本論文我們延伸Goldberg(1986)之結論,採用Ornstein Uhlenbeck positon process取代一般幾何布朗尼運動之假設來評價選擇權.Goldberg(1986)認為Ornstein Uhlenbeck positon process比幾何布朗尼運動更適合用來描述在不完全市場下之股價波動過程.我們在此波動過程的假設下,推倒出在風險中立的機率測度下歐式選擇權的評價模型及其避險參數,並將其結果與Black Scholes之模型作一比較,此評價模型亦可視為再不完全市場下的另一選擇權評價模型.此外,我們亦觀察在漲跌幅限制下股價波動之行為,發現股價具有三點特徵,而Ornstein Uhlenbeck positon process比幾何布朗尼運動更能貼切的表現出這些特徵,因此採用Ornstein Uhlenbeck positon process之選擇權評價模型較能合適地評價在漲跌幅限制下之選擇權價值. / In this thesis, we extend the approach of Goldenberg (1986) to consider Ornstein-Uhlenbeck position process as an alternative to Geometric Brownian Motion in modeling the underlying asset prices, and construct the option pricing model with this process. Goldenberg (1986) argued that Ornstein-Uhlenbeck position process is more consistent with the observed future prices in imperfect markets, and it could express the correlation of stock prices. Our model is an alternative option pricing model in imperfect market. We also investigate the behavior of stock prices in markets with the imposition of price limits. We find that the use of Ornstein-Uhlenbeck position process is more consistent with the characteristics of stock prices with price limit constraints than Geometric Brownian Motion. The use of Ornstein-Uhlenbeck position process could provide a more concise closed form of option pricing model when considering price limit constraints.

<p>Brownian motion has met growing interest in mathematics, physics and particularly in finance since it was introduced in the beginning of the twentieth century. Stochastic processes generalizing Brownian motion have influenced many research fields theoretically and practically. Moreover, along with more refined techniques in measure theory and functional analysis more stochastic processes were constructed and studied. Lévy processes, with Brownian motionas a special case, have been of major interest in the recent decades. In addition, Lévy processes include a number of other important processes as special cases like Poisson processes and subordinators. They are also related to stable processes.</p><p>In this thesis we generalize a result by S. Chandrasekhar [2] and Edward Nelson who gave a detailed proof of this result in his book in 1967 [12]. In Nelson’s first result standard Ornstein-Uhlenbeck processes are studied. Physically this describes free particles performing a random and irregular movement in water caused by collisions with the water molecules. In a further step he introduces a nonlinear drift in the position variable, i.e. he studies the case when these particles are exposed to an external field of force in physical terms.</p><p>In this report, we aim to generalize the result of Edward Nelson to the case of α-stable Lévy processes. In other words we replace the driving noise of a standard Ornstein-Uhlenbeck process by an α-stable Lévy noise and introduce a scaling parameter uniformly in front of all vector fields in the cotangent space, even in front of the noise. This corresponds to time being sent to infinity. With Chandrasekhar’s and Nelson’s choice of the diffusion constant the stationary state of the velocity process (which is approached as time tends to infinity) is the Boltzmann distribution of statistical mechanics.The scaling limits we obtain in the absence and presence of a nonlinear drift term by using the scaling property of the characteristic functions and time change, can be extended to other types of processes rather than α-stable Lévy processes.</p><p>In future, we will consider to generalize this one dimensional result to Euclidean space of arbitrary finite dimension. A challenging task is to consider the geodesic flow on the cotangent bundle of a Riemannian manifold with scaled drift and scaled Lévy noise. Geometrically the Ornstein-Uhlenbeck process is defined on the tangent bundle of the real line and the driving Lévy noise is defined on the cotangent space.</p>

In this thesis we use nonstandard methods for the valuation of derivatives on electricity. We model the dynamics of electricity spot price as mean reverting processes on the hyperfinite binomial tree and by switching to the risk-neutral world we derive analytical formulas for the price of forward contracts. Both of our models are fitted to the German electricity market and forward price predictions are compared with forward products traded on the exchange. We conclude that both the Ornstein-Uhlenbeck and the Schwartz one factor model fit long-term forward contracts well while our prediction results for short-term forward prod- ucts are not conclusive due to low liquidity and alternative approaches might be suitable. 1

La thèse est consacrée à étudier les relations entre les Équations aux Derivées Partielles Stochastiques et l'operateur de Kolmogorov associé dans des espaces de fonctions continues.<br />Dans la première partie, la théorie de la convergence faibles des fonctions est mis au point afin de donner des résultats généraux sur les semi-groupes des Markov et leur générateur.<br />Dans la deuxième partie, des modèles de semi-groups de Markov associés à des équations aux dérivées partielles stochastiques sont étudiés. En particulier, Ornstein-Uhlenbeck, réaction-diffusion et équations de Burgers ont été envisagées. Pour chaque cas, le semi-groupe de transition et son générateur infinitésimal ont été étudiées dans un espace de fonctions continues.<br />Les résultats principaux montrent que l'ensemble des fonctions exponentielles fournit un Core pour l'opérateur de Kolmogorov. En conséquence, on prouve l'unicité de l'équation de Kolmogorov de mesures (autrement dit de Fokker-Planck).

Brownian motion has met growing interest in mathematics, physics and particularly in finance since it was introduced in the beginning of the twentieth century. Stochastic processes generalizing Brownian motion have influenced many research fields theoretically and practically. Moreover, along with more refined techniques in measure theory and functional analysis more stochastic processes were constructed and studied. Lévy processes, with Brownian motionas a special case, have been of major interest in the recent decades. In addition, Lévy processes include a number of other important processes as special cases like Poisson processes and subordinators. They are also related to stable processes. In this thesis we generalize a result by S. Chandrasekhar [2] and Edward Nelson who gave a detailed proof of this result in his book in 1967 [12]. In Nelson’s first result standard Ornstein-Uhlenbeck processes are studied. Physically this describes free particles performing a random and irregular movement in water caused by collisions with the water molecules. In a further step he introduces a nonlinear drift in the position variable, i.e. he studies the case when these particles are exposed to an external field of force in physical terms. In this report, we aim to generalize the result of Edward Nelson to the case of α-stable Lévy processes. In other words we replace the driving noise of a standard Ornstein-Uhlenbeck process by an α-stable Lévy noise and introduce a scaling parameter uniformly in front of all vector fields in the cotangent space, even in front of the noise. This corresponds to time being sent to infinity. With Chandrasekhar’s and Nelson’s choice of the diffusion constant the stationary state of the velocity process (which is approached as time tends to infinity) is the Boltzmann distribution of statistical mechanics.The scaling limits we obtain in the absence and presence of a nonlinear drift term by using the scaling property of the characteristic functions and time change, can be extended to other types of processes rather than α-stable Lévy processes. In future, we will consider to generalize this one dimensional result to Euclidean space of arbitrary finite dimension. A challenging task is to consider the geodesic flow on the cotangent bundle of a Riemannian manifold with scaled drift and scaled Lévy noise. Geometrically the Ornstein-Uhlenbeck process is defined on the tangent bundle of the real line and the driving Lévy noise is defined on the cotangent space.

A stochastic differential equationdriven by a Brownian motion where the dispersion is determined by a parameter is considered. The parameter undergoes a change at a certain time point. Estimates of the time change point and the parameter, before and after that time, is considered.The estimates were presented in Lacus 2008. Two cases are considered: (1) the drift is known, (2) the drift is unknown and the dispersion space-independent. Applications to Dow-Jones index 1971-1974  and Goldmann-Sachs closings 2005-- May 2009 are given.

Frequency domain photon migration (FDPM) measurements are used to study the properties of dense colloidal dispersions with hard sphere and electrostatic interactions, which are otherwise difficult to analyze due to multiple scattering effects. Hard sphere interactions were studied using a theoretical model based upon a polydisperse mixture of particles using the hard sphere Percus Yevick theory. The particle size distribution and volume fraction were recovered by solving a non linear inverse problem using genetic algorithms. The mean sizes of the particles of 144 and 223 nm diameter were recovered within an error range of 0-15.53% of the mean diameters determined from dynamic light scattering measurements. The volume fraction was recovered within an error range of 0-24% of the experimentally determined volume fractions. At ionic strengths varying between 0.5 and 4 mM, multiple wavelength (660, 685, 785 and 828 nm) FDPM measurements of isotropic scattering coefficients were made of 144 and 223 nm diameter, monodisperse dispersions varying between 15% - 22% volume fraction, as well as of bidisperse mixtures of 144 and 223 nm diameter latex particles in 1:3, 1:1 and 3:1 mixtures varying between volume fractions of 15% - 24%. Structure factor models with Yukawa potential were computed by Monte Carlo (MC) simulations and numerical solution of the coupled Ornstein Zernike equations. In monodisperse dispersions of particle diameter 144 nm the isotropic scattering coefficient versus ionic strength show an increase with increasing ionic strength consistent with model predictions, whereas there was a reversal of trends and fluctuations for the particle diameter of 223 nm. In bidisperse mixtures for the case of maximum number of smaller particles, the isotropic scattering coefficient increased with increasing ionic strength and the trends were in conformity with MC simulations of binary Yukawa potential models. As the number of larger diameter particles increased in the dispersions, the isotropic scattering coefficients depicted fluctuations, and no match was found between the models and measurements for a number ratio of 1:3. The research lays the foundation for the determination of particle size distribution, volume fractions and an estimate of effective charge for high density of particles.

In this dissertation, we describe a novel method that we call Diffusing Colloidal Probe Microscopy (DCPM), which integrates Total Internal Reflection Microscopy (TIRM) and Video Microscopy (VM) methods to monitor three dimensional trajectories in colloidal ensembles levitated above macroscopic surfaces. TIRM and VM are well established optical microscopy techniques for measuring normal and lateral colloidal excursions near macroscopic planar surfaces. The interactions between particle-particle and particle-substrate in colloidal interfacial systems are interpreted by statistical analyses from distributions of colloidal particles; dynamic properties of colloidal assembly are also determined from particle trajectories. Our studies show that DCPM is able to detect many particle-surface interactions simultaneously and provides an ensemble average measurement of particle-surface interactions on a homogeneous surface to allow direct comparison of distributed and average properties. A benefit of ensemble averaging of many particles is the diminished need for time averaging, which can produce orders of magnitude faster measurement times at higher interfacial particle concentrations. The statistical analyses (Ornstein- Zernike and three dimensional Monte Carlo analyses) are used to obtain particle-particle interactions from lateral distribution functions and to understand the role of nonuniformities in interfacial colloidal systems. An inconsistent finding is the observation of an anomalous long range particle-particle attraction and recovery of the expected DLVO particle-wall interactions for all concentrations examined. The possible influence of charge heterogeneity and particle size polydispersity on measured distribution functions is discussed in regard to inconsistent particle-wall and particle-particle potentials. In the final part of this research, the ability of DCPM is demonstrated to map potential energy landscapes on patterned surfaces by monitoring interactions between diffusing colloidal probes with Au pattern features. Absolute separation is obtained from theoretical fits to measured potential energy profiles and direct measurement by sticking silica colloids to Au surfaces via electrophoretic deposition. Initial results indicate that, as colloidal probe and pattern feature dimensions become comparable, measured potential energy profiles suffer some distortion due to the increased probability of probes interacting with surfaces at the edges of adjacent pattern features. Measurements of lateral diffusion via analysis of mean square displacements also indicated lateral diffusion coefficients in excellent agreement with rigorous theoretical predictions.

<p>A stochastic differential equationdriven by a Brownian motion where the dispersion is determined by a parameter is considered. The parameter undergoes a change at a certain time point. Estimates of the time change point and the parameter, before and after that time, is considered.The estimates were presented in Lacus 2008. Two cases are considered: (1) the drift is known, (2) the drift is unknown and the dispersion space-independent. Applications to Dow-Jones index 1971-1974  and Goldmann-Sachs closings 2005-- May 2009 are given.</p>

Die vorliegende Arbeit beschäftigt sich mit der Parameteridentifikation in finanzmathematischen Modellen, welche sich durch eine zeitabhängige Volatilitätsfunktion und stochastische Driftkomponente auszeichnen. Als Referenzmodell wird eine Variante des Bivariaten Ornstein-Uhlenbeck-Modells betrachtet. Ziel ist es, die zeitabhängige Volatilitätsfunktion sowohl in der Vergangenheit als auch für ein kleines zukünftiges Zeitintervall zu identifizieren. Weiterhin sollen einige reellwertige Parameter, welche die stochastische Drift beschreiben, bestimmt werden. Dabei steht nicht die Anpassung des betrachteten Modells an reale Aktienpreisdaten im Vordergrund sondern eine mathematische Untersuchung der Chancen und Risiken der betrachteten Schätzverfahren. Als Daten können Aktienpreise und Optionspreise beobachtet werden. Aus hochfrequenten Aktienpreisdaten wird mittels Wavelet-Projektion die (quadrierte) Volatilitätsfunktion auf einem vergangenen Zeitintervall geschätzt. Mit der so bestimmten Volatilitätsfunktion und einigen Aktienpreisen können anschließend die reellwertigen Parameter mit Hilfe der Maximum-Likelihood-Methode bestimmt werden, wobei die Likelihoodfunktion mit Hilfe des Kalman Filters berechnet werden kann. Die Identifikation der Volatilitätsfunktion (oder abgeleiteter Größen) auf dem zukünftigen Zeitintervall aus Optionspreisen führt auf ein inverses Problem des Option Pricings, welches in ein äußeres nichtlineares und ein inneres lineares Problem zerlegt werden kann. Das innere Problem (die Identifikation einer Ableitung) ist ein Standardbeispielfür ein inkorrektes inverses Problem, d.h. die Lösung dieses Problems hängt nicht stetig von den Daten ab. Anhand von analytischen Untersuchungen von Nemytskii-Operatoren und deren Inversen wird in der Arbeit gezeigt, dass das äußere Problem gut gestellt aber in einigen Fällen schlecht konditioniert ist. Weiterhin wird ein Algorithmus für die schnelle Lösung des äußeren Problems unter Einbeziehung der Monotonieinformationen vorgeschlagen. Alle in der Arbeit diskutierten Verfahren werden anhand von numerischen Fallstudien illustriert.