An important application of term structure models is to measure the difference between the evolutions of two yield curves starting from the same initial point. Such a geometric problem can be tackled by use of the notion of information geometry after the mapping of yield curves to density functions on a Hilbert space. We prove that a pair of yield curves with large initial Bhattacharyya spherical distance would diverge from each other with a significant probability. / Finally, we implement the proposed model with initial data in the US swap market for 15 Feb, 2007. To test our model improvements over the traditional models, we also run the simulation with the Hull-White model and compare these two no-arbitrage models in various major characteristics. It shows that the proposed model forms a bridge linking interest rates and discount bonds, namely, given the initial term structure density and the volatility structure, we are able to reconstruct the short rate process and the bond price process. Our term structure density model is thus a unification of traditional models each having its own advantage. / Following the initial study of Brody and Hughston on applying information geometry to interest rate modeling, we propose a novel term structure model and investigate its application in the US swap market. Different from the traditional term structure models that impose assumptions on either bonds or rates, the newly proposed model is characterized by the evolution of a density function which is obtained from the derivative of the discount function with respect to the time left till maturity. We prove that such a density function can be interpreted as interest return on the discount bond. / The introduction of the term structure density turns the problem of yield curve dynamics into a problem of the evolution of a density distribution. There are at least three steps to model the dynamics of the density function: calibrate the initial term structure density, specify the market risk premium, and choose a proper volatility structure. First, we introduce two initial calibration methods, one by maximizing the Tsallis entropy and the other by the notion of superstatistics. By use of either method, we deduce a power-law distribution for the initial term structure density function. The entropy index q in this function, which is a well-known physics quantity, now finds its financial interpretation as the measure of departure of the current term structure from flatness on a continuously compounded basis. Our empirical experiments in the US swap market fully demonstrate this observation. Next, given the calibrated initial density, we develop the term structure dynamics in the risk-neutral world and prove that the market risk premium is immaterial. To deduce a concise martingale representation for the bond pricing formula, we choose a density volatility that possesses zero mean. Finally, as an illustration of the importance of volatility structure, the HJM volatilities are redesigned for interest rate positivity under the framework of the current model. / Yang, Yiping. / Adviser: Kwong Chung Ping. / Source: Dissertation Abstracts International, Volume: 73-03, Section: B, page: . / Thesis (Ph.D.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (leaves 187-192). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.

M.Sc. (Mathematical Statistics) / Stochastic Differential Equations (SDE’s) are commonly found in most of the modern finance used today. In this dissertation we use SDE’s to model a random phenomenon known as the short-term interest rate where the explanatory power of a particular short-term interest rate model is largely dependent on the description of the SDE to the real data. The challenge we face is that in most cases the transition density functions of these models are unknown and therefore, we need to find reliable and accurate alternative estimation techniques. In this dissertation, we discuss estimating techniques for discretely sampled continuous diffusion processes that do not require the true transition density function to be known. Moreover, the reader is introduced to the following techniques: (i) continuous time maximum likelihood estimation; (ii) discrete time maximum likelihood estimation; and (iii) estimating functions. We show through a Monte Carlo simulation study that the parameter estimates obtained from these techniques provide a good approximation to the estimates obtained from the true transition density. We also show that the bias in the mean reversion parameter can be reduced by implementing the jackknife bias reduction technique. Furthermore, the data analysis carried out on South-African interest rate data indicate strongly that single factor models do not explain the variability in the short-term interest rate. This may indicate the possibility of distinct jumps in the South-African interest rate market. Therefore, we leave the reader with the notion of incorporating jumps into a SDE framework.

In this thesis we establish a relationship between the Potential Approach to interest rates and the Market Models. This relationship allows us to derive the dynamics of forward LIBOR rates and forward swap rates by modelling the state price density. It means that we are able to secure the arbitrage-free condition and positive interest rate feature when we model the volatility drifts of those dynamics. On the other hand, we develop the Potential Approach, particularly the Hughston-Rafailidis Chaotic Interest Rate Model. The early argument enables us to infer that the Chaos Models belong to the Stochastic Volatility Market Models. In particular, we propose One-variable Chaos Models with the application of exponential polynomials. This maintains the generality of the Chaos Models and performs well for yield curves comparing with the Nelson-Siegel Form and the Svensson Form. Moreover, we calibrate the One-variable Chaos Model to European Caplets and European Swaptions. We show that the One-variable Chaos Models can reproduce the humped shape of the term structure of caplet volatility and also the volatility smile/skew curve. The calibration errors are small compared with the Lognormal Forward LIBOR Model, the SABR Model, traditional Short Rate Models, and other models under the Potential Approach. After the calibration, we introduce some new interest rate models under the Potential Approach. In particular, we suggest a new framework where the volatility drifts can be indirectly modelled from the short rate via the state price density.

Thesis (MComm (Statistics and Actuarial Science))--University of Stellenbosch, 2006. / An overview of modern and historical interest rate model theory is given with the specific aim of derivative pricing. A variety of stochastic interest rate models are discussed within a South African market context. The various models are compared with respect to characteristics such as mean reversion, positivity of interest rates, the volatility structures they can represent, the yield curve shapes they can represent and weather analytical bond and derivative prices can be found. The distribution of the interest rates implied by some of these models is also found under various measures. The calibration of these models also receives attention with respect to instruments available in the South African market. Problems associated with the calibration of the modern models are also discussed.

Dans le Chapitre 1, nous présentons une nouvelle approche pour évaluer des options dites à barrières basée sur une méthode connue sous le nom de méthode Vanna-Volga. Cette nouvelle méthode nous permet une calibration simple et rapide sur le marché des options à barrières directement ce qui permet d'évaluer ces options avec un outil en accord avec le marché. Nous comparons également nos résultats avec ceux provenant d’autres modèles célèbres et nous étudions la sensibilité de cette méthode par rapport aux données du marché. Nous donnons une nouvelle justification théorique associée à la méthode Vanna-Volga comme étant une approximation de Taylor du premier ordre du prix de l'option autour de la volatilité dite à la monnaie.<p><p><p>Dans le Chapitre 2 de la thèse nous allons développer un modèle qui compte de la volatilité implicite du marché et de la variabilité des taux d'intérêts. Nous travaillons dans le marché particulier des taux de changes, avec un modèle à volatilité locale pour la dynamique du taux de change dans lequel les taux d'intérêts domestiques et étrangers sont également supposé stochastiques. Nous dérivons l'expression de la volatilité locale et dérivons divers résultats particulièrement utiles pour la calibration du modèle. Finalement, nous développons un nouveau modèle hybride où la volatilité du taux de change possède une composante locale et une composante stochastique et nous dérivons une méthode de calibration pour ce nouveau modèle.<p><p><p>Dans le Chapitre 3, nous allons appliquer le modèle à volatilité locale et taux d'intérêts stochastiques développé dans le précédent chapitre mais dans le cadre d'évaluation de produits dérivés associés aux assurances vie. Nous utilisons une méthode de calibration développée dans le Chapitre 2. Les produits étudiés étant exotiques, nous allons également comparer les prix obtenus dans différents modèles, à savoir le modèle à volatilité locale, à volatilité stochastique et enfin à volatilité constante pour le sous-jacent, les trois modèles étant combinés avec des taux d'intérêts stochastiques.<p><p><p>Finalement, dans le Chapitre 4 nous allons travailler avec un modèle dit de Lévy pour modéliser le sous-jacent. Nous nous intéressons à l'évaluation d'options Asiatiques arithmétiques. Comme de nombreuses options exotiques, il n'est pas possible d'obtenir un prix analytique et dans ce cas seules les méthodes numériques permettent de résoudre le problème. Dans ce Chapitre 4, nous développons une méthode basée sur la méthode de simulations de Monte Carlo et nous employons deux types de variables de contrôle permettant d'améliorer la convergence du programme. Nous développons également une méthode permettant d'obtenir une borne inférieure au prix de l'option avec une efficacité qui surpasse les autres méthodes.<p> / Doctorat en Sciences / info:eu-repo/semantics/nonPublished

This thesis presents the main results of my research in the field of computational finance and portfolios optimization. We focus on pricing Asian basket options and portfolio problems in the presence of inflation with stochastic interest rates.<p><p>In Chapter 2, we concentrate upon the derivation of bounds for European-style discrete arithmetic Asian basket options in a Black and Scholes framework.We start from methods used for basket options and Asian options. First, we use the general approach for deriving upper and lower bounds for stop-loss premia of sums of non-independent random variables as in Kaas et al. [Upper and lower bounds for sums of random variables, Insurance Math. Econom. 27 (2000) 151–168] or Dhaene et al. [The concept of comonotonicity in actuarial science and finance: theory, Insurance Math. Econom. 31(1) (2002) 3–33]. We generalize the methods in Deelstra et al. [Pricing of arithmetic basket options by conditioning, Insurance Math. Econom. 34 (2004) 55–57] and Vanmaele et al. [Bounds for the price of discrete sampled arithmetic Asian options, J. Comput. Appl. Math. 185(1) (2006) 51–90]. Afterwards we show how to derive an analytical closed-form expression for a lower bound in the non-comonotonic case. Finally, we derive upper bounds for Asian basket options by applying techniques as in Thompson [Fast narrow bounds on the value of Asian options, Working Paper, University of Cambridge, 1999] and Lord [Partially exact and bounded approximations for arithmetic Asian options, J. Comput. Finance 10 (2) (2006) 1–52]. Numerical results are included and on the basis of our numerical tests, we explain which method we recommend depending on moneyness and time-to-maturity<p><p>In Chapter 3, we propose some moment matching pricing methods for European-style discrete arithmetic Asian basket options in a Black & Scholes framework. We generalize the approach of Curran M. (1994) [Valuing Asian and portfolio by conditioning on the geometric mean price”, Management science, 40, 1705-1711] and of Deelstra G. Liinev J. and Vanmaele M. (2004) [Pricing of arithmetic basket options by conditioning”, Insurance: Mathematics & Economics] in several ways. We create a framework that allows for a whole class of conditioning random variables which are normally distributed. We moment match not only with a lognormal random variable but also with a log-extended-skew-normal random variable. We also improve the bounds of Deelstra G. Diallo I. and Vanmaele M. (2008). [Bounds for Asian basket options”, Journal of Computational and Applied Mathematics, 218, 215-228]. Numerical results are included and on the basis of our numerical tests, we explain which method we recommend depending on moneyness and<p>time-to-maturity.<p><p>In Chapter 4, we use the stochastic dynamic programming approach in order to extend<p>Brennan and Xia’s unconstrained optimal portfolio strategies by investigating the case in which interest rates and inflation rates follow affine dynamics which combine the model of Cox et al. (1985) [A Theory of the Term Structure of Interest Rates, Econometrica, 53(2), 385-408] and the model of Vasicek (1977) [An equilibrium characterization of the term structure, Journal of Financial Economics, 5, 177-188]. We first derive the nominal price of a zero coupon bond by using the evolution PDE which can be solved by reducing the problem to the solution of three ordinary differential equations (ODE). To solve the corresponding control problems we apply a verification theorem without the usual Lipschitz assumption given in Korn R. and Kraft H.(2001)[A Stochastic control approach to portfolio problems with stochastic interest rates, SIAM Journal on Control and Optimization, 40(4), 1250-1269] or Kraft(2004)[Optimal Portfolio with Stochastic Interest Rates and Defaultable Assets, Springer, Berlin].<p><p><p> / Doctorat en Sciences / info:eu-repo/semantics/nonPublished