In this dissertation we survey a variety of methods for constructing zero-coupon yield curves. We show that, when accuracy is of the utmost importance, the bootstrap described by Hagan and West (2006), Smit (2000), and Daeves and Parlar (2000) provides the ideal framework. This bootstrap requires the use of an interpolation algorithm, and a large portion of this dissertation will thus be devoted to the task of establishing an ideal method for interpolating yield curve data. Only two of the interpolation methods considered in this dissertation are seen to perform promisingly: the monotone convex method developed by Hagan and West (2006), and the monotone preserving r(t)t method developed in this dissertation. We show that the monotone preserving r(t)t method performs slightly better than the monotone convex method, in terms of the continuity of the forward curve, and in terms of the stability of the interpolation function. When economic appeal is of the utmost importance, we find parametric models to be more suitable than bootstrapping. However, we show that bootstrapping can be used to obtain a hypothetical set of zero-coupon bond prices, which can be used to calibrate parametric models. We compare the performance of the Nelson and Siegel (1987) and Svensson (1992) models, when applied to a historic set of South African swap curves, and show that the Svensson (1992) model performs better than the Nelson and Siegel (1987) model on a consistent basis. Copyright / Dissertation (MSc)--University of Pretoria, 2012. / Mathematics and Applied Mathematics / unrestricted

This thesis presents three essays on global yield curve factors and international linkages across yield curves. The essays represent a contribution to our understanding of the effect of globalization on yields, addressing three topics: modeling global and local yield curve factors, modeling global and local yield curve factors in excess bond returns and a joint model of global macroeconomic and yield curve factors. The first essay proposes and develops an empirical model of global and local yield curve factors based on three factors proposed by Nelson and Siegel (1987) dynamized and reinterpreted by Diebold and Li (2006) as level, slope and curvature. The results support the existence of a global yield curve composed of global factors which together with local factors describe the yield curve of the USA, Germany and the UK. Specifically, the global factors explain on average 55% of the variance of yields, and impulse response functions indicate that shocks to global factors are larger and last longer than shocks to local factors. In the second essay, we examine the predictability content of the global and local yield curve factor model to predict excess bond returns one year ahead. We use a rolling window of fifteen years to compare in-sample predictability of our model and two benchmark models: the model proposed by Cochrane and Piazzesi (2005) and the global and local factor model proposed by Dahlquist and Hasseltoft (2011). The results indicate that the global and local yield curve factors from our model predict excess bond returns with an adjusted R² up to 59%. We also find that global factors explain up to 58% of the forecast error variance when predicting excess bond returns. Moreover, our model outperforms both competing models considering the USA, Germany and the UK.The third essay proposes and estimates a joint model of global macroeconomic and yield curve factors, which shows the interaction between global yield curve factors and global macroeconomic factors. Our findings show that the influence of macroeconomic factors on yield curve factors is stronger than the influence of yield curve factors on macroeconomic factors.

In practice, yield curves, i.e. plots of relation between yields and times to maturity for a group of comparable securities, are an important tool for assets and liabilities pricing as well as for financial decision making. The theoretical risk-free yield curve represents the term structure of interest rates that are used e.g. in insurance industry for pricing the liabilities, for which reserves are created, or also as a benchmark for pricing other assets in the market. When constructing the yield curve, it is not possible to observe yields of a group of assets for all maturities. That is why we use various mathematical methods which enable us to construct the yield curve also for unobserved maturities. In this thesis, some of these methods are introduced. The Svensson's method is one of the most important and frequently used ones. We use this method to derive the coupon curve from Czech government bonds aiming to construct the risk-free zero coupon yield curve. Later on, we use different weights for particular bonds trying to improve pricing of all the bonds based on the derived curve. Then, we also look for the curve that minimizes the mean squared error of estimated (compared to observed) prices. Because problems with liquidity can appear especially for long maturities, we apply all of the procedures to a...

This thesis uses Spline-based model, which was developed by McCulloch, and parsimonious model, which was developed by Nelson-Siegel, to estimate the yield curves of zero-coupon bonds in Turkey. In this thesis, we construct the data by using Turkish secondary government zero-coupon bond data, which contain the data from January 2005 to June 2005. After that, relative performances of models are compared using in-sample goodness of fit. As a result, we see that performance of McCulloch model in fitting yield is better than that of Nelson-Siegel model.

The aim of thesis is to analyze the duration and its application in portfolio management. The work is divided into three logical parts. The intoductory part deal with issues of yield curves and in the following chapters we will build on this knowledge. In the mainstay of thesis we concentrate primarily on duration and its various modifications. The last section is devoted to portfolio management with emphasis on the bond portfolio. All theoretical knowledge is then applied to practical examples, which should lead to a better understanding of the topic.

This thesis represents an in-depth empirical study of the dependence structures within the term structure of interest rates. Firstly, a comprehensive overview of term structure modelling literature and methods is provided together with a summary of theoretical notions regarding the use of high-frequency data and spectral analysis. Contrary to most studies, the frequency-domain approach is employed, with a special focus on dependency across various quantiles of the joint distribution of the term structure. The main results are obtained using the quantile cross-spectral analysis, a new robust and non-parametric method allowing to uncover dependence structures in quantiles of the joint distribution of multivariate time series. The results are estimated using a dataset consisting of 15 years worth of high-frequency tick-by-tick time series of US Treasury futures. Complex dependence structures are revealed showing signs of both cyclicity and dependence in various parts of the joint distribution of the term structure in the frequency domain. JEL Classification C49, C55, C58, E43, G12, G13 Keywords term structure of interest rates, yield curves, high-frequency analysis, spectral analysis, inter- est rate futures Author's e-mail adam.nedved@fsv.cuni.cz Supervisor's e-mail barunik@fsv.cuni.cz

The aim of this thesis is to model the dynamics of international term structure of interest rates taking into consideration several dependence channels.Thanks to a new international Treasury yield curve database, we observe that the explained variability decision criterion, suggested by the literature, is not able to select the best combination of factors characterizing the joint dynamics of yield curves. We propose a new methodology based on the maximisation of the likelihood function of a Gaussian state-space model with common and local factors. The associated identification problem is solved in an innovative way. By estimating several sets of countries, we select two global (and three local) factors which are also useful to forecast macroeconomic variables in each considered economy.In addition, our method allows us to detect hidden factors in the international bond returns. They are not visible through a classical principal component analysis of expected bond returns but they are helpful to forecast inflation and industrial production. Keywords: International treasury yield curves, common and local factors, state-space models, EM algorithm, International bond risk premia, principal components.

With the substantial size of the interest rate markets, the importance of accurate pricing, risk measurement and performance attribution can not be understated. However, the models used on the markets often have underlying issues with capturing the market's fundamental behavior. With this thesis, we aim to improve the pricing, risk measurement, and performance attribution of interest rate swap portfolios. The paper is divided into six main parts, by subject, to aid in achieving these goals. To begin with, we validate all cash flows with SEB to increase the validity of the results. Next, we implement an optimization-based model developed by Jörgen Blomvall to estimate multiple yield curves.  By considering innovations of the daily in-sample curves, risk factors are computed with principal component analysis. These risk factors are then used to simulate one-day and ten-day ahead scenarios for the multiple yield curves using a Monte Carlo method. Given these simulated scenarios, risk measures are then computed. When backtested, these risk measurements give an indication on the overall accuracy of the methodology, including the estimated curves, the derived risk factors, and the simulation methodology. Along with the simulation, on each out-of-sample day, monetary performance attribution for the portfolios is also performed. The performance attribution indicates what drives the value change in the portfolio. This can be used in order to evaluate the estimated yield curves and derived risk factors. The risk measurement and performance attribution is done for three different portfolios of interest rate swaps on the EUR, USD, and SEK markets. However, the risk factors are only estimated for EUR data and used for all portfolios.  The main difference to previous work in this area is that, for all implementations, a multiple yield curve environment is studied. Different PCA algorithms are evaluated to increase the precision and speed of the risk factor calculation. Mean reverting risk factors are developed in the simulation framework, along with a Latin hypercube sampling method accounting for dependence in the random variables to reduce variance. We also study the EUR and SEK markets, while the focus in previous literature is on the USD market. Lastly, we calculate and backtest the risk measures value-at-risk and expected shortfall for one-day and ten-day horizons. Four different PCA methods are implemented, a bidiagonal divide and conquer SVD algorithm, a randomized SVD method, an Arnoldi method, and an optimization-based PCA algorithm. We opt to use the first one due to high accuracy and the ability to calculate all eigenpairs. However, we recommend to use the Arnoldi method in future implementations and to further study the optimization-based method. The Latin hypercube sampling with dependence method is able to produce random variables with the same correlation as the input variables. In the simulation, we are able to produce results that pass all backtests for the risk measures considering the USD portfolio. For the EUR and SEK portfolios, it is shown that the risk measures are too conservative. The results of the mean reversion method indicate that it produces slightly less conservative estimates for the ten-day horizon. In the performance attribution, we show that we are able to produce results with small error terms, therefore indicating accurately estimated term structures, risk factors, and pricing. We conclude that we are partly able to fulfill the stated purpose of this thesis due to having produced accurate pricing and satisfactory performance attribution results for all portfolios, and stable risk measures for the USD portfolio. However, it is not possible to state with certainty that improved risk measurements have been achieved for the EUR and SEK portfolios. Although, we present several alternative approaches to remedy this in future implementations.

Cette thèse concerne la modélisation de la dynamique des courbes des taux internationales avec prise en compte de plusieurs canaux de dépendance. A l’aide d’une nouvelle base de données des taux souverains internationaux, nous observons que le critère de la variabilité expliquée, proposé par la littérature, n’est pas capable de sélectionner une meilleure combinaison des facteurs décrivant la dynamique jointe des courbes des taux. Nous proposons une méthode nouvelle de section des facteurs fondée sur la maximisation de vraisemblance d’un modèle espace-état linéaire gaussien avec facteurs communs et locaux. Le problème d’identification associée est résolu d’une façon novatrice. En estimant différents combinaisons de pays, nous sélectionnons des deux facteurs globaux et trois locaux ayant un pouvoir prédictif des variables macro-économiques (activité économique et taux d’inflation) dans chaque économie considérée. Notre méthode nous permet aussi de détecter des facteurs cachés dans les rendements obligataires. Ils ne sont pas visibles à travers une analyse classique en composant principales des rendements obligataires et ils contribuent à la prévision du taux d’inflation et du taux de croissance de la production industrielle. / The aim of this thesis is to model the dynamics of international term structure of interest rates taking into consideration several dependence channels.Thanks to a new international Treasury yield curve database, we observe that the explained variability decision criterion, suggested by the literature, is not able to select the best combination of factors characterizing the joint dynamics of yield curves. We propose a new methodology based on the maximisation of the likelihood function of a Gaussian state-space model with common and local factors. The associated identification problem is solved in an innovative way. By estimating several sets of countries, we select two global (and three local) factors which are also useful to forecast macroeconomic variables in each considered economy.In addition, our method allows us to detect hidden factors in the international bond returns. They are not visible through a classical principal component analysis of expected bond returns but they are helpful to forecast inflation and industrial production. Keywords: International treasury yield curves, common and local factors, state-space models, EM algorithm, International bond risk premia, principal components.