Nonlinear Expectations And Stochastic Calculus Under Uncertainty

This book is focused on the recent developments on problems of probability model uncertainty by using the notion of nonlinear expectations and, in particular, sublinear expectations. It provides a gentle coverage of the theory of nonlinear expectations and related stochastic analysis. Many notions and results, for example, G-normal distribution, G-Brownian motion, G-Martingale representation theorem, and related stochastic calculus are first introduced or obtained by the author. This book is based on Shige Peng’s lecture notes for a series of lectures given at summer schools and universities worldwide. It starts with basic definitions of nonlinear expectations and their relation to coherent measures of risk, law of large numbers and central limit theorems under nonlinear expectations, and develops into stochastic integral and stochastic calculus under G-expectations. It ends with recent research topic on G-Martingale representation theorem and G-stochastic integral for locally integrable processes. With exercises to practice at the end of each chapter, this book can be used as a graduate textbook for students in probability theory and mathematical finance. Each chapter also concludes with a section Notes and Comments, which gives history and further references on the material covered in that chapter. Researchers and graduate students interested in probability theory and mathematical finance will find this book very useful.

ICM 2010 proceedings comprises a four-volume set containing articles based on plenary lectures and invited section lectures, the Abel and Noether lectures, as well as contributions based on lectures delivered by the recipients of the Fields Medal, the Nevanlinna, and Chern Prizes. The first volume will also contain the speeches at the opening and closing ceremonies and other highlights of the Congress.

Financial engineering has become the focus of widespread media attention as a result of the worldwide financial crisis of recent years. This book is the second in a series dealing with financial engineering from Ajou University in Korea. The main objective of the series is to disseminate recent developments and important issues in financial engineering to graduate students and researchers, and to provide surveys or pedagogical exposition of important published papers in a broad perspective, as well as analyses of important financial news concerning financial engineering research, practices or regulations. Real Options, Ambiguity, Risk and Insurance, comprises 12 chapters and is divided into three parts. In Part I, five chapters deal with real options analysis, which addresses the issue of investment decisions in complex, innovative or risky projects. Part II presents three chapters on ambiguity. The notion of ambiguity is one of the major breakthroughs in the expected utility theory; ambiguity arises as uncertainties cannot be precisely described in the probability space. Part III consists of four chapters devoted to risk and insurance, and covers mutual insurance for non-traded risks, downside risk management, and credit risk in fixed income markets. This volume will be useful to both graduate students and researchers in understanding relatively new areas in economics and finance, as well as challenging aspects of mathematics.

"Since 2004, the Tokyo Metropolitan University (TMU) has been conducting workshops that serve as a forum for academic researchers and practitioners to exchange ideas and developments in different fields of finance. This book is based on papers presented at the 2014 workshop held in Tokyo, on 6-7 November, 2014. The chapters address state-of-the-art techniques in mathematical finance and financial engineering. The authors share ideas and information on new methods and up-to-date results of their research in these fields. This book is a must-read for researchers, practitioners, and graduate students in the fields of mathematical finance, quantitative finance and financial engineering."--Provided by publisher.

Since 2004, the Tokyo Metropolitan University (TMU) has been conducting workshops that serve as a forum for academic researchers and practitioners to exchange ideas and developments in different fields of finance. This book is based on papers presented at the 2014 workshop held in Tokyo, on 6–7 November, 2014. The chapters address state-of-the-art techniques in mathematical finance and financial engineering. The authors share ideas and information on new methods and up-to-date results of their research in these fields. This book is a must-read for researchers, practitioners, and graduate students in the fields of mathematical finance, quantitative finance and financial engineering. Contents: Moment Properties of Probability Distributions Used in Stochastic Financial Models (J Stoyanov)An Equilibrium Approach to Indifference Pricing with Model Uncertainty (M H A Davis and D Yoshikawa)Volume Imbalance and Market Making (Á Cartea, R. Donnelly and S Jaimungal)Optimal Short-Covering with Regime Switching (T K. Chung)Effects of Reversibility on Investment Timing and Quantity Under Asymmetric Information (X Cui and T. Shibata)Quadratic Gaussian Joint Pricing Model for Stocks and Bonds: Theory and Empirical Analysis (K Kikuchi)Option Pricing with Ambiguous Correlation and Fast Mean-reverting Volatilities (M H Leung and H Y Wong)Callable Stock Loans (C C Siu, S C P Yam and W Zhou)Cash Management and Control Band Policies for Spectrally One-sided Lévy Processes (K Yamazaki)A Second-order Monotone Modification of the Sharpe Ratio (M Zhitlukhin) Readership: Graduate students, researchers and practitioners of financial engineering and mathematical finance. Key Features:Contains cutting-edge research in financial engineeringServes as a bridge between academic researchers and practitionersKeywords:Financial Engineering;Mathematical Finance;Money & Banking;Risk Management;Real Option;Corporate Finance;Computational Finance

This volume is devoted to original research results and survey articles reviewing recent developments in reduction for stochastic PDEs with multiscale as well as application to science and technology, and to present some future research direction. This volume includes a dozen chapters by leading experts in the area, with a broad audience in mind. It should be accessible to graduate students, junior researchers and other professionals who are interested in the subject. We also take this opportunity to celebrate the contributions of Professor Anthony J Roberts, an internationally leading figure on the occasion of his 60th years birthday in 2017.

This is the first book to systematically present control theory for stochastic distributed parameter systems, a comparatively new branch of mathematical control theory. The new phenomena and difficulties arising in the study of controllability and optimal control problems for this type of system are explained in detail. Interestingly enough, one has to develop new mathematical tools to solve some problems in this field, such as the global Carleman estimate for stochastic partial differential equations and the stochastic transposition method for backward stochastic evolution equations. In a certain sense, the stochastic distributed parameter control system is the most general control system in the context of classical physics. Accordingly, studying this field may also yield valuable insights into quantum control systems. A basic grasp of functional analysis, partial differential equations, and control theory for deterministic systems is the only prerequisite for reading this book.