In The Bible of Options Strategies, Second Edition, legendary options trader Guy Cohen systematically presents today's most effective strategies for trading options: how and why they work, when they're appropriate and inappropriate, and how to use each one responsibly and with confidence. Updated throughout, this edition contains new chapters assessing the current options landscape, discussing margin collateral issues, and introducing Cohen's exceptionally valuable OVI indicators. The Bible of Options Strategies, Second Edition is practical from start to finish: modular, easy to navigate, and thoroughly cross-referenced, so you can find what you need fast, and act before your opportunity disappears. Cohen systematically covers every key area of options strategy: income strategies, volatility strategies, sideways market strategies, leveraged strategies, and synthetic strategies. Even the most complex techniques are explained with unsurpassed clarity - making them accessible to any trader with even modest options experience. More than an incredible value, this is the definitive reference to contemporary options trading: the one book you need by your side whenever you trade. For all options traders with at least some experience.

The focus of the present volume is stochastic optimization of dynamical systems in discrete time where - by concentrating on the role of information regarding optimization problems - it discusses the related discretization issues. There is a growing need to tackle uncertainty in applications of optimization. For example the massive introduction of renewable energies in power systems challenges traditional ways to manage them. This book lays out basic and advanced tools to handle and numerically solve such problems and thereby is building a bridge between Stochastic Programming and Stochastic Control. It is intended for graduates readers and scholars in optimization or stochastic control, as well as engineers with a background in applied mathematics.

The focus of the present volume is stochastic optimization of dynamical systems in discrete time where - by concentrating on the role of information regarding optimization problems - it discusses the related discretization issues. There is a growing need to tackle uncertainty in applications of optimization. For example the massive introduction of renewable energies in power systems challenges traditional ways to manage them. This book lays out basic and advanced tools to handle and numerically solve such problems and thereby is building a bridge between Stochastic Programming and Stochastic Control. It is intended for graduates readers and scholars in optimization or stochastic control, as well as engineers with a background in applied mathematics.

The conference, coorganized by INRIA and Ecole des Mines de Paris, focuses on Discrete Event Systems (DES) and is aimed at engineers, scientists and mathematicians working in the fields of Automatic Control, Operations Research and Statistics who are interested in the modelling, analysis and optimization of DES. Various methods such as Automata theory, Petri nets, etc. are proposed to describe and analyze such systems. Comparison of these different mathematical approaches and the global confrontation of theoretical approaches with applications in manufacturing, telecommunications, parallel computing, transportation, etc. are the goals of the conference.

Ce livre considere le traitement de problemes d'optimisation de grande taille. L'idee est d'eclater le probleme d'optimisation global en sous-problemes plus petits, donc plus faciles a resoudre, chacun impliquant l'un des sous-systemes (decomposition), mais sans renoncer a obtenir l'optimum global, ce qui necessite d'utiliser une procedure iterative (coordination). Ce sujet a fait l'objet de plusieurs livres publies dans les annees 70 dans le contexte de l'optimisation deterministe. Nous presentans ici les principes essentiels et methodes de decomposition-coordination au travers de situations typiques, puis nous proposons un cadre general qui permet de construire des algorithmes corrects et d'etudier leur convergence. Cette theorie est presentee aussi bien dans le contexte de l'optimisation deterministe que stochastique. Ce materiel a ete enseigne par les auteurs dans divers cours de 3eme cycle et egalement mis en oeuvre dans de nombreuses applications industrielles. Des exercices et problemes avec corriges illustrent le potentiel de cette approche. This book discusses large-scale optimization problems involving systems made up of interconnected subsystems. The main viewpoint is to break down the overall optimization problem into smaller, easier-to-solve subproblems, each involving one subsystem (decomposition), without sacrificing the objective of achieving the global optimum, which requires an iterative process (coordination). This topic emerged in the 70's in the context of deterministic optimization. The present book describes the main principles and methods of decomposition-coordination using typical situations, then proposes a general framework that makes it possible to construct well-behaved algorithms and to study their convergence. This theory is presented in the context of deterministic as well as stochastic optimization, and has been taught by the authors in graduate courses and implemented in numerous industrial applications. The book also provides exercises and problems with answers to illustrate the potential of this approach.