Is long memory necessary? An empirical investigation of nonnegative interest rate processes

This paper analyzes a class of nonnegative processes for the short-term interest rate. The dynamics of interest rates and yields are driven by the dynamics of the conditional volatility of the pricing kernel. We study Markovian interest rate processes as well as more general non-Markovian processes that display “short” and “long” memory. These processes also display heteroskedasticity patterns that are more general than those of existing models. We find that deviations from the Markovian structure significantly improve the empirical performance of the model. Certain aspects of the long memory effect can be captured with a (less parsimonious) short memory parameterization, but a simulation experiment suggests that the implied term structures corresponding to the estimated long- and short-memory specifications are very different. We also find that the choice of proxy for the short rate affects the estimates of heteroskedasticity patterns.     

Estimating and Testing Exponential-Affine Term Structure Models by Kalman Filter

This paper proposes a unified state-space formulation for parameter estimation of exponential-affine term structure models. The proposed method uses an approximate linear Kalman filter which only requires specifying the conditional mean and variance of the system in an approximate sense. The method allows for measurement errors in the observed yields to maturity, and can simultaneously deal with many yields on bonds with different maturities. An empirical analysis of two special cases of this general class of model is carried out: the Gaussian case (Vasicek 1977) and the non-Gaussian case (Cox Ingersoll and Ross 1985 and Chen and Scott 1992). Our test results indicate a strong rejection of these two cases. A Monte Carlo study indicates that the procedure is reliable for moderate sample sizes.     

Estimating the structural credit risk model when equity prices are contaminated by trading noises

The transformed-data maximum likelihood estimation (MLE) method for structural credit risk models developed by Duan [Duan, J.-C., 1994. Maximum likelihood estimation using price data of the derivative contract. Mathematical Finance 4, 155–167] is extended to account for the fact that observed equity prices may have been contaminated by trading noises. With the presence of trading noises, the likelihood function based on the observed equity prices can only be evaluated via some nonlinear filtering scheme. We devise a particle filtering algorithm that is practical for conducting the MLE estimation of the structural credit risk model of Merton [Merton, R.C., 1974. On the pricing of corporate debt: The risk structure of interest rates. Journal of Finance 29, 449–470]. We implement the method on the Dow Jones 30 firms and on 100 randomly selected firms, and find that ignoring trading noises can lead to significantly over-estimating the firm’s asset volatility. The estimated magnitude of trading noise is in line with the direction that a firm’s liquidity will predict based on three common liquidity proxies. A simulation study is then conducted to ascertain the performance of the estimation method.     

APPROXIMATING GARCH-JUMP MODELS, JUMP-DIFFUSION PROCESSES, AND OPTION PRICING

This paper considers the pricing of options when there are jumps in the pricing kernel and correlated jumps in asset prices and volatilities. We extend theory developed by Nelson (1990) and Duan (1997) by considering the limiting models for our approximating GARCH Jump process. Limiting cases of our processes consist of models where both asset price and local volatility follow jump diffusion processes with correlated jump sizes. Convergence of a few GARCH models to their continuous time limits is evaluated and the benefits of the models explored.     

THE GARCH OPTION PRICING MODEL

This article develops an option pricing model and its corresponding delta formula in the context of the generalized autoregressive conditional heteroskedastic (GARCH) asset return process. the development utilizes the locally risk-neutral valuation relationship (LRNVR). the LRNVR is shown to hold under certain combinations of preference and distribution assumptions. the GARCH option pricing model is capable of reflecting the changes in the conditional volatility of the underlying asset in a parsimonious manner. Numerical analyses suggest that the GARCH model may be able to explain some well-documented systematic biases associated with the Black-Scholes model.     

MAXIMUM LIKELIHOOD ESTIMATION USING PRICE DATA OF THE DERIVATIVE CONTRACT

This article develops a general methodology that uses the observed prices of a derivative contract to compute maximum likelihood parameter estimates for an unobserved asset value process. the use of this estimation methodology is demonstrated in two applications: Vasicek's term structure model and deposit insurance pricing. This methodology can also be useful in the empirical analysis of complex financial contracts involving embedded options.     

投资时滞、信贷规则与经济动态 --转轨时期我国信贷政策规则及其效应的动态分析

文章在考虑投资时滞的情况下分析了两种不同的信贷规则对经济的动态影响，相位图的分析结果表明：在促进增长的目标下，信贷增长与消费波动同向，经济将趋于收敛；在消除通胀的目标下，信贷增长与消费波动反向，经济将趋于发散。对我国的实证结果显示，我国的信贷变化与消费呈正相关关系且具有戈氏因果关系的特征，表明我国的信贷规则目标是以促进增长为主。同时，信贷相对于投资不具有超外生性的结果表明，随着我国信贷规则的变化，信贷对投资的影响需要重新进行评估。最后，从实现稳定增长的角度出发，货币政策应同时关注信贷与货币供应量，且信贷政策的目标主要应是促进经济增长。     

Volatility and maturity effects in the Nikkei index futures

Many financial data series are found to exhibit stochastic volatility. Some of these time series are constructed from contracts with time-varying maturities. In this paper, we focus on index futures, an important subclass of such time series. We propose a bivariate GARCH model with the maturity effect to describe the joint dynamics of the spot index and the futures-spot basis. The setup makes it possible to examine the Samuelson effect as well as to compare the hedge ratios under scenarios with and without the maturity effect. The Nikkei-225 index and its futures are used in our empirical analysis. Contrary to the Samuelson effect, we find that the volatility of the futures price decreases when the contract is closer to its maturity. We also apply our model to futures hedging, and find that both the optimal hedge ratio and the hedging effectiveness critically depend on both the maturity and GARCH effects. © 1999 John Wiley & Sons, Inc. Jrl Fut Mark 19: 895–909, 1999     

Multiperiod corporate default prediction—A forward intensity approach

A forward intensity model for the prediction of corporate defaults over different future periods is proposed. Maximum pseudo-likelihood analysis is then conducted on a large sample of the US industrial and financial firms spanning the period 1991–2011 on a monthly basis. Several commonly used factors and firm-specific attributes are shown to be useful for prediction at both short and long horizons. Our implementation also factors in momentum in some variables and documents their importance in default prediction. The model’s prediction is very accurate for shorter horizons. Its accuracy deteriorates somewhat when the horizon is increased to two or three years, but the performance still remains reasonable. The forward intensity model is also amenable to aggregation, which allows for an analysis of default behavior at the portfolio and/or economy level.