This volume is a collection of solicited and refereed articles from distinguished researchers across the field of stochastic analysis and its application to finance. The articles represent new directi
This book introduces some advanced topics in probability theories - both pure and applied. It is divided into two parts: the first part deals with the analysis of stochastic dynamical systems, in term
The theory of Markov decision processes focuses on controlled Markov chains in discrete time. The authors establish the theory for general state and action spaces and at the same time show its applica
This book provides a comprehensive account of stochastic filtering as a modeling tool in finance and economics. It aims to present this very important tool with a view to making it more popular among
This book presents a concise and rigorous treatment of stochastic calculus. It also gives its main applications in finance, biology and engineering. In finance, the stochastic calculus is applied to p
This book presents a concise and rigorous treatment of stochastic calculus. It also gives its main applications in finance, biology and engineering. In finance, the stochastic calculus is applied to p
Drawing from many sources in the literature, Stochastic Dominance and Applications to Finance, Risk and Economics illustrates how stochastic dominance (SD) can be used as a method for risk assessment
"This book uniquely utilizes visualization tools to explain and study statistical learning methods. Covering classification and regression, the book is divided into two parts. First, various visualiza
This book presents recently developed statistical methods and theory required for the application of the tools of functional data analysis to problems arising in geosciences, finance, economics and bi
Financial engineering has been proven to be a useful tool for risk management, but using the theory in practice requires a thorough understanding of the risks and ethical standards involved. Stochasti
The recent financial crisis has heightened the need for appropriate methodologies for managing and monitoring complex risks in financial markets. The measurement, management, and regulation of risks in portfolios composed of credits, credit derivatives, or life insurance contracts is difficult because of the nonlinearities of risk models, dependencies between individual risks, and the several thousands of contracts in large portfolios. The granularity principle was introduced in the Basel regulations for credit risk to solve these difficulties in computing capital reserves. In this book, authors Patrick Gagliardini and Christian Gouriéroux provide the first comprehensive overview of the granularity theory and illustrate its usefulness for a variety of problems related to risk analysis, statistical estimation, and derivative pricing in finance and insurance. They show how the granularity principle leads to analytical formulas for risk analysis that are simple to implement and accurate e
The recent financial crisis has heightened the need for appropriate methodologies for managing and monitoring complex risks in financial markets. The measurement, management, and regulation of risks in portfolios composed of credits, credit derivatives, or life insurance contracts is difficult because of the nonlinearities of risk models, dependencies between individual risks, and the several thousands of contracts in large portfolios. The granularity principle was introduced in the Basel regulations for credit risk to solve these difficulties in computing capital reserves. In this book, authors Patrick Gagliardini and Christian Gouriéroux provide the first comprehensive overview of the granularity theory and illustrate its usefulness for a variety of problems related to risk analysis, statistical estimation, and derivative pricing in finance and insurance. They show how the granularity principle leads to analytical formulas for risk analysis that are simple to implement and accurate e
The purpose of the book is to present the Malliavin-Skorohod calculus for additive processes, that is, processes with independent increments; in other words, Lévy processes without the hypothesis of s
This book is designed to help readers grasp the conceptual underpinnings of time series modeling in order to gain a deeper understanding of the ever-changing dynamics of the financial world.It
This book introduces the theory of stochastic processes with applications taken from physics and finance. Fundamental concepts like the random walk or Brownian motion but also Levy-stable distribution
Corporate Finance: Core was developed for the graduate (MBA) level as a concise, up-to-date, and to-the-point product, the majority of which can be realistically covered in a single term or course. To achieve the objective of reaching out to the many different types of students and the varying course settings, corporate finance is distilled down to its core, while maintaining a decidedly modern approach. Purely theoretical issues are downplayed, and the use of extensive and elaborate calculations is minimized to illustrate points that are either intuitively obvious or of limited practical use. The goal was to focus on what students really need to carry away from a principles course. A balance is struck by introducing and covering the essentials, while leaving more specialized topics to follow-up courses. Net present value is treated as the underlying and unifying concept in corporate finance. Every subject covered is firmly rooted in valuation, and care is taken throughout to explain h
