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Pathwise functional lto calculus and its applications to the mathematical financeNkosi, Siboniso Confrence January 2019 (has links)
Thesis (M.Sc. (Applied Mathematics)) -- University of Limpopo, 2019 / Functional Itˆo calculus is based on an extension of the classical Itˆo calculus to functionals depending
on the entire past evolution of the underlying paths and not only on its current value. The
calculus builds on F¨ollmer’s deterministic proof of the Itˆo formula Föllmer (1981) and a notion
of pathwise functional derivative recently proposed by Dupire (2019). There are no smoothness
assumptions required on the functionals, however, they are required to possess certain directional
derivatives which may be computed pathwise, see Cont and Fournié (2013); Schied and
Voloshchenko (2016a); Cont (2012).
In this project we revise the functional Itô calculus together with the notion of quadratic variation.
We compute the pathwise change of variable formula utilizing the functional Itô calculus and the
quadratic variation notion. We study the martingale representation for the case of weak derivatives,
we allow the vertical operator, rX, to operate on continuous functionals on the space of
square-integrable Ft-martingales with zero initial value. We approximate the hedging strategy,
H, for the case of path-dependent functionals, with Lipschitz continuous coefficients. We study
some hedging strategies on the class of discounted market models satisfying the quadratic variation
and the non-degeneracy properties. In the classical case of the Black-Scholes, Greeks are an
important part of risk-management so we compute Greeks of the price given by path-dependent
functionals. Lastly we show that they relate to the classical case in the form of examples. / NRF and
AIMS-SA
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Essays on Market Microstructure and Pathwise Directional DerivativesBielagk, Jana 23 February 2018 (has links)
Wir befassen uns mit Gleichgewichtsproblemen, die bei dem Zusammentreffen von Märkten und Marktteilnehmern entstehen, zuerst in einem Modell mit konkurrierenden Märkten mit Feedback und asymmetrischer Information und dann mit strategisch interagierenden Händlern. Zudem untersuchen wir spezielle Richtungsableitung im Kontext des pfadweisen Malliavinkalküls.
Im ersten Kapitel analysieren wir ein Prinzipal-Agenten-Problem mit einem monopolistischen Dealer, der mit einem Crossing-Netzwerk (CN) um den Handel mit Agenten mit privater Information konkurriert. Wir untersuchen die gewinnmaximierenden Angebote des Dealers für unterschiedliche Outside-Optionen und formulieren hinreichende Bedingungen für die Existenz und Eindeutigkeit einer optimalen Lösung. In unserem Modell ist die Einführung des CN für die Agenten vorteilhaft und ein Gleichgewichtspreis existiert.
Im zweiten Kapitel analysieren wir den Einfluss vergleichender Leistungsbewertung von Händlern auf die Preisfindung im Marktgleichgewicht. Ein Derivat soll einen markträumenden Preis bekommen unter Beachtung der strategisch handelnden Agenten. Das Risiko eines Händlers setzt sich aus dem eigenen Risikoprofil und dem Erfolg des Handelns relativ zum durchschnittlichen Handelserfolg aller zusammen und er wird durch eine BSDE gemessen. Wir bestimmen einen repräsentativen Agenten und zeigen so die Existenz und Eindeutigkeit eines Gleichgewichtspreises. Weiterhin können wir diesen charakterisieren und im Spezialfall von entropischen Risikomaßen konkret berechnen. In diesem Spezialfall führen wir auch eine Parameteranalyse durch.
Das dritte Kapitel verknüpft klassischen und pfadweisen Malliavinkalkül. Wir definieren und analysieren pfadweise Richtungsableitungen mit Hilfe von Perturbationen mit Cameron-Martin-Funktionen, mit (Hölder-)stetigen Funktionen, mit unstetigen Funktionen und mit Maßen. Somit sind sowohl die klassische Malliavin-Ableitung als auch Dupires vertikale Ableitung als Spezialfälle enthalten. / We analyze equilibrium problems arising from interacting markets and market participants, first competing markets with feedback and asymmetric information, then strategically interacting traders; moreover we analyze a new notion of a pathwise directional derivative in the context of pathwise Malliavin calculus.
The first chapter analyzes a principal-agent game in which a monopolistic profit-maximizing dealer competes with a crossing network (CN) for trading with privately informed agents. We analyze the structure of the dealer’s offered pricing schedules for different outside options. We give sufficient conditions for the existence and uniqueness of a solution to the dealer’s problem and show that in our setting the introduction of the CN is beneficial for the agents. Additionally, we discuss existence and uniqueness of an equilibrium price for the feedback between dealer and CN.
In the second chapter we analyze the impact of performance concerns on a problem of equilibrium pricing. A derivative is priced such that the market clears, given strategically behaving agents. Their risk stems from a risky position in the future and the relative trading gains compared to all other agents. The risk measure of each agent is specified by a BSDE. In spite of the strategic interaction, we are able to apply a representative agent approach to obtain existence and uniqueness of the equilibrium market price of external risk. In the special case of entropic risk measures, we perform a parameter analysis.
The third chapter provides a link between classical and pathwise Malliavin calculus. We define and analyze pathwise directional derivatives via perturbations with Cameron-Martin functions, (Hölder-)continuous functions, discontinuous functions and measures, thereby including both the traditional Malliavin derivative and the vertical derivative from Dupire’s work.
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Numerical Complexity Analysis of Weak Approximation of Stochastic Differential EquationsTempone Olariaga, Raul January 2002 (has links)
The thesis consists of four papers on numerical complexityanalysis of weak approximation of ordinary and partialstochastic differential equations, including illustrativenumerical examples. Here by numerical complexity we mean thecomputational work needed by a numerical method to solve aproblem with a given accuracy. This notion offers a way tounderstand the efficiency of different numerical methods. The first paper develops new expansions of the weakcomputational error for Ito stochastic differentialequations using Malliavin calculus. These expansions have acomputable leading order term in a posteriori form, and arebased on stochastic flows and discrete dual backward problems.Beside this, these expansions lead to efficient and accuratecomputation of error estimates and give the basis for adaptivealgorithms with either deterministic or stochastic time steps.The second paper proves convergence rates of adaptivealgorithms for Ito stochastic differential equations. Twoalgorithms based either on stochastic or deterministic timesteps are studied. The analysis of their numerical complexitycombines the error expansions from the first paper and anextension of the convergence results for adaptive algorithmsapproximating deterministic ordinary differential equations.Both adaptive algorithms are proven to stop with an optimalnumber of time steps up to a problem independent factor definedin the algorithm. The third paper extends the techniques to theframework of Ito stochastic differential equations ininfinite dimensional spaces, arising in the Heath Jarrow Mortonterm structure model for financial applications in bondmarkets. Error expansions are derived to identify differenterror contributions arising from time and maturitydiscretization, as well as the classical statistical error dueto finite sampling. The last paper studies the approximation of linear ellipticstochastic partial differential equations, describing andanalyzing two numerical methods. The first method generates iidMonte Carlo approximations of the solution by sampling thecoefficients of the equation and using a standard Galerkinfinite elements variational formulation. The second method isbased on a finite dimensional Karhunen- Lo`eve approximation ofthe stochastic coefficients, turning the original stochasticproblem into a high dimensional deterministic parametricelliptic problem. Then, adeterministic Galerkin finite elementmethod, of either h or p version, approximates the stochasticpartial differential equation. The paper concludes by comparingthe numerical complexity of the Monte Carlo method with theparametric finite element method, suggesting intuitiveconditions for an optimal selection of these methods. 2000Mathematics Subject Classification. Primary 65C05, 60H10,60H35, 65C30, 65C20; Secondary 91B28, 91B70. / QC 20100825
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Une étude de la régularité de solutions d'EDS Rétrogrades et de leurs utilisations en finance / Regularity of solutions to Backward SDEs and applications to financeMastrolia, Thibaut 14 December 2015 (has links)
Dans cette thèse, nous donnerons tout d'abord des conditions sur les paramètres d’une EDSR à générateur lipschitzien ou à croissance quadratique telles que les processus solutions de l’EDSR admettent des densités par rapport à la mesure de Lebesgue. Puis, nous donnerons des conditions sur les paramètres d’une EDSR non-markovienne à générateur lipschitzien ou quadratique telles que les processus solutions de l’EDSR admettent une dérivée de Malliavin, à l’aide d’une nouvelle caractérisation de cette dérivée. Ce résultat nous fournira une nouvelle structure interne des espaces de Malliavin que nous étudierons. Nous donnerons ensuite des conditions nous assurant que des solutions d’EDSR non-markoviennes à générateurs lipschitziens stochastiques sont différentiables au sens de Malliavin en utilisant cette caractérisation. Nous ferons ensuite une analyse de densités pour les lois des solutions de telles EDSR et nous appliquerons nos résultats à la biologie. Enfin, nous étudierons deux exemples d’utilisations des EDSR en finance. On s’intéressera tout d’abord à un problème de maximisation d’utilité avec un horizon aléatoire que nous réduirons à l’analyse d’un nouveau type d’EDSR à coefficients singuliers et nous illustrerons nos résultats par des simulations numériques. Puis, nous résoudrons un problème de type Principal/Agent sous volatilité incertaine. / In the first part of this PhD thesis, we give conditions on the parameters of Lipschitz and quadratic growth BSDEs such that the laws of the components Y and Z of the solutions to such BSDEs admit densities with respect to the Lebesgue measure. We then provide conditions on the parameters of non-Markovian Lipschitz or quadratic growth BSDEs such that the components Y and Z of their solutions are Malliavin differentiable. We obtain these conditions by applying a new characterization of the Malliavin differentiability, as an Lp convergence criterion of difference quotients. This result provide also a new characterization of the Malliavin-Sobolev spaces that we study in detail. To finish this first theoretical part, we provide conditions ensuring that solutions of non-Markovian stochastic-Lipschitz BSDEs are Malliavin differentiable by applying the characterization of the Malliavin differentiability obtained. We then analyse the existence of densities for the laws of the components of solutions to such BSDEs and we apply our result to a model of gene expression. In the second part of this thesis, we investigate financial problems dealing with BSDEs. We first solve a utility maximization problem with a random horizon, characterized by an exogenous default time. We reduce it to the analysis of a specific BSDE, which we call BSDE with singular coefficients, when the default time is assumed to be bounded. We give conditions ensuring the existence and the uniqueness of solutions to such BSDE and we illustrate our results by numerical simulations. Then, we solve a Principal/Agent problem with ambiguity, in which the "Nature" impacts both the utilities of the Agent and the Principal, charaterized by sets of probability measures which modify the volatility.
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Structures contrôlées pour les équations aux dérivées partielles / Controlled structures for partial differential equationsFurlan, Marco 26 June 2018 (has links)
Le projet de thèse comporte différentes directions possibles: a) Améliorer la compréhension des relations entre la théorie des structures de régularité développée par M. Hairer et la méthode des Distributions Paracontrolées développée par Gubinelli, Imkeller et Perkowski, et éventuellement fournir une synthèse des deux. C'est très spéculatif et, pour le moment, il n'y a pas de chemin clair vers cet objectif à long terme. b) Utiliser la théorie des Distributions Paracontrolées pour étudier différents types d'équations aux dérivés partiels: équations de transport et équations générales d'évolution hyperbolique, équations dispersives, systèmes de lois de conservation. Ces EDP ne sont pas dans le domaine des méthodes actuelles qui ont été développées principalement pour gérer les équations d'évolution semi-linéaire parabolique. c) Une fois qu'une théorie pour l'équation de transport perturbée par un signal irregulier a été établie, il sera possible de se dédier à l'étude des phénomènes de régularisation par le bruit qui, pour le moment, n'ont étés étudiés que dans le contexte des équations de transport perturbées par le mouvement brownien, en utilisant des outils standard d'analyse stochastique. d) Les techniques du Groupe de Renormalisation (GR) et les développements multi-échelles ont déjà été utilisés à la fois pour aborder les EDP et pour définir des champs quantiques euclidiens. La théorie des Distributions Paracontrolées peut être comprise comme une sorte d'analyse multi-échelle des fonctionnels non linéaires et il serait intéressant d'explorer l'interaction des techniques paradifférentielles avec des techniques plus standard, comme les "cluster expansions" et les méthodes liées au GR. / The thesis project has various possible directions: a) Improve the understanding of the relations between the theory of Regularity Structures developed by M.Hairer and the method of Paracontrolled Distributions developed by Gubinelli, Imkeller and Perkowski, and eventually to provide a synthesis. This is highly speculative and at the moment there are no clear path towards this long term goal. b) Use the theory of Paracontrolled Distributions to study different types of PDEs: transport equations and general hyperbolic evolution equation, dispersive equations, systems of conservation laws. These PDEs are not in the domain of the current methods which were developed mainly to handle parabolic semilinear evolution equations. c) Once a theory of transport equation driven by rough signals have been established it will become possible to tackle the phenomena of regularization by transport noise which for the moment has been studied only in the context of transport equations driven by Brownian motion, using standard tools of stochastic analysis. d) Renormalization group (RG) techniques and multi-scale expansions have already been used both to tackle PDE problems and to define Euclidean Quantum Field Theories. Paracontrolled Distributions theory can be understood as a kind of mul- tiscale analysis of non-linear functionals and it would be interesting to explore the interplay of paradifferential techniques with more standard techniques like cluster expansions and RG methods.
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Variational and Ergodic Methods for Stochastic Differential Equations Driven by Lévy ProcessesGairing, Jan Martin 03 April 2018 (has links)
Diese Dissertation untersucht Aspekte des Zusammenspiels von ergodischem Langzeitver-
halten und der Glättungseigenschaft dynamischer Systeme, die von stochastischen Differen-
tialgleichungen (SDEs) mit Sprüngen erzeugt sind. Im Speziellen werden SDEs getrieben
von Lévy-Prozessen und der Marcusschen kanonischen Gleichung untersucht. Ein vari-
ationeller Ansatz für den Malliavin-Kalkül liefert eine partielle Integration, sodass eine
Variation im Raum in eine Variation im Wahrscheinlichkeitsmaß überführt werden kann.
Damit lässt sich die starke Feller-Eigenschaft und die Existenz glatter Dichten der zuge-
hörigen Markov-Halbgruppe aus einer nichtstandard Elliptizitätsbedingung an eine Kom-
bination aus Gaußscher und Sprung-Kovarianz ableiten. Resultate für Sprungdiffusionen
auf Untermannigfaltigkeiten werden aus dem umgebenden Euklidischen Raum hergeleitet.
Diese Resultate werden dann auf zufällige dynamische Systeme angewandt, die von lin-
earen stochastischen Differentialgleichungen erzeugt sind. Ruelles Integrierbarkeitsbedin-
gung entspricht einer Integrierbarkeitsbedingung an das Lévy-Maß und gewährleistet die
Gültigkeit von Oseledets multiplikativem Ergodentheorem. Damit folgt die Existenz eines
Lyapunov-Spektrums. Schließlich wird der top Lyapunov-Exponent über eine Formel der
Art von Furstenberg–Khasminsikii als ein ergodisches Mittel der infinitesimalen Wachs-
tumsrate über die Einheitssphäre dargestellt. / The present thesis investigates certain aspects of the interplay between the ergodic long
time behavior and the smoothing property of dynamical systems generated by stochastic
differential equations (SDEs) with jumps, in particular SDEs driven by Lévy processes and
the Marcus’ canonical equation. A variational approach to the Malliavin calculus generates
an integration-by-parts formula that allows to transfer spatial variation to variation in the
probability measure. The strong Feller property of the associated Markov semigroup and
the existence of smooth transition densities are deduced from a non-standard ellipticity
condition on a combination of the Gaussian and a jump covariance. Similar results on
submanifolds are inferred from the ambient Euclidean space.
These results are then applied to random dynamical systems generated by linear stochas-
tic differential equations. Ruelle’s integrability condition translates into an integrability
condition for the Lévy measure and ensures the validity of the multiplicative ergodic theo-
rem (MET) of Oseledets. Hence the exponential growth rate is governed by the Lyapunov
spectrum. Finally the top Lyapunov exponent is represented by a formula of Furstenberg–
Khasminskii–type as an ergodic average of the infinitesimal growth rate over the unit
sphere.
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