Volatility Structures of ForwardRates and the Dynamics of the TermStructure:a Multifactor Case

For general volatility structures for forward rates, the evolution of interest rates may not be Markovian and the entire path may be necessary to capture the dynamics of the term structure. This article identifies conditions on the volatility structure of forward rates that permit the dynamics of the term structure to be represented by a finite-dimensional state variable Markov process. In the deterministic volatility case, we interpret then-factor model as a sum ofn unidimensional models.

Term Structure of Interest Rates Based on Artificial Neural Network

In light of the nonlinear approaching capability of artificial neural networks （ ANN）, the term structure of interest rates is predicted using The generalized regression neural network （GRNN） and back propagation （BP） neural networks models. The prediction performance is measured with US interest rate data. Then, RBF and BP models are compared with Vasicek＇s model and Cox-Ingersoll-Ross （CIR） model. The comparison reveals that neural network models outperform Vasicek＇s model and CIR model, which are more precise and closer to the real market situation.

Empirical Estimation of Term Structure of Interbank Rates in China

Nelson-Siegel model （ NS model） and 2 extended NS models were compared by using daily interbank government bond data Based on the grouping of bonds according to the residual term to maturity, the empirical research proceeded with in-sample and outof-sample tests. The results show that the 3 models are almost equivalent in estimating interbank term structure of interest rates. Within the term to maturities between 0 and 7 years, the gap of the absolute errors of the 3 models between in-sample and out-of-sample is smRller than 0.2 Yuan, and the absolute values of the in-sample and out-of-sample errors are smaller than 0. 1 Yuan, so the estimation is credible. Within the term to maturities between 7 and 20 years, the gap of the absolute errors of the 3 models between in-sample and out-of-sample is larger than 0.4 Yuan, and the absolute values of the in-sample and out-of-sample errors are larger than 1.0 Yuan, so the estimation is incredible.

Simulation Methods of Stochastic Volatility Interest Rate Term Structure

A term structure model bearing features of stochastic volatility and stochastic mean drift with jump （SVJ-SD model for short） is built in the paper to describe the stochastic behavior of interest rates.Based on sample data of an interest rate of national bond repurchase,maximum likelihood （ML）,linear Kalman filter and efficient method of moments （EMM） are used to estimate the model.While ML works well for simple models,it may lead to considerable deviation in parameter estimation when dynamic risks of interest rates are considered in them.Linear Kalman filter is a tractable and reasonably accurate technique for estimation cases where ML was not feasible.Moreover,when compared with the first two approaches,using EMM can obtain better parameter estimates for complex models with non-affine structures.

Perturbation Analysis of Structured Least Squares Problems and Its Application in Calibration of Interest Rate Term Structure

A structured perturbation analysis of the least squares problem is considered in this paper.The new error bound proves to be sharper than that for general perturbations. We apply the new error bound to study sensitivity of changing the knots for curve fitting of interest rate term structure by cubic spline.Numerical experiments are given to illustrate the sharpness of this bound.

PMCMC for Term Structure of Interest Rates under Markov Regime Switching and Jumps

A parameter estimation method,called PMCMC in this paper,is proposed to estimate a continuous-time model of the term structure of interests under Markov regime switching and jumps.There is a closed form solution to term structure of interest rates under Markov regime.However,the model is extended to be a CKLS model with non-closed form solutions which is a typical nonlinear and non-Gaussian state-space model(SSM)in the case of adding jumps.Although the difficulty of parameter estimation greatly prevents from researching models,we prove that the nonlinear and non-Gaussian state-space model has better performances in studying volatility.The method proposed in this paper will be implemented in simulation and empirical study for SHIBOR.Empirical results illustrate that the PMCMC algorithm has powerful advantages in tackling the models.

国债利率期限结构与货币政策传导机制研究——基于利率市场化与货币政策转型的双重视角

构建Nelson-Siegel模型拟合国债利率期限结构曲线的水平因子、斜率因子和曲率因子,在此基础上构建TVP-VAR模型,探究数量型和价格型货币政策框架下基于国债利率期限结构曲线的货币政策传导机制,并研究利率市场化对传导有效性的作用。实证研究表明:价格型和数量型货币政策对国债水平因子作用相同,但对斜率因子作用不同,通过斜率因子对金融市场利率和货币供给量的传导和通过水平因子的传导都具有相反的作用,说明政策利率通过国债斜率因子的传导仍存有阻塞;我国数量型货币政策传导机制仍能发挥一定作用,但传导有效性也逐渐减弱,随着利率市场化的推进,价格型货币政策传导有效性逐渐增强,但仍有局限性。对此,应该进一步完善国债收益率曲线,更好发挥国债收益率曲线的定价基准作用,推进利率市场化改革,加快疏通货币政策传导梗阻,并加快货币政策转型。

国债收益率与高频宏观因子--基于非规则混频利率期限结构模型

及时反映金融市场与宏观经济的动态作用机制是大数据时代制定前瞻性货币政策和投资决策分析的关键。重大突发事件增加了动态经济机制的不确定性,有必要挖掘高频信息加以识别。为此,本文提出一种非规则混频宏观利率期限结构(IR-MF-NS)模型,并基于我国国债收益率和宏观经济信息进行检验。研究发现:与传统模型相比,新模型国债收益率的拟合效果有所改善;国债收益率期限结构与宏观经济存在相互作用机制,实体经济活动与斜率因子呈负相关关系,这与我国逆周期监管目标相一致;高频曲度因子对通货膨胀产生显著正向持续性冲击,验证了曲度因子在高频数据中发挥重要作用的结论;经济机制受信息频率影响,低频数据的“平滑效应”使得低频经济机制表现出平稳效果;高频数据因为信息波动产生“反转效应”使得低频机制和高频机制出现背离;受到重大突发事件的冲击后,国债收益率与宏观基本面的联动性出现系统性减弱,期限结构因子的预测方差作用降低,而宏观基本面对国债收益率预测方差的贡献增大。

结构性货币政策对我国利率期限结构的影响——基于三因子视角

本文利用Nelson-Siegel模型构造反映利率期限结构的水平、斜率和曲率因子,并将其与结构性货币政策变量、回购利率、通货膨胀率一起建立向量误差修正模型(VEC),以此分析结构性货币政策对我国利率期限结构的短期波动和长期均衡影响。研究表明:通过Nelson-Siegel模型提取的利率期限结构三因子可以较好地体现出利率期限结构的形态特征。从长期来看,在“量”的方面,通过中期借贷便利操作释放流动性能够显著降低长期债券收益率,引起债券长短期利差的减少,收益率曲线变得更弯曲。在“价”的方面,提高常备借贷便利利率使得收益率曲线平坦化,但并未有效引起收益率曲线上移,而上调中期借贷便利利率,能够提高长期债券收益率,债券长短期利差增大,收益率曲线弯曲程度变小。本文通过对比数量型和价格型货币政策工具的实施效果,发现价格型货币政策工具对市场利率有着更显著的影响。

非参数利率期限结构模型的实证检验

利用随机过程的原理和非参数的核函数估计方法建立了非参数的利率期限结构模型 ,采用上海证券交易所的国债回购利率数据对建立的模型进行了实证检验 ,并与 Vasicek、CIR模型进行了比较 .结果显示 ,短期利率扩散过程的漂移函数和扩散函数都是非线性的 ,短期利率的概率分布不服从参数模型所假设的分布 .实证结果证实 ,与参数模型相比 。

利率期限结构与宏观经济因素的动态相依性——基于VAR模型的经验研究

利率期限结构的变化受到各种宏观经济冲击的影响,宏观经济冲击通过利率期限结构的变化影响到资产收益曲线。文章通过估计和检验结构VAR模型,发现货币冲击、供给冲击和价格冲击都对短期利率产生了持续显著的影响,而对长期利率则没有显著作用效果。宏观经济冲击只对收益曲线的截距参数具有显著影响,而对收益曲线的斜率参数和曲率参数的影响微弱。

银行同业拆借市场利率期限结构实证研究

对我国银行同业拆借市场利率期限结构进行了实证研究,实证结果表明:中国银行间同业拆借利率在亚洲金融危机后发生了结构性变化,金融危机发生之前我国银行同业拆借利率支持利率期限结构中的预期理论,但金融危机发生之后却不能给予预期理论以充分的支持.

利率的期限结构与经济增长预期

利率的期限结构是指在某一特定时点不同到期期限利率的集合.经济理论表明利率的期限结构中包含了关于市场对未来利率的预期、货币当局的政策态度、经济增长预期、通货膨胀预期、就业以及经济周期等方面的经济信息.文章根据有关的经济理论研究利率期限结构对未来经济增长的解释和预测能力.实证结果表明,利率期限结构在一定的期间内能够对未来的经济增长做出解释和预测.

基于三次样条函数的中国国债利率期限结构曲线构造

以上交所债券价格隐含的利率期限结构数据作为分析对象,利用三次样条函数构造出了中国的利率期限结构曲线,并对其作了相关的介评。

利率期限结构特征的拟合与预测

本文从经典利率期限结构模型和数量利率期限结构模型中选取了三因子Vasicek模型、三因子CIR模型、多项式样条模型、指数样条模型、DL模型和动态SV模型等6个应用广泛且具有代表性的利率期限结构模型,分别基于2008年7月至2014年3月中国和美国市场的月度国债收益率数据进行拟合与预测,并采用均方误差(RMSE)和平均绝对误差(MAE)对实证效果进行判别。结果表明,DL模型在针对中国市场和美国市场数据的拟合与预测方面能力均十分突出且效果稳定,指数样条模型次之,而其他模型则在利率期限结构特征的刻画效果方面存在更强的数据依赖与能力不足问题。本文的结论能够为实证研究利率期限结构特征的模型选取提供科学依据和数据支持。

基于Vasicek和CIR模型中的中国货币市场利率行为实证分析

本文引进了一种全新的计量经济学方法———广义矩估计法 ,并通过MATLAB程序 ,使用中国货币市场的数据对Vasicek和CIR模型进行了参数估计 ,与以前的估计方法相比 ,得出的结果都相当显著 ,从而能更好的了解中国货币市场利率行为的特点。

基于Vasicek和CIR模型的SHIBOR期限结构实证分析

基于无损卡尔曼滤波(UKF)估计方法,分别使用Vasicek模型和CIR模型对上海银行间同业拆放利率(SHIBOR)的动态特性进行刻画,并对其期限结构进行实证研究。在此基础上,对比分析两模型对SHIBOR数据的拟合性,结果表明:Vasicek模型和CIR模型对SHIBOR市场利率的动态特性均具有很好的刻画和描述能力,而Vasicek模型的数据拟合效果更好一些。