英文标题：
《Modeling Nelson-Siegel Yield Curve using Bayesian Approach》
---
作者：
Sourish Das
---
最新提交年份：
2018
---
英文摘要：
  Yield curve modeling is an essential problem in finance. In this work, we explore the use of Bayesian statistical methods in conjunction with Nelson-Siegel model. We present the hierarchical Bayesian model for the parameters of the Nelson-Siegel yield function. We implement the MAP estimates via BFGS algorithm in rstan. The Bayesian analysis relies on the Monte Carlo simulation method. We perform the Hamiltonian Monte Carlo (HMC), using the rstan package. As a by-product of the HMC, we can simulate the Monte Carlo price of a Bond, and it helps us to identify if the bond is over-valued or under-valued. We demonstrate the process with an experiment and US Treasury\'s yield curve data. One of the interesting observation of the experiment is that there is a strong negative correlation between the price and long-term effect of yield. However, the relationship between the short-term interest rate effect and the value of the bond is weakly positive. This is because posterior analysis shows that the short-term effect and the long-term effect are negatively correlated.
---
中文摘要：
收益率曲线建模是金融学中的一个基本问题。在这项工作中，我们探讨了贝叶斯统计方法与Nelson-Siegel模型的结合使用。我们提出了Nelson-Siegel屈服函数参数的分层贝叶斯模型。我们在rstan中通过BFGS算法实现MAP估计。贝叶斯分析依赖于蒙特卡罗模拟方法。我们使用rstan软件包执行哈密顿蒙特卡罗（HMC）。作为HMC的副产品，我们可以模拟债券的蒙特卡罗价格，这有助于我们确定债券是高估还是低估。我们通过一个实验和美国财政部的收益率曲线数据证明了这一过程。实验中一个有趣的观察结果是，价格与收益率的长期效应之间存在着强烈的负相关。然而，短期利率效应与债券价值之间的关系为弱正。这是因为后验分析表明短期效应和长期效应呈负相关。
---
分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Statistical Finance        统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
--

---
PDF下载：
-->