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Author: Mathieu Le Bellac
Publisher:
ISBN: 9789813142114
Category : Electronic books
Languages : en
Pages : 232
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Book Description
Author: Mathieu Le Bellac
Publisher:
ISBN: 9789813142114
Category : Electronic books
Languages : en
Pages : 232
Get Book Here
Book Description
Author: Mathieu Le Bellac
Publisher: World Scientific Publishing Company
ISBN: 981314212X
Category : Business & Economics
Languages : en
Pages : 232
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Book Description
Since 2007, the repeated financial crises around the world have brought to the headlines financial practices and models considered to fuel the economic instabilities. Deep Dive into Financial Models: Modeling Risk and Uncertainty comes handy in demystifying the underlying quantitative finance concepts. With a limited use of mathematical formalism, the book explains thoroughly the models, their hypotheses, principles and other building blocks. A particular care is given to model limitations and their misuse for investment strategies, asset pricing, or risk management. Its reader-friendly nature provides readers with a head start in quantitative finance.
Author: Anurag Singal
Publisher:
ISBN: 9781720144519
Category :
Languages : en
Pages : 115
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Book Description
To use a cliché, we live in a volatile uncertain complex and ambiguous (VUCA) world.Organizations simply cannot afford to try out new strategies in reality and correct mistakes, once they've occurred.The stakes are too high. Thus emerges the utility of this technique across functions like financial planning and risk management. Financial models help a business manager simulate the future and see the impact of their change, without risking costly setbacks of real world trials and errors.Mastering the art of financial modeling is imperative for those who want to enter the ultra-competitive world of corporate finance, investment banking, private equity, or equity research. Only those who excel (pun intended) in modeling early on are often the most successful long-term.The book will help readers dive deep into the vocabulary and the syntax, the art and science of financial modeling and valuation. Readers will be able to prepare/use existing models more competently, interpret the results and have greater comfort over the integrity and accuracy of the model's calculations.
Author: Terisa Roberts
Publisher: John Wiley & Sons
ISBN: 1119824931
Category : Business & Economics
Languages : en
Pages : 214
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Book Description
A wide-ranging overview of the use of machine learning and AI techniques in financial risk management, including practical advice for implementation Risk Modeling: Practical Applications of Artificial Intelligence, Machine Learning, and Deep Learning introduces readers to the use of innovative AI technologies for forecasting and evaluating financial risks. Providing up-to-date coverage of the practical application of current modelling techniques in risk management, this real-world guide also explores new opportunities and challenges associated with implementing machine learning and artificial intelligence (AI) into the risk management process. Authors Terisa Roberts and Stephen Tonna provide readers with a clear understanding about the strengths and weaknesses of machine learning and AI while explaining how they can be applied to both everyday risk management problems and to evaluate the financial impact of extreme events such as global pandemics and changes in climate. Throughout the text, the authors clarify misconceptions about the use of machine learning and AI techniques using clear explanations while offering step-by-step advice for implementing the technologies into an organization’s risk management model governance framework. This authoritative volume: Highlights the use of machine learning and AI in identifying procedures for avoiding or minimizing financial risk Discusses practical tools for assessing bias and interpretability of resultant models developed with machine learning algorithms and techniques Covers the basic principles and nuances of feature engineering and common machine learning algorithms Illustrates how risk modeling is incorporating machine learning and AI techniques to rapidly consume complex data and address current gaps in the end-to-end modelling lifecycle Explains how proprietary software and open-source languages can be combined to deliver the best of both worlds: for risk models and risk practitioners Risk Modeling: Practical Applications of Artificial Intelligence, Machine Learning, and Deep Learning is an invaluable guide for CEOs, CROs, CFOs, risk managers, business managers, and other professionals working in risk management.
Author: Massimo Morini
Publisher: John Wiley & Sons
ISBN: 0470977744
Category : Business & Economics
Languages : en
Pages : 452
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Book Description
A guide to the validation and risk management of quantitative models used for pricing and hedging Whereas the majority of quantitative finance books focus on mathematics and risk management books focus on regulatory aspects, this book addresses the elements missed by this literature--the risks of the models themselves. This book starts from regulatory issues, but translates them into practical suggestions to reduce the likelihood of model losses, basing model risk and validation on market experience and on a wide range of real-world examples, with a high level of detail and precise operative indications.
Author: Thomas S. Y. Ho
Publisher: Oxford University Press
ISBN: 0199923981
Category : Business & Economics
Languages : en
Pages : 762
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Book Description
The essential premise of this book is that theory and practice are equally important in describing financial modeling. In it the authors try to strike a balance in their discussions between theories that provide foundations for financial models and the institutional details that provide the context for applications of the models. The book presents the financial models of stock and bond options, exotic options, investment grade and high-yield bonds, convertible bonds, mortgage-backed securities, liabilities of financial institutions--the business model and the corporate model. It also describes the applications of the models to corporate finance. Furthermore, it relates the models to financial statements, risk management for an enterprise, and asset/liability management with illiquid instruments. The financial models are progressively presented from option pricing in the securities markets to firm valuation in corporate finance, following a format to emphasize the three aspects of a model: the set of assumptions, the model specification, and the model applications. Generally, financial modeling books segment the world of finance as "investments," "financial institutions," "corporate finance," and "securities analysis," and in so doing they rarely emphasize the relationships between the subjects. This unique book successfully ties the thought processes and applications of the financial models together and describes them as one process that provides business solutions. Created as a companion website to the book readers can visit www.thomasho.com to gain deeper understanding of the book's financial models. Interested readers can build and test the models described in the book using Excel, and they can submit their models to the site. Readers can also use the site's forum to discuss the models and can browse server based models to gain insights into the applications of the models. For those using the book in meetings or class settings the site provides Power Point descriptions of the chapters. Students can use available question banks on the chapters for studying.
Author: Dessislava A. Pachamanova
Publisher: John Wiley & Sons
ISBN: 0470882123
Category : Business & Economics
Languages : en
Pages : 786
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Book Description
An introduction to the theory and practice of financial simulation and optimization In recent years, there has been a notable increase in the use of simulation and optimization methods in the financial industry. Applications include portfolio allocation, risk management, pricing, and capital budgeting under uncertainty. This accessible guide provides an introduction to the simulation and optimization techniques most widely used in finance, while at the same time offering background on the financial concepts in these applications. In addition, it clarifies difficult concepts in traditional models of uncertainty in finance, and teaches you how to build models with software. It does this by reviewing current simulation and optimization methodology-along with available software-and proceeds with portfolio risk management, modeling of random processes, pricing of financial derivatives, and real options applications. Contains a unique combination of finance theory and rigorous mathematical modeling emphasizing a hands-on approach through implementation with software Highlights not only classical applications, but also more recent developments, such as pricing of mortgage-backed securities Includes models and code in both spreadsheet-based software (@RISK, Solver, Evolver, VBA) and mathematical modeling software (MATLAB) Filled with in-depth insights and practical advice, Simulation and Optimization Modeling in Finance offers essential guidance on some of the most important topics in financial management.
Author: Michael Rees
Publisher: John Wiley & Sons
ISBN: 1119995205
Category : Business & Economics
Languages : en
Pages : 304
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Book Description
Financial Modelling in Practice: A Concise Guide for Intermediate and Advanced Level is a practical, comprehensive and in-depth guide to financial modelling designed to cover the modelling issues that are relevant to facilitate the construction of robust and readily understandable models. Based on the authors extensive experience of building models in business and finance, and of training others how to do so this book starts with a review of Excel functions that are generally most relevant for building intermediate and advanced level models (such as Lookup functions, database and statistical functions and so on). It then discusses the principles involved in designing, structuring and building relevant, accurate and readily understandable models (including the use of sensitivity analysis techniques) before covering key application areas, such as the modelling of financial statements, of cash flow valuation, risk analysis, options and real options. Finally, the topic of financial modelling using VBA is treated. Practical examples are used throughout and model examples are included in the attached CD-ROM. Aimed at intermediate and advanced level modellers in Excel who wish to extend and consolidate their knowledge, this book is focused, practical, and application-driven, facilitating knowledge to build or audit a much wider range of financial models. Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.
Author: James R. Morris
Publisher: CRC Press
ISBN: 1420090550
Category : Business & Economics
Languages : en
Pages : 757
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Book Description
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 enables professionals and students to learn how to develop and use computer-based models for financial planning. Providing critical tools for the financial toolbox, this volume shows how to use these tools to build successful models. Placing a strong emphasis on the structure of models, the book focuses on developing models that are consistent with the theory of finance and, at the same time, are practical and usable. The authors introduce powerful tools that are imperative to the financial management of the operating business. These include interactive cash budgets and pro forma financial statements that balance even under the most extreme assumptions, valuation techniques, forecasting techniques that range from simple averages to time series methods, Monte Carlo simulation, linear programming, and optimization. The tools of financial modeling can be used to solve the problems of planning the firm’s investment and financing decisions. These include evaluating capital projects, planning the financing mix for new investments, capital budgeting under capital constraints, optimal capital structure, cash budgeting, working capital management, mergers and acquisitions, and constructing efficient security portfolios. While the primary emphasis is on models related to corporate financial management, the book also introduces readers to a variety of models related to security markets, stock and bond investments, portfolio management, and options. This authoritative book supplies broad-based coverage and free access to @Risk software for Monte Carlo simulation, making it an indispensible text for professionals and students in financial management. Please contact customer service for access to the software if your copy of the book does not contain this information.
Author: Sinem Derindere Köseoğlu
Publisher: Springer Nature
ISBN: 3031352912
Category : Business & Economics
Languages : en
Pages : 307
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Book Description
This book sheds new light on the most important contemporary and emerging startup valuation topics. Drawing on the first-hand professional experience of practitioners, professionals, and startup experts from various fields of finance, combined with a sound academic foundation, it offers a practical guide to startup valuation and presents applications, practical examples, and case studies of real startup ecosystems. The book discusses pressing questions, such as: Why are startups in California are higher valued than those in New York? Or why do startups based in London receive higher valuations than those in Paris, Berlin, or Milan, even when they are based in similarly-sized economies, share the same industries, and often even have the same investors? Answering these questions, the authors present key topics, such as hierarchical and segmented approaches to startup valuation, business plans, and sensitivity analysis, many methods such as venture capital valuation, first Chicago valuation, scorecard valuation, Dave Berkus valuation, risk factor summation valuation, and discounted cash flow valuation, in addition to business valuation by data envelopment analysis and real options analysis, as well as critical conceptual issues in the valuation such as expected returns of the venture capital and price versus value concepts, among others. The book will help angel investors, venture capitalists, institutional investors, crowd-based fractional investors, and investment fund professionals understand how to use basic and advanced analytics for a more precise valuation that helps them craft their long-term capital-raising strategy and keep their funding requests in perspective. It will also appeal to students and scholars of finance and business interested in a better understanding of startup valuation.
