基于NS族模型的中国公司债信用利差预测

本文以中国公司债为研究对象, 基于NS族模型研究了信用利差的预测问题。通过对不同期限、不同信用评级公司债信用利差的样本内外预测效果进行实证比较, 得到主要结论如下:(1)模型对中长期公司债信用利差的预测误差低于短期公司债。(2)不同信用评级公司债信用利差的预测效果受剩余到期期限的影响:1年期的AAA级公司债的预测误差低于AA+和AA级公司债; 5年期的AA+级公司债的预测误差低于AAA和AA级公司债; 10年期的AA级公司债的预测误差低于AAA和AA+级公司债。成果为各经济主体预测信用利差提供了具体思路和方法, 有利于做出合理的金融决策。     

公司债信用利差对产出和通胀的预测——基于BMA模型的研究

本文研究了2008年1月至2016年10月期间中国公司债信用利差对于产出和通胀的预测能力,通过将公司债按照期限和信用级别划分为不同组合得到多个信用利差序列,利用BMA框架下的样本外预测方法对工业增加值指数和居民消费者指数进行预测研究,结果显示信用风险较高以及到期期限较短的信用利差对产出包含显著的预测信息,且预测能力随时间变化而发生变化。这一方面表明了我国公司债信用利差已经包含了显著的经济前瞻性信息,债券定价市场化改革成果得以显现;另一方面也成为我国存在金融加速机制的实证依据,为宏观经济的预测和政策制定提供参考。     

中美两国公司债信用利差动态过程比较研究

选取中美两国2011年1月至2017年4月的公司债和国债月度交易数据,基于SV模型得到两国公司债的信用利差序列,进而对中美两国公司债的信用利差进行时间序列比较分析.实证发现,中国公司债信用利差序列表现出自回归和移动平均特征,而美国公司债信用利差序列则仅呈现自回归特征;在方差结构方面,中国公司债信用利差序列的残差不具有ARCH效应,而美国公司债信用利差序列的残差具有明显的ARCH效应.同时,对中美两国公司债信用利差建立VAR模型并进行脉冲响应分析,发现中美两国信用利差序列的相关性不强,对彼此的冲击的反应均较弱,为债券市场投资者构建跨国市场债券组合来分散信用风险提供决策支持.     

基于共轭几何变换程序的国债市场利率期限结构波动建模

本文变革已有的利率期限结构模型估计依赖于定价误差平方和最小化原则,引入几何双重变换程序解决非线性约束的误差绝对距离最小化问题,丰富国债市场利率波动和定价研究的理论体系和研究方法;运用负指数平滑立方L₁样条优化模型,克服B样条函数对节点数目与定位的过度敏感和放宽对贴现函数的二阶导数平滑要求,协同拟合误差绝对距离与贴现函数波动率最小化,保留B样条函数刻画中长期利率波动趋势的优势,增强对短期利率波动结构突变的估计、定价和预测能力,缓解B样条和NSS模型在利率期限结构拟合存在的过度波动问题。     

基于组合预测的静态利率期限结构优化模型

针对单个静态利率期限结构模型在拟合收益率曲线时的不足,本文引入组合预测的方法,在绝对误差和与方差和最小准则下,分别建立了静态利率期限结构组合优化模型,并给出了模型的遗传算法求解过程。然后将上海证券交易所2004～2009年的国债每日交易数据分为样本内数据和样本外数据,对多项式样条、指数样条、NS、SV和组合优化模型进行实证比较。结果表明：无论是对于样本内数据的拟合,还是对于样本外数据的预测,组合优化模型的统计特征指标几乎都要优于其他单一模型,并且具有良好的适应性和稳健性,适用于拟合我国国债利率期限结构。     

基于不同核函数的非参数与参数利率模型的国债定价

以上海证券交易所的国债回购利率数据为样本,本文采用两种不同核函数:高斯核和抛物线核对非参数利率期限结构模型进行估计.结果显示:短期利率的密度函数是非正态的,扩散过程的漂移函数和扩散函数都是非线性的,高斯核比抛物线核对扩散函数拟合更平滑.然后,给出了基于非参数和参数利率模型的国债定价的方法,并对非参数利率模型、Vasicek模型、CIR模型、多项式样条静态模型进行国债定价预测比较与分析.     

基于样条变换的PLS回归的非线性结构分析

基于样条变换的:PLS非线性回归模型既吸取了样条函数分段拟合以适应任意曲线连续变化的优点,又借鉴了偏最小二乘回归方法能够有效解决自变量集合高度相关的技术.针对多元加法模型,从理论和仿真试验的角度分别验证了,对于多个独立自变量对单因变量为非线性关系的数据系统,基于样条变换的PLS回归方法不仅能够有效实现自变量对因变量的整体预测,而且能够提取各维自变量对因变量的单独非线性作用特征,从而确定数据系统内部的复杂非线性结构关系,增强了模型的可解释性.     

我国人口时间序列的变系数预测模型

根据1952-2005年我国人口总量和GDP总量数据,建立变系数模型.采用逐步回归的方法来选择显著滞后变量子集,推导出系数函数的样条估计表达式,最后运用Bootstrap思想,进行点预测和区间预测。运算结果表明:对于该组数据,变系数模型能较理想地描述数据之间的内在结构,且具有较少的预测误差.     

部分函数线性变系数模型的样条估计及其应用

本文针对Tecator数据介绍一种新的模型一部分函数线性变系数模型,并基于样条估计方法得到了模型中未知系数函数的估计,同时在适当的条件下给出了系数函数估计及模型均方预测误差的收敛速度。通过数值模拟说明本文所提估计方法的有效性。最后基于该模型对Tecator数据进行了统计分析。     

运用非均匀三次B样条拟合我国国债利率期限结构

运用非均匀三次B样条作为拟合函数,以我国上海证券交易所附息国债的日价格为数据,拟合了我国国债的利率期限结构.实证结果显示,使用"等额现金量法"来确定样条节点向量,所拟合出的我国国债利率期限结构符合经济原理,且对债券价格的估计误差较小.     

Valuing risky debt: A new model combining structural information with the reduced-form approach

A new model of credit risk is proposed in which the intensity of default is described by an additional stochastic differential equation coupled with the process of the obligor’s asset value. Such an approach allows us to incorporate structural information as well as to capture the effect of external factors (e.g. macroeconomic factors) in a both parsimonious and economically consistent way. From the practical standpoint, the proposed model offers great flexibility and allows us to obtain credit spread curves of many different shapes, including double humped term structures. Furthermore, an approximate closed-form solution is derived, which is accurate, easy to implement, and allows for an efficient calibration to realized credit spreads. Numerical experiments are presented showing that the novel approach provides a very satisfactory fitting to market data and outperforms the model developed by Madan and Unal (2000).     

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??Inspired by intuitive meanings of truncated power basis's coefficients, the local penalization based on range's linear decreasing function is given in penalized spline regression model. This method gives less penalization to fitting curve where data is with more volatility, which makes fitted curve controls tradeoff between goodness-of-fit and smoothness better. Simulations show that regression models with local penalized spline obtain lower information rules' scores than global penalized spline when the data is with heteroskedasticity.     

基于径向基的自适应惩罚样条回归模型

传统惩罚样条回归模型中惩罚项的设置未考虑数据的空间异质性,因而对复杂数据的拟合缺乏自适应性.文章通过对径向基函数的几何意义分析,以节点两侧相邻区域内数据点的纵向极差为基础,构造局部惩罚权重向量并加入到约束回归模型的惩罚项中,构造了基于径向基的自适应惩罚样条回归模型.新模型在观测数据波动较大的区域,给予拟合曲线较小的惩罚,而在观测数据波动较小的区域,给予拟合曲线较大的惩罚,从而使拟合曲线能自适应地反映观测数据的局部变化特征.模拟和应用结果显示新模型的拟合效果显著优于传统的惩罚样条回归模型.     

A reduced-form model with default intensities containing contagion and regime-switching Vasicek processes

The contagion credit risk model is used to describe the contagion effect among different financial institutions. Under such a model, the default intensities are driven not only by the common risk factors, but also by the defaults of other considered firms. In this paper, we consider a two-dimensional credit risk model with contagion and regime-switching. We assume that the default intensity of one firm will jump when the other firm defaults and that the intensity is controlled by a Vasicek model with the coefficients allowed to switch in different regimes before the default of other firm. By changing measure, we derive the marginal distributions and the joint distribution for default times. We obtain some closed form results for pricing the fair spreads of the first and the second to default credit default swaps (CDSs). Numerical results are presented to show the impacts of the model parameters on the fair spreads.     

Modelling Specific Interest Rate Risk with Estimation of Missing Data

For the treatment of specific interest rate risk, a risk model is suggested, quantifying and combining both market and credit risk components consistently. The market risk model is based on credit spreads derived from traded bond prices. Though traded bond prices reveal a maximum amount of issuer specific information, illiquidity problems do not allow for classical parameter estimation in this context. To overcome this difficulty an efficient multiple imputation method is proposed that also quantifies the amount of risk associated with missing data. The credit risk component is based on event risk caused by correlated rating migrations of individual bonds using a Copula function approach.     

Determining the term structure of interest rates

The term structure of interest rates described by the zero-coupon yield curve is considered in developed countries as the main indicator of the financial market condition, one of the most important macroeconomic parameters, and a reference standard for security pricing in other sectors of the fixed-income market financial instruments. In this article, a new numerical method for constructing the term structure of interest rates from the quotes of a group of bonds of the same credit quality and liquidity is proposed.     

跳-扩散过程下具有目标杠杆比率的违约风险模型

本文在研究公司债务违约风险时,假设公司价值的动态变化服从跳-扩散过程;假设公司可以根据公司价值的变化调整其债务水平,因而存在公司的目标杠杆比率,违约边界定义为公司历史价值的对数加权平均;当公司价值下降到违约边界时发生债务违约.数值模拟表明公司债务的信用利差对公司的目标杠杆比率和跳过程的强度具有高度的敏感性.本文的模型解决了在长期和短期信用利差预测时结构化模型和约化模型存在的缺陷.     

Approximating term structure of interest rates using cubic L1 splines

Classical spline fitting methods for estimating the term structure of interest rates have been criticized for generating highly fluctuating fitting curves for bond price and discount function. In addition, the performance of these methods usually relies heavily on parameter tuning involving human judgement. To overcome these drawbacks, a recently developed cubic L₁ spline model is proposed for term structure analysis. Cubic L₁ splines preserve the shape of the data, exhibit no extraneous oscillation and have small fitting errors. Cubic L₁ splines are tested using a set of real financial data and compared with the widely used B-splines.     

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.     

利率期限结构与宏观经济变量的相互关系研究

本文研究了利率期限结构与宏观经济变量之间的相互关系。运用利率期限结构与宏观经济变量的无套利模型,对向量自回归模型进行了扩展,将其引入到状态空间模型框架中,基于卡尔曼滤波并结合EM算法对模型参数进行了有效估计,结合实际数据对利率期限结构与宏观经济变量的相互影响关系进行了实证研究。结果表明:利率期限结构与宏观经济变量的双向影响关系显著;宏观经济变量对利率期限结构具有一定的解释力;研究利率期限结构时,宏观经济变量的影响作用不能忽略。