Nonparametric Smoothing of Yield Curves

This paper proposes a new nonparametric approach to the problem of inferring term structure estimates using coupon bond prices. The nonparametric estimator is defined on the basis of a penalized least squares criterion. The solution is a natural cubic spline, and the paper presents an iterative procedure for solving the non-linear first-order conditions. Besides smoothness, there are no a priori restrictions on the yield curve, and the position of the knots and the optimal smoothness can be determined from data. For these reasons the smoothing procedure is said to be completely data driven. The paper also demonstrates that smoothing a simple transformation of the yield curve greatly improves the stability of longer-term yield curve estimates.     

Nonlinearities in the Brazilian Yield Curve

ABSTRACT

The article indicates the yield curve can be modeled using a continuous estimator as smooth transition regression, instead of traditional switch models, because bonds are traded continuously in the financial market. The results indicate that nonlinearity in the yield curve explains the pitfalls of monetary policy. The positive correlation between inflation and spread is consistent with a rise on uncertainty due to inflation risk or seems to indicate Brazilian Central Bank’s monetary policy credibility in the sample period. Therefore, if dependence on international capital exists, the Brazilian economic policy makers must monitor the movements in yield and analyze its feedback frequently in order to guide their plans and decisions.     

Fractionally Integrated Models With ARCH Errors: With an Application to the Swiss 1-Month Euromarket Interest Rate

We introduce ARFIMA-ARCH models, which simultaneously incorporate fractional differencing and conditional heteroskedasticity. We develop the likelihood function and we use it to construct the bias-corrected maximum (modified profile) likelihood estimator. Finite-sample properties of the estimation procedure are explored by Monte Carlo simulation. Backus and Zin (1993) have motivated the existence of fractional integration in interest rates by the persistence of the short rate and the variability of the long end of the yield curve. An empirical investigation of a daily one-month Swiss Euromarket interest rate finds a difference parameter of 0.72. This indicates non-stationary behavior. In contrast to first-order integrated models, the long-run cumulative response of shocks to the series is zero.     

Accurate Short-Term Yield Curve Forecasting using Functional Gradient Descent

We propose a multivariate nonparametric technique for generatingreliable short-term historical yield curve scenarios and confidenceintervals. The approach is based on a Functional Gradient Descent(FGD) estimation of the conditional mean vector and covariancematrix of a multivariate interest rate series. It is computationallyfeasible in large dimensions and it can account for nonlinearitiesin the dependence of interest rates at all available maturities.Based on FGD we apply filtered historical simulation to computereliable out-of-sample yield curve scenarios and confidenceintervals. We back-test our methodology on daily USD bond datafor forecasting horizons from 1 to 10 days. Based on severalstatistical performance measures we find significant evidenceof a higher predictive power of our method when compared toscenarios generating techniques based on (i) factor analysis,(ii) a multivariate CCC-GARCH model, or (iii) an exponentialsmoothing covariances estimator as in the RiskMetrics^TM approach.     

The Local Whittle Estimator of Long-Memory Stochastic Volatility

We propose a new semiparametric estimator of the degree of persistencein volatility for long memory stochastic volatility (LMSV) models.The estimator uses the periodogram of the log squared returnsin a local Whittle criterion which explicitly accounts for thenoise term in the LMSV model. Finite-sample and asymptotic standarderrors for the estimator are provided. An extensive simulationstudy reveals that the local Whittle estimator is much lessbiased and that the finite-sample standard errors yield moreaccurate confidence intervals than the widely-used GPH estimator.The estimator is also found to be robust against possible leverageeffects. In an empirical analysis of the daily Deutsche Mark/USDollar exchange rate, the new estimator indicates stronger persistencein volatility than the GPH estimator, provided that a largenumber of frequencies is used.     

Multi-Factor Cox-Ingersoll-Ross Models of the Term Structure: Estimates and Tests from a Kalman Filter Model

This paper presents a method for estimating multi-factor versions of the Cox-Ingersoll-Ross (1985b) model of the term structure of interest rates. The fixed parameters in one, two, and three factor models are estimated by applying an approximate maximum likelihood estimator in a state-space model using data for the U.S. treasury market. A nonlinear Kalman filter is used to estimate the unobservable factors. Multi-factor models are necessary to characterize the changing shape of the yield curve over time, and the statistical tests support the case for two and three factor models. A three factor model would be able to incorporate random variation in short term interest rates, long term rates, and interest rate volatility.     

The Effect of Monetary Unification on German Bond Markets

We develop a benchmark against which the effects of ECB monetary policy on the German bond market can be evaluated. We first estimate an affine term structure model for the pre‐EMU period linking the German yield curve with the Bundesbank monetary policy. The German monetary policy and its implied yield curve are then reprojected onto the EMU period. The reprojected yield curve differs significantly from the observed one. Short‐term interest rates during the EMU period are significantly lower than they would have been in case the Bundesbank were still in charge of monetary policy. Furthermore, yield spreads increased substantially during the EMU period.     

Estimation of Crop Yields and Insurance Premiums Using a Shrinkage Estimator

We explore the estimation of crop yields and insurance premiums using a hierarchical Bayes small area estimator. The estimator is evaluated for Area Yield Production (AYP) policy using quasi-simulated corn yields in the United States. Its performance in producing reliable mean county yield and premium estimates is compared to that of a naive estimator. We also investigate the impact of these efficiency improvements on the residual losses between a farm-level policy and AYP. The proposed estimator is found to be substantially more efficient and less biased than the naive estimator.     

美国房地产周期与经济衰退的可预测性研究

本文对房地产周期与收益率曲线反转对经济衰退的预测两个变量的联合预测进行了理论探讨和实证检验。实证结果表明,房地产周期和收益率曲线反转的联合预测力远大于单变量预测力。将本文实证结果应用于2006年以来经济数据的分析表明,从预测角度看美国经济将在2007-2008年间进入衰退。