This book provides a hands-on guide to how financial models are actually implemented and used in practice, on a daily basis, for pricing and risk-management purposes. It shows how to put these models into use in production while minimizing the cost of implementation and maximizing robustness and control. Addressing some of the most important and cutting-edge issues, it describes how to build the necessary models in order to risk manage all the costs involved in options fabrication within the world of equity derivatives and hybrids. This is achieved by extending classical models and improving them in order to account for complex features. The book is primarily aimed at market practitioners (traders, risk managers, risk control, top managers), as well as Masters students in Quantitative/Mathematical Finance. It will also be useful for instructors hoping to enrich their courses with practical examples. The prerequisites are basic stochastic calculus and a general knowledge of financial markets and financial derivatives.

The effect Lean Manufacturing programs have on profit and loss statements during the early months of their implementation often causes them to be viewed as failures. The length of time it will take traditional financial reports to reflect lean manufacturing improvements depends upon how poorly the operation was doing in terms of inventory managemen

Make informed business decisions with the beginner's guide to financial modeling using Microsoft Excel Financial Modeling in Excel For Dummies is your comprehensive guide to learning how to create informative, enlightening financial models today. Not a math whiz or an Excel power-user? No problem! All you need is a basic understanding of Excel to start building simple models with practical hands-on exercises and before you know it, you'll be modeling your way to optimized profits for your business in no time. Excel is powerful, user-friendly, and is most likely already installed on your computer—which is why it has so readily become the most popular financial modeling software. This book shows you how to harness Excel's capabilities to determine profitability, develop budgetary projections, model depreciation, project costs, value assets and more. You'll learn the fundamental best practices and know-how of financial modeling, and how to put them to work for your business and your clients. You'll learn the tools and techniques that bring insight out of the numbers, and make better business decisions based on quantitative evidence. You'll discover that financial modeling is an invaluable resource for your business, and you'll wonder why you've waited this long to learn how! Companies around the world use financial modeling for decision making, to steer strategy, and to develop solutions. This book walks you through the process with clear, expert guidance that assumes little prior knowledge. Learn the six crucial rules to follow when building a successful financial model Discover how to review and edit an inherited financial model and align it with your business and financial strategy Solve client problems, identify market projections, and develop business strategies based on scenario analysis Create valuable customized templates models that can become a source of competitive advantage From multinational corporations to the mom-and-pop corner store, there isn't a business around that wouldn't benefit from financial modeling. No need to buy expensive specialized software—the tools you need are right there in Excel. Financial Modeling in Excel For Dummies gets you up to speed quickly so you can start reaping the benefits today!

Complex-Valued Modeling in Economics and Finance outlines the theory, methodology, and techniques behind modeling economic processes using complex variables theory. The theory of complex variables functions is widely used in many scientific fields, since work with complex variables can appropriately describe different complex real-life processes. Many economic indicators and factors reflecting the properties of the same object can be represented in the form of complex variables. By describing the relationship between various indicators using the functions of these variables, new economic and financial models can be created which are often more accurate than the models of real variables. This book pays critical attention to complex variables production in stock market modeling, modeling illegal economy, time series forecasting, complex auto-aggressive models, and economic dynamics modeling. Very little has been published on this topic and its applications within the fields of economics and finance, and this volume appeals to graduate-level students studying economics, academic researchers in economics and finance, and economists.

A properly structured financial model can provide decision makers with a powerful planning tool that helps them identify the consequences of their decisions before they are put into practice. Introduction to Financial Models for Management and Planning, Second Edition enables professionals and students to learn how to develop and use computer-based models for financial planning. This volume provides critical tools for the financial toolbox, then shows how to use them tools to build successful models.

This innovative book employs the social studies of finance approach which aims to enhance the dialogue between finance and sociology by addressing the blind spots of economic and financial theories. In so doing, it challenges the accusations made towards financial models in the aftermath of the last economic crisis and argues that they cannot be condemned indiscriminately. Their influence on markets and society is not straightforward, but determined by the many ways in which models are created and then used. Ekaterina Svetlova analyses the various patterns of the application of models in asset management, risk management and financial engineering to demonstrate that their power is far more fragile than widespread criticism would indicate.

This textbook provides a comprehensive modeling, reformulation and optimization approach for solving production planning and supply chain planning problems, covering topics from a basic introduction to planning systems, mixed integer programming (MIP) models and algorithms through the advanced description of mathematical results in polyhedral combinatorics required to solve these problems. Based on twenty years worth of research in which the authors have played a significant role, the book addresses real life industrial production planning problems (involving complex production structures with multiple production stages) using MIP modeling and reformulation approach. The book provides an introduction to MIP modeling and to planning systems, a unique collection of reformulation results, and an easy to use problem-solving library. This approach is demonstrated through a series of real life case studies, exercises and detailed illustrations. Review by Jakub Marecek (Computer Journal) The emphasis put on mixed integer rounding and mixing sets, heuristics in-built in general purpose integer programming solvers, as well as on decompositions and heuristics using integer programming should be praised... There is no doubt that this volume offers the present best introduction to integer programming formulations of lotsizing problems, encountered in production planning. (2007)