Using the factor analysis of information risk (FAIR) methodology developed over ten years and adopted by corporations worldwide, Measuring and Managing Information Risk provides a proven and credible framework for understanding, measuring, and analyzing information risk of any size or complexity. Intended for organizations that need to either build a risk management program from the ground up or strengthen an existing one, this book provides a unique and fresh perspective on how to do a basic quantitative risk analysis. Covering such key areas as risk theory, risk calculation, scenario modeling, and communicating risk within the organization, Measuring and Managing Information Risk helps managers make better business decisions by understanding their organizational risk. - Uses factor analysis of information risk (FAIR) as a methodology for measuring and managing risk in any organization. - Carefully balances theory with practical applicability and relevant stories of successful implementation. - Includes examples from a wide variety of businesses and situations presented in an accessible writing style.

How can a company that has never turned a profit have a multibillion dollar valuation? Why do some start-ups attract large investments while others do not? Aswath Damodaran, finance professor and experienced investor, argues that the power of story drives corporate value, adding substance to numbers and persuading even cautious investors to take risks. In business, there are the storytellers who spin compelling narratives and the number-crunchers who construct meaningful models and accounts. Both are essential to success, but only by combining the two, Damodaran argues, can a business deliver and sustain value. Through a range of case studies, Narrative and Numbers describes how storytellers can better incorporate and narrate numbers and how number-crunchers can calculate more imaginative models that withstand scrutiny. Damodaran considers Uber's debut and how narrative is key to understanding different valuations. He investigates why Twitter and Facebook were valued in the billions of dollars at their public offerings, and why one (Twitter) has stagnated while the other (Facebook) has grown. Damodaran also looks at more established business models such as Apple and Amazon to demonstrate how a company's history can both enrich and constrain its narrative. And through Vale, a global Brazil-based mining company, he shows the influence of external narrative, and how country, commodity, and currency can shape a company's story. Narrative and Numbers reveals the benefits, challenges, and pitfalls of weaving narratives around numbers and how one can best test a story's plausibility.

Offering a fresh, transparent approach encompassing new material, this invigorating volume measures political risk - for instance the risk that foreign investment might face in any country. It also demonstrates how progress or regress made in good governance initiatives as conditionalities to aid can be assessed. Governments can monitor their own policy environment(s), and take remedial action if necessary. The methodology allows for measurement of previously un-quantified 'soft' factors that add to the risks foreign investors might face, demonstrating why these factors are of importance to both risk assertive and risk averse investors. Features include: - 103 contextualized, measurable risk factors and their 411 risk factor indicators. - Guidelines to using these factors in order to perform generic macro analyses, or micro, client/project/industry-specific analyses. - Explanation of the methodology with which to comprehensively measure the probability of risk occurring in any macro or micro investment climate.

Financial Risk Forecasting is a complete introduction to practical quantitative risk management, with a focus on market risk. Derived from the authors teaching notes and years spent training practitioners in risk management techniques, it brings together the three key disciplines of finance, statistics and modeling (programming), to provide a thorough grounding in risk management techniques. Written by renowned risk expert Jon Danielsson, the book begins with an introduction to financial markets and market prices, volatility clusters, fat tails and nonlinear dependence. It then goes on to present volatility forecasting with both univatiate and multivatiate methods, discussing the various methods used by industry, with a special focus on the GARCH family of models. The evaluation of the quality of forecasts is discussed in detail. Next, the main concepts in risk and models to forecast risk are discussed, especially volatility, value-at-risk and expected shortfall. The focus is both on risk in basic assets such as stocks and foreign exchange, but also calculations of risk in bonds and options, with analytical methods such as delta-normal VaR and duration-normal VaR and Monte Carlo simulation. The book then moves on to the evaluation of risk models with methods like backtesting, followed by a discussion on stress testing. The book concludes by focussing on the forecasting of risk in very large and uncommon events with extreme value theory and considering the underlying assumptions behind almost every risk model in practical use – that risk is exogenous – and what happens when those assumptions are violated. Every method presented brings together theoretical discussion and derivation of key equations and a discussion of issues in practical implementation. Each method is implemented in both MATLAB and R, two of the most commonly used mathematical programming languages for risk forecasting with which the reader can implement the models illustrated in the book. The book includes four appendices. The first introduces basic concepts in statistics and financial time series referred to throughout the book. The second and third introduce R and MATLAB, providing a discussion of the basic implementation of the software packages. And the final looks at the concept of maximum likelihood, especially issues in implementation and testing. The book is accompanied by a website - www.financialriskforecasting.com – which features downloadable code as used in the book.

A ground shaking exposé on the failure of popular cyber risk management methods How to Measure Anything in Cybersecurity Risk exposes the shortcomings of current "risk management" practices, and offers a series of improvement techniques that help you fill the holes and ramp up security. In his bestselling book How to Measure Anything, author Douglas W. Hubbard opened the business world's eyes to the critical need for better measurement. This book expands upon that premise and draws from The Failure of Risk Management to sound the alarm in the cybersecurity realm. Some of the field's premier risk management approaches actually create more risk than they mitigate, and questionable methods have been duplicated across industries and embedded in the products accepted as gospel. This book sheds light on these blatant risks, and provides alternate techniques that can help improve your current situation. You'll also learn which approaches are too risky to save, and are actually more damaging than a total lack of any security. Dangerous risk management methods abound; there is no industry more critically in need of solutions than cybersecurity. This book provides solutions where they exist, and advises when to change tracks entirely. Discover the shortcomings of cybersecurity's "best practices" Learn which risk management approaches actually create risk Improve your current practices with practical alterations Learn which methods are beyond saving, and worse than doing nothing Insightful and enlightening, this book will inspire a closer examination of your company's own risk management practices in the context of cybersecurity. The end goal is airtight data protection, so finding cracks in the vault is a positive thing—as long as you get there before the bad guys do. How to Measure Anything in Cybersecurity Risk is your guide to more robust protection through better quantitative processes, approaches, and techniques.

Investment Risk Management provides an overview of developments in risk management and a synthesis of research on the subject. The chapters examine ways to alter exposures through measuring and managing risk exposures and provide an understanding of the latest strategies and trends within risk management.