Black-scholes type equations

In this work we are concerned with the analysis and numerical solution of Black-Scholes type equations arising in the modeling of incomplete financial markets and an inverse problem of determining the local volatility function in a generalized Black-Scholes model from observed option prices. In the first chapter a fully nonlinear Black-Scholes equation which models transaction costs arising in option pricing is discretized by a new high order compact scheme. The compact scheme is proved to be unconditionally stable and non-oscillatory and is very efficient compared to classical schemes. Moreover, it is shown that the finite difference solution converges locally uniformly to the unique viscosity solution of the continuous equation. In the next chapter we turn to the calibration problem of computing local volatility functions from market data in a generalized Black-Scholes setting. We follow an optimal control approach in a Lagrangian framework. We show the existence of a global solution and study first- and second-order optimality conditions. Furthermore, we propose an algorithm that is based on a globalized sequential quadratic programming method and a primal-dual active set strategy, and present numerical results. In the last chapter we consider a quasilinear parabolic equation with quadratic gradient terms, which arises in the modeling of an optimal portfolio in incomplete markets. The existence of weak solutions is shown by considering a sequence of approximate solutions. The main difficulty of the proof is to infer the strong convergence of the sequence. Furthermore, we prove the uniqueness of weak solutions under a smallness condition on the derivatives of the covariance matrices with respect to the solution, but without additional regularity assumptions on the solution. The results are illustrated by a numerical example.

Finite Element Method For A Nonlocal Problem Of Kirchhoff Type

The nonlocal term in the nonlinear equations of Kirchhoff type causes difficulties when the equation is solved numerically by using the Newton-Raphson method. This is because the Jacobian of the Newton-Raphson method is full. In this article, the finite element system is replaced by an equivalent system for which the Jacobian is sparse. We derive quasi-optimal error estimates for the finite element method and demonstrate the results with numerical experiments.

Noether-type discrete conserved quantities arising from a finite element approximation of a variational problem

In this work, we prove a weak Noether-type Theorem for a class of variational problems that admit broken extremals. We use this result to prove discrete Noether-type conservation laws for a conforming finite element discretisation of a model elliptic problem. In addition, we study how well the finite element scheme satisfies the continuous conservation laws arising from the application of Noether’s first theorem (1918). We summarise extensive numerical tests, illustrating the conservation of the discrete Noether law using the p-Laplacian as an example and derive a geometric-based adaptive algorithm where an appropriate Noether quantity is the goal functional.

Optimal control with stochastic PDE constraints and uncertain controls

The optimal control of problems that are constrained by partial differential equations with uncertainties and with uncertain controls is addressed. The Lagrangian that defines the problem is postulated in terms of stochastic functions, with the control function possibly decomposed into an unknown deterministic component and a known zero-mean stochastic component. The extra freedom provided by the stochastic dimension in defining cost functionals is explored, demonstrating the scope for controlling statistical aspects of the system response. One-shot stochastic finite element methods are used to find approximate solutions to control problems. It is shown that applying the stochastic collocation finite element method to the formulated problem leads to a coupling between stochastic collocation points when a deterministic optimal control is considered or when moments are included in the cost functional, thereby forgoing the primary advantage of the collocation method over the stochastic Galerkin method for the considered problem. The application of the presented methods is demonstrated through a number of numerical examples. The presented framework is sufficiently general to also consider a class of inverse problems, and numerical examples of this type are also presented. © 2011 Elsevier B.V.

Diskontinuierliche Galerkin-Verfahren für die operationelle Wettervorhersage

In dieser Arbeit wird ein neuer Dynamikkern entwickelt und in das bestehendernnumerische Wettervorhersagesystem COSMO integriert. Für die räumlichernDiskretisierung werden diskontinuierliche Galerkin-Verfahren (DG-Verfahren)rnverwendet, für die zeitliche Runge-Kutta-Verfahren. Hierdurch ist ein Verfahrenrnhoher Ordnung einfach zu realisieren und es sind lokale Erhaltungseigenschaftenrnder prognostischen Variablen gegeben. Der hier entwickelte Dynamikkern verwendetrngeländefolgende Koordinaten in Erhaltungsform für die Orographiemodellierung undrnkoppelt das DG-Verfahren mit einem Kessler-Schema für warmen Niederschlag. Dabeirnwird die Fallgeschwindigkeit des Regens, nicht wie üblich implizit imrnKessler-Schema diskretisiert, sondern explizit im Dynamikkern. Hierdurch sindrndie Zeitschritte der Parametrisierung für die Phasenumwandlung des Wassers undrnfür die Dynamik vollständig entkoppelt, wodurch auch sehr große Zeitschritte fürrndie Parametrisierung verwendet werden können. Die Kopplung ist sowohl fürrnOperatoraufteilung, als auch für Prozessaufteilung realisiert.rnrnAnhand idealisierter Testfälle werden die Konvergenz und die globalenrnErhaltungseigenschaften des neu entwickelten Dynamikkerns validiert. Die Massernwird bis auf Maschinengenauigkeit global erhalten. Mittels Bergüberströmungenrnwird die Orographiemodellierung validiert. Die verwendete Kombination ausrnDG-Verfahren und geländefolgenden Koordinaten ermöglicht die Behandlung vonrnsteileren Bergen, als dies mit dem auf Finite-Differenzenverfahren-basierendenrnDynamikkern von COSMO möglich ist. Es wird gezeigt, wann die vollernTensorproduktbasis und wann die Minimalbasis vorteilhaft ist. Die Größe desrnEinflusses auf das Simulationsergebnis der Verfahrensordnung, desrnParametrisierungszeitschritts und der Aufteilungsstrategie wirdrnuntersucht. Zuletzt wird gezeigt dass bei gleichem Zeitschritt die DG-Verfahrenrnaufgrund der besseren Skalierbarkeit in der Laufzeit konkurrenzfähig zurnFinite-Differenzenverfahren sind.

A characteristic based numerical method with tracking for nonlinear wave equations

Many physical problems can be modeled by scalar, first-order, nonlinear, hyperbolic, partial differential equations (PDEs). The solutions to these PDEs often contain shock and rarefaction waves, where the solution becomes discontinuous or has a discontinuous derivative. One can encounter difficulties using traditional finite difference methods to solve these equations. In this paper, we introduce a numerical method for solving first-order scalar wave equations. The method involves solving ordinary differential equations (ODEs) to advance the solution along the characteristics and to propagate the characteristics in time. Shocks are created when characteristics cross, and the shocks are then propagated by applying analytical jump conditions. New characteristics are inserted in spreading rarefaction fans. New characteristics are also inserted when values on adjacent characteristics lie on opposite sides of an inflection point of a nonconvex flux function, Solutions along characteristics are propagated using a standard fourth-order Runge-Kutta ODE solver. Shocks waves are kept perfectly sharp. In addition, shock locations and velocities are determined without analyzing smeared profiles or taking numerical derivatives. In order to test the numerical method, we study analytically a particular class of nonlinear hyperbolic PDEs, deriving closed form solutions for certain special initial data. We also find bounded, smooth, self-similar solutions using group theoretic methods. The numerical method is validated against these analytical results. In addition, we compare the errors in our method with those using the Lax-Wendroff method for both convex and nonconvex flux functions. Finally, we apply the method to solve a PDE with a convex flux function describing the development of a thin liquid film on a horizontally rotating disk and a PDE with a nonconvex flux function, arising in a problem concerning flow in an underground reservoir.

Counting zero kernel pairs over a finite field

Helmke et al. have recently given a formula for the number of reachable pairs of matrices over a finite field. We give a new and elementary proof of the same formula by solving the equivalent problem of determining the number of so called zero kernel pairs over a finite field. We show that the problem is, equivalent to certain other enumeration problems and outline a connection with some recent results of Guo and Yang on the natural density of rectangular unimodular matrices over F-qx]. We also propose a new conjecture on the density of unimodular matrix polynomials. (C) 2016 Elsevier Inc. All rights reserved.

Finite element modelling of the sismic behaviour of water front structures

Water front structures have suffered significant damage in many of the recent earthquakes. These include gravity type quay walls, vertically composite walls, cantilever retaining walls, anchored bulkheads and similar structures. One of the primary causes for the poor performance of these classes of structures is the liquefaction of the foundation soil and in some instances liquefaction of the backfill soil. The liquefaction of the soil in-front of the quay wall tends to cause large lateral displacements and rotation of the wall. Often such gravity walls are placed on rubble mound deposited onto the sea bed.This paper presents finite element analyses of such a problem in which strength degradation of the foundation soil and the backfill material will be modelled using PZ mark III constitutive model. The performance of the wall in terms of its lateral displacement, vertical settlement and/or the rotation suffered by the wall will be presented. In addition, the contours of the horizontal and vertical effective stresses and the excess pore pressure ratio will be presented at different time instants together with hyrdraulic gradients. Immediately after the earthquake, the hydraulic gradients indicate migration of pore water into the region below the wall, suggesting further softening of the foundation soil below the wall.

Formalizing Triggers: A Learning Model for Finite Spaces

In a recent seminal paper, Gibson and Wexler (1993) take important steps to formalizing the notion of language learning in a (finite) space whose grammars are characterized by a finite number of parameters. They introduce the Triggering Learning Algorithm (TLA) and show that even in finite space convergence may be a problem due to local maxima. In this paper we explicitly formalize learning in finite parameter space as a Markov structure whose states are parameter settings. We show that this captures the dynamics of TLA completely and allows us to explicitly compute the rates of convergence for TLA and other variants of TLA e.g. random walk. Also included in the paper are a corrected version of GW's central convergence proof, a list of "problem states" in addition to local maxima, and batch and PAC-style learning bounds for the model.

Bose-Einstein condensation dynamics in three dimensions by the pseudospectral and finite-difference methods

We suggest a pseudospectral method for solving the three-dimensional time-dependent Gross-Pitaevskii (GP) equation, and use it to study the resonance dynamics of a trapped Bose-Einstein condensate induced by a periodic variation in the atomic scattering length. When the frequency of oscillation of the scattering length is an even multiple of one of the trapping frequencies along the x, y or z direction, the corresponding size of the condensate executes resonant oscillation. Using the concept of the differentiation matrix, the partial-differential GP equation is reduced to a set of coupled ordinary differential equations, which is solved by a fourth-order adaptive step-size control Runge-Kutta method. The pseudospectral method is contrasted with the finite-difference method for the same problem, where the time evolution is performed by the Crank-Nicholson algorithm. The latter method is illustrated to be more suitable for a three-dimensional standing-wave optical-lattice trapping potential.

Foil rolling : a new interpretation of experimental results

This paper explores a new interpretation of experiments on foil rolling. The assumption that the roll remains convex is relaxed so that the strip profile may become concave, or thicken in the roll gap. However, we conjecture that the concave profile is associated with phenomena which occur after the rolls have stopped. We argue that the yield criterion must be satisfied in a nonconventional manner if such a phenomenon is caused plastically. Finite element analysis on an extrusion problem appears to confirm this conjecture.

Optimal Parameter Trajectory Estimation in Parameterized SDEs: An Algorithmic Procedure

We consider the problem of estimating the optimal parameter trajectory over a finite time interval in a parameterized stochastic differential equation (SDE), and propose a simulation-based algorithm for this purpose. Towards this end, we consider a discretization of the SDE over finite time instants and reformulate the problem as one of finding an optimal parameter at each of these instants. A stochastic approximation algorithm based on the smoothed functional technique is adapted to this setting for finding the optimal parameter trajectory. A proof of convergence of the algorithm is presented and results of numerical experiments over two different settings are shown. The algorithm is seen to exhibit good performance. We also present extensions of our framework to the case of finding optimal parameterized feedback policies for controlled SDE and present numerical results in this scenario as well.

Numerical studies of gypsum plasterboard and MGO board lined LSF walls exposed to fire

Fire resistance of cold-formed light gauge steel frame (LSF) wall systems is enhanced by lining them with single or multiple layers of wall boards with varying thermal properties. These wall boards are gypsum plasterboards or Magnesium Oxide (MgO) boards produced by different manufacturers. Thermal properties of these boards appear to show considerable variations and this can lead to varying fire resistance levels (FRL) for their wall systems. Currently FRLs of wall systems are determined using full scale fire tests, but they are time consuming and expensive. Recent research studies on the fire performance of LSF wall systems have used finite element studies to overcome this problem, but they were developed based on 1-D and 2-D finite element platform capable of performing either heat transfer or structural analysis separately. Hence in this research a 3-D finite element model was developed first for LSF walls lined with gypsum plasterboard and cavity insulation materials. Accurate thermal properties of these boards are essential for finite element modelling, and thus they were measured at both ambient and elevated temperatures. This experimental study included specific heat, relative density and thermal conductivity of boards. The developed 3-D finite element model was then validated using the available fire tests results of LSF walls lined with gypsum plasterboard, and is being used to investigate the fire performance of different LSF wall configurations. The tested MgO board exhibited significant variations in their thermal properties in comparison to gypsum plasterboards with about 50% loss of its initial mass at about 500 ºC compared to 16% for gypsum plasterboards. Hence the FRL of MgO board lined LSF wall systems is likely to be significantly reduced. This paper presents the details of this research study on the fire performance of LSF wall systems lined with gypsum plasterboard and MgO board including the developed 3-D finite element models, thermal property tests and the results.

Determinação de uma fonte de contaminantes no estuário do Rio Macaé através da técnica de problemas inversos

Um grande desafio da atualidade é a preservação dos recursos hídricos, bem como o correto manejo dos mesmos, frente à expansão das cidades e às atividades humanas. A qualidade de um corpo hídrico é usualmente avaliada através da análise de parâmetros biológicos, físicos e químicos. O comportamento de tais parâmetros pode convenientemente ser simulado através de modelos matemáticos e computacionais, que surgem assim como uma ferramenta bastante útil, por sua capacidade de geração de cenários que possam embasar, por exemplo, tomadas de decisão. Nesta tese são discutidas técnicas de estimação da localização e intensidade de uma fonte de contaminante conservativo, hipoteticamente lançado na região predominantemente fluvial de um estuário. O lançamento aqui considerado se dá de forma pontual e contínua e a região enfocada compreendeu o estuário do Rio Macaé, localizado na costa norte do Rio de Janeiro. O trabalho compreende a solução de um problema direto, que consiste no transporte bidimensional (integrado na vertical) desse contaminante hipotético, bem como a aplicação de técnicas de problemas inversos. Para a solução do transporte do contaminante, aqui modelada pela versão 2D horizontal da equação de advecção-difusão, foram utilizados como métodos de discretização o Método de Elementos Finitos e o Método de Diferenças Finitas. Para o problema hidrodinâmico foram utilizados dados de uma solução já desenvolvida para estuário do Rio Macaé. Analisada a malha de acordo com o método de discretização, foram definidas a geometria do estuário e os parâmetros hidrodinâmicos e de transporte. Para a estimação dos parâmetros propostos foi utilizada a técnica de problemas inversos, com o uso dos métodos Luus-Jaakola, Algoritmo de Colisão de Partículas e Otimização por Colônia de Formigas para a estimação da localização e do método Seção Áurea para a estimação do parâmetro de intensidade da fonte. Para a definição de uma fonte, com o objetivo de propor um cenário experimental idealizado e de coleta de dados de amostragem, foi realizada a análise de sensibilidade quanto aos parâmetros a serem estimados. Como os dados de amostragem de concentração foram sintéticos, o problema inverso foi resolvido utilizando-os com e sem ruído, esse introduzido de forma artificial e aleatória. Sem o uso de ruído, os três métodos mostraram-se igualmente eficientes, com uma estimação precisa em 95% das execuções. Já com o uso de dados de amostragem com ruídos de 5%, o método Luus-Jaakola mostrou-se mais eficiente em esforço e custo computacional, embora todos tenham estimado precisamente a fonte em 80% das execuções. Considerando os resultados alcançados neste trabalho tem-se que é possível estimar uma fonte de constituintes, quanto à sua localização e intensidade, através da técnica de problemas inversos. Além disso, os métodos aplicados mostraram-se eficientes na estimação de tais parâmetros, com estimações precisas para a maioria de suas execuções. Sendo assim, o estudo do comportamento de contaminantes, e principalmente da identificação de fontes externas, torna-se uma importante ferramenta para a gestão dos recursos hídricos, possibilitando, inclusive, a identificação de possíveis responsáveis por passivos ambientais.