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This paper estimates and tests consumption-based pricing kernels used in common equilibrium interest rate term structure models. In contrast to previous papers that use return orthogonality conditions, estimation in this paper is accomplished using moment conditions from a consumption-based option pricing equation and market prices of interest rate options. Thismethodology is more sensitive to preference misspecification over states associated with large changes in consumption than previous techniques. In addition, this methodology provides a large set of natural moment conditions to use in estimation and testing compared to an arbitrary choiceof return orthogonality conditions (e.g. instruments selected) used in GMM estimation. Eurodollar futures option prices and an estimated joint model of quarterly aggregate consumption and three month Eurodollar rates suggest are used to estimate and test pricing kernels based on logarithmic, power, and exponential utility functions. Using the market prices ofinterest rate options, evidence is found which is consistent with the equity premium puzzle; very high levels of risk aversion are needed to justify the observed premium associated with an investment position positively correlated with aggregate consumption. In addition, evidence isfound which is consistent with the riskfree rate puzzle: at high levels of risk-aversion for power or exponential utility, negative rates of time preference are needed to fit the observed low risklessinterest rates. These results suggest that typical term structure models are misspecified in terms of assumed preferences. This may have deleterious effects on model estimates of the interest rate term structure estimates and interest rate option prices.
This study compares continuous-time stochastic interest rate and stochastic volatility models of interest rate derivatives, examining these models across several dimensions: different classes of models, factor structures, and pricing algorithms. We consider a broader universe of pricing models, using improved econometric and numerical methodologies. We establish several criteria for model quality that are motivated by financial theory as well as practice: realism of the assumed stochastic process for the term structure, consistency with no-arbitrage or financial market equilibrium, consistency with financial practice, parsimony, as well as computational efficiency. A model which scores well along these grounds will also exhibit superior pricing performance with regard to traded interest rate options. This helps resolve the controversies over the stochastic process for yield curve dynamics, the models that best manage and measure interest rate risk, and theories of the term structure that are supported by empirical results. We perform econometric experiments at three levels: the short rate, bond prices, as well as interest rate derivatives. We extend CKLS (1992) to a broader class of single factor spot rate models and international interest rates. We find that a single-factor general parametric model (1FGPM) of the term structure, with non-linearity in the drift function, better captures the time series dynamics of US 30 Day T-Bill rates. The 1FGPM not only forecasts interest rate changes out-of-sample better relative to other parametric models, but also relative to the non-parametric model of Jiang (1998). Finally, our results vary greatly across international markets. Building upon the work of Longstaff and Schwartz (1992), we perform a statistical analysis of the U.S. default-free term structure over the period 4:1964 to 10:1997. We utilize a constant correlation multivariate GARCH principal components analysis (CCM-PCA), and identify at least three factors associated with traditional measures of risk in the fixed income literature (level, slope, and curvature) that capture 98% of the variation in the default-free term structure. We perform tests of various term structure models on US Treasury bonds, comparing a two factor Cox-Ingersoll-Ross (2FCIR) model with a multi-layer perceptron neural network approach (MLP-ANN), in pricing and hedging discount bonds. We find that while the MLP-ANN can better fit bond prices in-sample, the 2F-CIR model is superior in hedging against unanticipated changes in the short rate and its volatility. Furthermore, we find the 2FCIR model to perform favorably in comparison to the CCM-PCA, MLP-ANN, as well as the 1FGPM in forecasting bond yield changes. Finally, we compare various interest rate bond option pricing models, in their ability to price interest rate derivatives and manage and interest rate risk. We compare three approaches to pricing interest rate derivatives: spot rate (e.g., CIR), forward-rate (i.e., HJM), and non-parametric models (e.g., multivariate kernel estimation.) This is extended to a broader factor structure. While the best model in terms of mean square error (MSE) is the non parametric (MNWK) model, the 3 factor jump diffusion (3FGJD) model performs best among parametric models. In hedging analysis, while these preferred models still outperform within each grouping, the non parametric model is no longer the best performing model, while the 2FCIR is the best model in hedging options in terms of MSE.
Proposes a non-parametric two-factor term-structure model that imposes no restrictions on the functional forms of the diffusion functions.
The increased volatility of interest rates during recent years and the corresponding introduction of a variety of interest rate derivative securities like bond options, futures and embedded options in mortgages, underlines the need for a comprehensive financial theory to determine values of fixed income instruments and derivative securities consistently. This book provides: * a detailed overview and classification of the different approaches to value interest rate dependent securities * a comparison of the numerical approaches to value complex securities * an empirical examination for the Dutch Fixed Income Market of some well-known interest rate models which demonstrates recent improvements to describe interest rate movements in relation to contingent claim valuation.