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 the n-factor model as a sum of n 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.

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.

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.

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 out-of-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 smaller 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.

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。

变坡比衔接段结构阶梯溢洪道水力特性研究

该文依托庙堂水库溢洪道工程,采用数值模拟的方法对比了传统曲线型衔接段阶梯溢洪道与变坡比衔接段结构阶梯溢洪道的水力特性,结果表明:变坡比衔接段结构能够有效降低阶梯消能结构的流速,最大降低40%,校核工况下使得消力池进口流速降低47%,能有效缩短消力池的长度,节省工程造价;变坡比衔接段结构溢洪道负压幅值降低38%,降低了阶梯结构发生空化破坏的几率,同时阶梯溢洪道的消能率提高10%,更有利于溢洪道的消能。变坡比衔接段结构阶梯溢洪道的适用性更强,更有利于溢洪道的安全运行,可为类似工程提供参考。

多弧段曲边内凹蜂窝可调泊松比结构的力学性能研究

该文提出一种多弧段曲边内凹可调泊松比新型胞元。通过调整弧角,可以设计得到正泊松比、零泊松比和负泊松比的胞元结构。利用能量法求得结构的等效泊松比与等效弹性模量解析表达式,所得结果与有限元结果吻合较好。基于提出的新型胞元构建多胞蜂窝结构,利用数值方法讨论了低速和高速冲击作用下,正泊松比、零泊松比和负泊松比结构的冲击变形失效行为与单位质量能量吸收率。研究发现:低速冲击时,三种泊松比(正/零/负)结构的局部变形不同;高速冲击时,惯性效应使局部变形集中在冲击端,三种泊松比(正/零/负)结构的胞元变形模式不同。不论低速还是高速冲击,负泊松比结构都表现出优异的吸能效果。随着壁厚的增加,结构的吸能效果显著增强。

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。

结构性软土压缩特性研究

针对结构性软土的压缩性 ,通过对温州软土的原状土和重塑土在不同加压率下的固结试验 ,分析原状土和重塑土不同的压缩性状以及加压率对土体压缩性状的影响。在此基础上对已有的原位压缩曲线确定方法进行探讨 ,并结合对世界各地土样的试验室压缩曲线的分析 ,提出新的折线形原位压缩曲线确定方法。

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。

不同煤体结构类型煤的导电性质研究

为了从测井曲线中正确解译出原生结构煤和构造煤,指导煤矿安全生产和煤层气开发,使用4263B型LCR参数测试仪测试了频率1、10、100 kHz下原生结构煤和构造煤的视电阻率。测试结果表明:构造煤的视电阻率小于原生结构煤的视电阻率;在烟煤阶段煤岩的视电阻率随变质程度增加而增加,而到了无烟煤阶段突然减小;煤的视电阻率与测试频率成反比;煤的导电性具有各向异性特征,煤的不同极化方向视电阻率不同。对原生结构煤和构造煤导电性差异的研究有助于提高测井曲线解译的准确率。

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。

利率期限结构的样条估计模型及其实证研究

以B样条为基点,综合研究利率期限结构的样条估计模型,对多种样条模型进行理论推导和参数估计求解,并在此基础上做出实证比较分析。通过比较分析各个模型在利率曲线估计、债券定价和收益率估计等方面的实证结果,可以发现较少节点的三次样条模型是最为理想的。

基于模糊聚类与改进BP算法的日负荷特性曲线分类与短期负荷预测

提出了一种将模糊聚类技术与人工神经网络中的BP网络相结合的日负荷特性曲线分类与短期负荷预测的方法。通过模糊聚类技术将不同用户的负荷特性曲线进行分类,建立出不同的典型负荷曲线。然后利用同预测曲线相同类型的典型曲线,结合温度、日类型、湿度等对短期负荷预测影响较大的因素作为学习样本建立相应的BP网络模型。针对传统BP算法的不足,利用变学习速率和附加动量来改进BP算法并预测日负荷曲线。通过对实际日负荷曲线样本进行分类和对短期负荷进行预测证明该方法预测精度较高,在实际应用中具备可行性。