capturing all the statistically significant time changes in volatility of interest rates, thus giving an account of jumps in market dynamics. The performance of the new approach is carried out for different term structures and is tested for both models. It is shown how the proposed methodology overcomes both the usual challenges (e.g. simulating regime switching, volatility clustering, skewed tails, etc.) as well as the new ones added by the current market environment characterized by low to negative interest rates.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
