基于市场债券报价的利率模型参数估计与比较

分别基于短期利率期限结构延拓Vasicek与CIR模型,提出了一种有效的正则化参数估计计算方法.方法将通过当前交易市场中不同期限的零息债券市场报价来实现对于时间函数的参数估计.数值试验表明了参数估计方法的稳定性.     

Embedding the Vasicek model into the Cox–Ingersoll–Ross model

The Cox–Ingersoll–Ross (CIR) model and the Vasicek model are two well‐known single factor models of the interest spot rate. In this paper, we construct a mapping by means of which the price of a zero‐coupon bond in the CIR model may be obtained from a corresponding price in the Vasicek model. We use symmetry analysis to construct this mapping and verify it by transforming three arbitrary solutions of the pricing equation in the Vasicek model into solutions of the corresponding equation in the CIR model. Copyright © 2010 John Wiley & Sons, Ltd.     

A square root interest rate model fitting discrete initial term structure data

This paper presents one-factor and multifactor versions of a term structure model in which the factor dynamics are given by Cox/Ingersoll/Ross (CIR) type ‘square root’ diffusions with piece wise constant parameters. The model is fitted to initial term structures given by a finite number of data points, interpolating endogenously. Closed form and near closed form solutions for a large class of fixed income derivatives are derived in terms of a compound noncentral chi-square distribution. An implementation of the model is discussed where the initial term structure of volatility is fitted via cap prices.     

Semiparametric regression analysis for clustered doubly-censored data

This paper considers clustered doubly-censored data that occur when there exist several correlated survival times of interest and only doubly censored data are available for each survival time. In this situation, one approach is to model the marginal distribution of failure times using semiparametric linear transformation models while leaving the dependence structure completely arbitrary. We demonstrate that the approach of Cai et al. (Biometrika 87:867–878, 2000) can be extended to clustered doubly censored data. We propose two estimators by using two different estimated censoring weights. A simulation study is conducted to investigate the proposed estimators.     

Using Utility Functions to Model Risky Bonds

This paper prices defaultable bonds by incorporating inherent risks with the use of utility functions. By allowing risk preferences into the valuation of bonds, nonlinearity is introduced in their pricing. The utility‐function approach affords the advantage of yielding exact solutions to the risky bond pricing equation when familiar stochastic models are used for interest rates. This can be achieved even when the default probability parameter is itself a stochastic variable. Valuations are found for the power‐law and log utility functions under the interest‐rate dynamics of the extended Vasicek and CIR models.     

The term structure of interest rates in the economic and monetary union

The main purpose of this article is to present a new numerical procedure that can be used to implement a variety of different interest rate models. The new approach allows to construct no-arbitrage models for the term structure, where the stochastic process driving the rates is infinitely divisible, as in the cases of pure-diffusion and jump-diffusion mean reverting models. The new method determines a unique fully specified hexanomial tree, consistent with risk neutral probabilities. A simple forward recursive procedure solves for the entire tree. The proposed lattice model, which generalized the Hull and White [37] single-factor model, is relatively simple, computational efficient and can fit any initial term structure observed in the market. Numerical experiments demonstrate how the jump-diffusion mean reverting model is particularly suited to describe the European money market rates behavior. Interest rates controlled by the monetary authorities behave as if they are jump processes and the term structure, at short maturity, is contingent upon the levels of these official rates.     

PRICING EUROPEAN OPTION IN A DOUBLE EXPONENTIAL JUMP-DIFFUSION MODEL WITH TWO MARKET STRUCTURE RISKS AND ITS COMPARISONS

Using Fourier inversion transform, P.D.E. and Feynman-Kac formula, the closedform solution for price on European call option is given in a double exponential jump-diffusion model with two different market structure risks that there exist CIR stochastic volatility of stock return and Vasicek or CIR stochastic interest rate in the market. In the end, the result of the model in the paper is compared with those in other models, including BS model with numerical experiment. These results show that the double exponential jump-diffusion model with CIR-market structure risks is suitable for modelling the real-market changes and very useful.     

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。     

Markov interest rate models

A general procedure for creating Markovian interest rate models is presented. The models created by this procedure automatically fit within the HJM framework and fit the initial term structure exactly. Therefore they are arbitrage free. Because the models created by this procedure have only one state variable per factor, twoand even three-factor models can be computed efficiently, without resorting to Monte Carlo techniques. This computational efficiency makes calibration of the new models to market prices straightforward. Extended Hull- White, extended CIR, Black-Karasinski, Jamshidian's Brownian path independent models, and Flesaker and Hughston's rational log normal models are one-state variable models which fit naturally within this theoretical framework. The ‘separable’ n-factor models of Cheyette and Li, Ritchken, and Sankarasubramanian - which require n(n + 3)/2 state variables - are degenerate members of the new class of models with n(n + 3)/2 factors. The procedure is used to create a new class of one-factor models, the ‘β-η models.’ These models can match the implied volatility smiles of swaptions and caplets, and thus enable one to eliminate smile error. The β-η models are also exactly solvable in that their transition densities can be written explicitly. For these models accurate - but not exact - formulas are presented for caplet and swaption prices, and it is indicated how these closed form expressions can be used to efficiently calibrate the models to market prices.     

Forecasting mortality rate improvements with a high-dimensional VAR

Forecasting mortality rates is a problem which involves the analysis of high-dimensional time series. Most of usual mortality models propose to decompose the mortality rates into several latent factors to reduce this complexity. These approaches, in particular those using cohort factors, have a good fit, but they are less reliable for forecasting purposes. One of the major challenges is to determine the spatial–temporal dependence structure between mortality rates given a relatively moderate sample size. This paper proposes a large vector autoregressive (VAR) model fitted on the differences in the log-mortality rates, ensuring the existence of long-run relationships between mortality rate improvements. Our contribution is threefold. First, sparsity, when fitting the model, is ensured by using high-dimensional variable selection techniques without imposing arbitrary constraints on the dependence structure. The main interest is that the structure of the model is directly driven by the data, in contrast to the main factor-based mortality forecasting models. Hence, this approach is more versatile and would provide good forecasting performance for any considered population. Additionally, our estimation allows a one-step procedure, as we do not need to estimate hyper-parameters. The variance–covariance matrix of residuals is then estimated through a parametric form. Secondly, our approach can be used to detect nonintuitive age dependence in the data, beyond the cohort and the period effects which are implicitly captured by our model. Third, our approach can be extended to model the several populations in long run perspectives, without raising issue in the estimation process. Finally, in an out-of-sample forecasting study for mortality rates, we obtain rather good performances and more relevant forecasts compared to classical mortality models using the French, US and UK data. We also show that our results enlighten the so-called cohort and period effects for these populations.     

随机期度与利率反向变动关系的初步研究

本文介绍了随机利率下相应的期度—随机期度的定义及其性质.对常见的随机利率模型Vasciek 模型和CIR模型,证明了随机期度与随机利率之间存在着反向的变动关系,从而辅证了随机期度定义的合理性.     

Solutions of two-factor models with variable interest rates

The focus of this work is on numerical solutions to two-factor option pricing partial differential equations with variable interest rates. Two interest rate models, the Vasicek model and the Cox–Ingersoll–Ross model (CIR), are considered. Emphasis is placed on the definition and implementation of boundary conditions for different portfolio models, and on appropriate truncation of the computational domain. An exact solution to the Vasicek model and an exact solution for the price of bonds convertible to stock at expiration under a stochastic interest rate are derived. The exact solutions are used to evaluate the accuracy of the numerical simulation schemes. For the numerical simulations the pricing solution is analyzed as the market completeness decreases from the ideal complete level to one with higher volatility of the interest rate and a slower mean-reverting environment. Simulations indicate that the CIR model yields more reasonable results than the Vasicek model in a less complete market.     

分段时变参数CIR模型及其实证研究

经济环境总体是变化的,但在一定阶段会保持局部稳定.鉴于此,提出了分段时变参数CIR模型的构想,并用它来建模短期利率与汇率.给出了CIR模型设定检验的广义残差拟合优度检验法,用之来检验模型的时变性.用数值模拟和实证分析来验证分段时变参数CIR模型进行利率、汇率建模的可行性和合理性.数值模拟表明,两组符合CIR(Cox-Ingersoll-Ross)模型的数据合在一起不一定还符合CIR模型.通过对短期国库券利率和加拿大元与美元汇率数据的实证分析,发现用分段时变参数CIR模型来描述短期利(汇)率比一般的固定常数CIR模型更加合理.     

Valuation of Two-Factor Interest Rate Contingent Claims Using Green's Theorem

Abstract

Over the years a number of two-factor interest rate models have been proposed that have formed the basis for the valuation of interest rate contingent claims. This valuation equation often takes the form of a partial differential equation that is solved using the finite difference approach. In the case of two-factor models this has resulted in solving two second-order partial derivatives leading to boundary errors, as well as numerous first-order derivatives. In this article we demonstrate that using Green's theorem, second-order derivatives can be reduced to first-order derivatives that can be easily discretized; consequently, two-factor partial differential equations are easier to discretize than one-factor partial differential equations. We illustrate our approach by applying it to value contingent claims based on the two-factor CIR model. We provide numerical examples that illustrate that our approach shows excellent agreement with analytical prices and the popular Crank–Nicolson method.     

Graphical tools for model-based mixture discriminant analysis

The paper introduces a methodology for visualizing on a dimension reduced subspace the classification structure and the geometric characteristics induced by an estimated Gaussian mixture model for discriminant analysis. In particular, we consider the case of mixture of mixture models with varying parametrization which allow for parsimonious models. The approach is an extension of an existing work on reducing dimensionality for model-based clustering based on Gaussian mixtures. Information on the dimension reduction subspace is provided by the variation on class locations and, depending on the estimated mixture model, on the variation on class dispersions. Projections along the estimated directions provide summary plots which help to visualize the structure of the classes and their characteristics. A suitable modification of the method allows us to recover the most discriminant directions, i.e., those that show maximal separation among classes. The approach is illustrated using simulated and real data.     

A comparative evaluation of alternative models of the term structure of interest rates

In the paper alternative models of the term structure of interest rates are classified in two different approaches: the no-arbitrage and the general equilibrium approach. It is maintained that the general equilibrium approach is superior on a theoretical ground for two main reasons: first, relevant variables, such as the spot interest rate and the interest risk-premium, are endogenous; second, the relationship between the real and the financial side of the economy becomes a clear and important element in the understanding of the term structure. As regards the applications, however, the advantages of the general equilibrium over the no-arbitrage approach are not so clear: the major role in the empiricil performance of alternative models is played by their ability to capture volatility. At the current state of the literature, there is no model that outperforms others, in particular on the empirical side.     

On the simulation of portfolios of interest rate and credit risk sensitive securities

We discuss extensions of reduced-form and structural models for pricing credit risky securities to portfolio simulation and valuation. Stochasticity in interest rates and credit spreads is captured via reduced-form models and is incorporated with a default and migration model based on the structural credit risk modelling approach. Calculated prices are consistent with observed prices and the term structure of default-free and defaultable interest rates. Three applications are discussed: (i) study of the inter-temporal price sensitivity of credit bonds and the sensitivity of future portfolio valuation with respect to changes in interest rates, default probabilities, recovery rates and rating migration, (ii) study of the structure of credit risk by investigating the impact of disparate risk factors on portfolio risk, and (iii) tracking of corporate bond indices via simulation and optimisation models. In particular, we study the effect of uncertainty in credit spreads and interest rates on the overall risk of a credit portfolio, a topic that has been recently discussed by Kiesel et al. [The structure of credit risk: spread volatility and ratings transitions. Technical report, Bank of England, ISSN 1268-5562, 2001], but has been otherwise mostly neglected. We find that spread risk and interest rate risk are important factors that do not diversify away in a large portfolio context, especially when high-quality instruments are considered.     

CIR框架下的投资组合效用微分博弈

建立了Cox-Ingersoll—Ross随机利率下的关于两个投资者的投资组合效用微分博弈模型．市场利率具有CIR动力,博弈双方存在唯一的损益函数,损益函数取决于投资者的投资组合财富．一方选择动态投资组合策略以最大化损益函数,而另一方则最小化损益函数．运用随机控制理论,在一般的效用函数下得到了基于效用的博弈双方的最优策略．特别考虑了常数相对风险厌恶情形,获得了显示的最优投资组合策略和博弈值．最后给出了数值例子和仿真结果以说明本文的结论．     

A Feynman-Kac type formula for a fixed delay CIR model

Stochastic delay differential equations (SDDE’s) have been used for financial modeling. In this article, we study a SDDE obtained by the equation of a CIR process, with an additional fixed delay term in drift; in particular, we prove that there exists a unique strong solution (positive and integrable) which we call fixed delay CIR process. Moreover, for the fixed delay CIR process, we derive a Feynman-Kac type formula, leading to a generalized exponential-affine formula, which is used to determine a bond pricing formula when the interest rate follows the delay’s equation. It turns out that, for each maturity time T, the instantaneous forward rate is an affine function (with time dependent coefficients) of the rate process and of an auxiliary process (also depending on T). The coefficients satisfy a system of deterministic differential equations.     

关于长期债券是长期投者无风险资产的研究

假设短期利率服从C IR模型,通过研究投资者如何选择长期债券和短期债券进行资产配置,发现保守的长期投资者在长期债券上投资的比例更大;投资者的投资期限越长,投资的长期债券越多;在进行债券投资时不存在市场时机的选择。对于长期投资者而言,可以为其提供长期稳定收益率的长期债券才是无风险的。