The changing behaviour of the term structure of post-war US

Using U.S. interest rate data covering the period 1950:1-1992:7, this paper tests the rational expectations model of the term structure of interest rates. We show evidence that the rational expectations model of the term structure is supported by the data during the seventies and a period lasting from the mid-eighties to the end of the sample. However, during the …fties, sixties and a period that covers most of the Volcker’s office term (from September 1979 to April 1986) the term structure model is rejected by the data. Moreover, wefind evidence of regime changes in the short-term rate process and the term structure of interest rates. These regime switches roughly coincide with changes in the Federal Reserve chairman. The switches in monetary policy taking place when the chairmanship of the Federal Reserve changes therefore seem to play an important role in characterizing the term structure of interest rates.

Testing for non-stationarity and cointegration allowing for the possibility of a structural break: an application to EuroSterling interest rates

In this paper we examine the order of integration of EuroSterling interest rates by employing techniques that can allow for a structural break under the null and/or alternative hypothesis of the unit-root tests. In light of these results, we investigate the cointegrating relationship implied by the single, linear expectations hypothesis of the term structure of interest rates employing two techniques, one of which allows for the possibility of a break in the mean of the cointegrating relationship. The aim of the paper is to investigate whether or not the interest rate series can be viewed as I(1) processes and furthermore, to consider whether there has been a structural break in the series. We also determine whether, if we allow for a break in the cointegration analysis, the results are consistent with those obtained when a break is not allowed for. The main results reported in this paper support the conjecture that the ‘short’ Euro-currency rates are characterised as I(1) series that exhibit a structural break on or near Black Wednesday, 16 September 1992, whereas the ‘long’ rates are I(1) series that do not support the presence of a structural break. The evidence from the cointegration analysis suggests that tests of the expectations hypothesis based on data sets that include the ERM crisis period, or a period that includes a structural break, might be problematic if the structural break is not explicitly taken into account in the testing framework.

A Semi-Parametric Factor Model for Interest Rates.

Understanding the dynamics of interest rates and the term structure has important implications for issues as diverse as real economic activity, monetary policy, pricing of interest rate derivative securities and public debt financing. Our paper follows a longstanding tradition of using factor models of interest rates but proposes a semi-parametric procedure to model interest rates.

Essays in macroeconomy and dynamic term-structure models

This thesis is composed of three articles with the subjects of macroeconomics and - nance. Each article corresponds to a chapter and is done in paper format. In the rst article, which was done with Axel Simonsen, we model and estimate a small open economy for the Canadian economy in a two country General Equilibrium (DSGE) framework. We show that it is important to account for the correlation between Domestic and Foreign shocks and for the Incomplete Pass-Through. In the second chapter-paper, which was done with Hedibert Freitas Lopes, we estimate a Regime-switching Macro-Finance model for the term-structure of interest rates to study the US post-World War II (WWII) joint behavior of macro-variables and the yield-curve. We show that our model tracks well the US NBER cycles, the addition of changes of regime are important to explain the Expectation Theory of the term structure, and macro-variables have increasing importance in recessions to explain the variability of the yield curve. We also present a novel sequential Monte-Carlo algorithm to learn about the parameters and the latent states of the Economy. In the third chapter, I present a Gaussian A ne Term Structure Model (ATSM) with latent jumps in order to address two questions: (1) what are the implications of incorporating jumps in an ATSM for Asian option pricing, in the particular case of the Brazilian DI Index (IDI) option, and (2) how jumps and options a ect the bond risk-premia dynamics. I show that jump risk-premia is negative in a scenario of decreasing interest rates (my sample period) and is important to explain the level of yields, and that gaussian models without jumps and with constant intensity jumps are good to price Asian options.

Affine processes, arbitrage-Free Term structures of legendre polynomials,and option pricing

Multivariate Affine term structure models have been increasingly used for pricing derivatives in fixed income markets. In these models, uncertainty of the term structure is driven by a state vector, while the short rate is an affine function of this vector. The model is characterized by a specific form for the stochastic differential equation (SDE) for the evolution of the state vector. This SDE presents restrictions on its drift term which rule out arbitrages in the market. In this paper we solve the following inverse problem: Suppose the term structure of interest rates is modeled by a linear combination of Legendre polynomials with random coefficients. Is there any SDE for these coefficients which rules out arbitrages? This problem is of particular empirical interest because the Legendre model is an example of factor model with clear interpretation for each factor, in which regards movements of the term structure. Moreover, the Affine structure of the Legendre model implies knowledge of its conditional characteristic function. From the econometric perspective, we propose arbitrage-free Legendre models to describe the evolution of the term structure. From the pricing perspective, we follow Duffie et al. (2000) in exploring Legendre conditional characteristic functions to obtain a computational tractable method to price fixed income derivatives. Closing the article, the empirical section presents precise evidence on the reward of implementing arbitrage-free parametric term structure models: The ability of obtaining a good approximation for the state vector by simply using cross sectional data.

Essays on the monetary aspects of the term structure of nominal interest rates

Interest rates are key economic variables to much of finance and macroeconomics, and an enormous amount of work is found in both fields about the topic. Curiously, in spite of their common interest, finance and macro research on the topic have seldom interacted, using different approaches to address its main issues with almost no intersection. Concerned with interest rate contingent claims, finance term structure models relate interest rates to lagged interest rates; concerned with economic relations and macro dynamics, macro models regress a few interest rates on a wide variety of economic variables. If models are true though simplified descriptions of reality, the relevant factors should be captured by both the set of bond yields and that of economic variables. Each approach should be able to address the other field concerns with equal emciency, since the economic variables are revealed by the bond yields and these by the economic variables.

Estimating the term structure of volatility and fixed income derivative pricing

Estimating the parameters of the instantaneous spot interest rate process is of crucial importance for pricing fixed income derivative securities. This paper presents an estimation for the parameters of the Gaussian interest rate model for pricing fixed income derivatives based on the term structure of volatility. We estimate the term structure of volatility for US treasury rates for the period 1983 - 1995, based on a history of yield curves. We estimate both conditional and first differences term structures of volatility and subsequently estimate the implied parameters of the Gaussian model with non-linear least squares estimation. Results for bond options illustrate the effects of differing parameters in pricing.

Long-term dynamics of death rates of emphysema, asthma, and pneumonia and improving air quality.

BACKGROUND: The respiratory tract is a major target of exposure to air pollutants, and respiratory diseases are associated with both short- and long-term exposures. We hypothesized that improved air quality in North Carolina was associated with reduced rates of death from respiratory diseases in local populations. MATERIALS AND METHODS: We analyzed the trends of emphysema, asthma, and pneumonia mortality and changes of the levels of ozone, sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and particulate matters (PM2.5 and PM10) using monthly data measurements from air-monitoring stations in North Carolina in 1993-2010. The log-linear model was used to evaluate associations between air-pollutant levels and age-adjusted death rates (per 100,000 of population) calculated for 5-year age-groups and for standard 2000 North Carolina population. The studied associations were adjusted by age group-specific smoking prevalence and seasonal fluctuations of disease-specific respiratory deaths. RESULTS: Decline in emphysema deaths was associated with decreasing levels of SO2 and CO in the air, decline in asthma deaths-with lower SO2, CO, and PM10 levels, and decline in pneumonia deaths-with lower levels of SO2. Sensitivity analyses were performed to study potential effects of the change from International Classification of Diseases (ICD)-9 to ICD-10 codes, the effects of air pollutants on mortality during summer and winter, the impact of approach when only the underlying causes of deaths were used, and when mortality and air-quality data were analyzed on the county level. In each case, the results of sensitivity analyses demonstrated stability. The importance of analysis of pneumonia as an underlying cause of death was also highlighted. CONCLUSION: Significant associations were observed between decreasing death rates of emphysema, asthma, and pneumonia and decreases in levels of ambient air pollutants in North Carolina.

Forecasting the Yield Curve of Government Bonds: A Comparative Study

For the past 20 years, researchers have applied the Kalman filter to the modeling and forecasting the term structure of interest rates. Despite its impressive performance in in-sample fitting yield curves, little research has focused on the out-of-sample forecast of yield curves using the Kalman filter. The goal of this thesis is to develop a unified dynamic model based on Diebold and Li (2006) and Nelson and Siegel’s (1987) three-factor model, and estimate this dynamic model using the Kalman filter. We compare both in-sample and out-of-sample performance of our dynamic methods with various other models in the literature. We find that our dynamic model dominates existing models in medium- and long-horizon yield curve predictions. However, the dynamic model should be used with caution when forecasting short maturity yields

International evidence on the predictability of returns to securitized real estate assets: econometric models versus neural networks

The performance of various statistical models and commonly used financial indicators for forecasting securitised real estate returns are examined for five European countries: the UK, Belgium, the Netherlands, France and Italy. Within a VAR framework, it is demonstrated that the gilt-equity yield ratio is in most cases a better predictor of securitized returns than the term structure or the dividend yield. In particular, investors should consider in their real estate return models the predictability of the gilt-equity yield ratio in Belgium, the Netherlands and France, and the term structure of interest rates in France. Predictions obtained from the VAR and univariate time-series models are compared with the predictions of an artificial neural network model. It is found that, whilst no single model is universally superior across all series, accuracy measures and horizons considered, the neural network model is generally able to offer the most accurate predictions for 1-month horizons. For quarterly and half-yearly forecasts, the random walk with a drift is the most successful for the UK, Belgian and Dutch returns and the neural network for French and Italian returns. Although this study underscores market context and forecast horizon as parameters relevant to the choice of the forecast model, it strongly indicates that analysts should exploit the potential of neural networks and assess more fully their forecast performance against more traditional models.

An empirical analysis of the Australian dollar swap spreads

This paper examines the relationship between the Australian dollar interest rate swap spread and the term structure of the interest rates, and also the determinants of interest rate swap spreads. For this purpose, we estimate the term structure of interest rates using the parsimonious fitting function of Nelson and Siegel [Journal of Business 60 (1987) 476] for the Australian government bonds and Australian interest rate swaps for certain maturities that are not available. We analyse the swap spread over the term structure of the government bonds and how changes in swap determinants affect the changes in swap spreads. The sample period covers the daily interval from 6 December 1996 to 31 December 1999.

Volatility dynamics in the term structure of Latin American sovereign international bonds

We examine the nature of volatility dynamics in the term structure of sovereign bonds issued in international markets by major Latin American countries. Focusing only on the U.S. dollar-denominated sovereign international bonds, this study shows the heterogeneous nature of volatility effects that affect the term structure of individual countries in Latin America. Considering the significance of the Argentine credit event in the region, we also account for any change in dynamics following the Argentine default in 2001 by subsampling the pre- and postdefault windows. We also find some evidence of liquidity-driven volatility interaction in the term structure.

Hedging options in a garch environment: testing the term structure of stochastic volatility models

This paper develops a methodology for testing the term structure of volatility forecasts derived from stochastic volatility models, and implements it to analyze models of S&P500 index volatility. U sing measurements of the ability of volatility models to hedge and value term structure dependent option positions, we fmd that hedging tests support the Black-Scholes delta and gamma hedges, but not the simple vega hedge when there is no model of the term structure of volatility. With various models, it is difficult to improve on a simple gamma hedge assuming constant volatility. Ofthe volatility models, the GARCH components estimate of term structure is preferred. Valuation tests indicate that all the models contain term structure information not incorporated in market prices.

Business cycles in emerging economies : the role of interest rates

This paper documents the empirical relation between the interest rates that emerging economies face in international capital markets and their business cycles. It shows that the patterns observed in the data can be interpreted as the equilibrium of a dynamic general equilibrium model of a small open economy, in which (i) firms have to pay for a fraction of the input bill before production takes place, and (ii) preferences generate a labor supply that is independent of the interest rate. In our sample, interest rates are strongly countercyclical, strongly positively correlated with net exports, and they lead the cycle. Output is very volatile and consumption is more volatile than output. The sample includes data for Argentina during 1983-2000 and for four other large emerging economies, Brazil, Mexico, Korea, and Philippines, during 1994-2000. The model is calibrated to Argentina’s economy for the period 1983-1999. When the model is fed with actual US interest rates and the actual default spreads of Argentine sovereign interest rates, interest rates alone can explain forty percent of output fluctuations. When simulated technology shocks are added to the model, it can account for the main empirical regularities of Argentina’s economy during the period. A 1% increase in country risk causes a contemporaneous fall in output of 0.5 ’subsequent recovery. An increase in US rates causes output to fall by the same on impact and by almost 2% two years after the shock. The asymetry in the effect of shocks to US rates and country risk is due to the fact that US interest rates are more persistent than country risk and that there is a significant spillover effect from US interest rates to country risk.