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State of the art risk management techniques and practices—supplemented with interactive analytics All too often risk management books focus on risk measurement details without taking a broader view. Quantitative Risk Management delivers a synthesis of common sense management together with the cutting-edge tools of modern theory. This book presents a road map for tactical and strategic decision making designed to control risk and capitalize on opportunities. Most provocatively it challenges the conventional wisdom that "risk management" is or ever should be delegated to a separate department. Good managers have always known that managing risk is central to a financial firm and must be the responsibility of anyone who contributes to the profit of the firm. A guide to risk management for financial firms and managers in the post-crisis world, Quantitative Risk Management updates the techniques and tools used to measure and monitor risk. These are often mathematical and specialized, but the ideas are simple. The book starts with how we think about risk and uncertainty, then turns to a practical explanation of how risk is measured in today's complex financial markets. Covers everything from risk measures, probability, and regulatory issues to portfolio risk analytics and reporting Includes interactive graphs and computer code for portfolio risk and analytics Explains why tactical and strategic decisions must be made at every level of the firm and portfolio Providing the models, tools, and techniques firms need to build the best risk management practices, Quantitative Risk Management is an essential volume from an experienced manager and quantitative analyst.
State of the art risk management techniques and practices—supplemented with interactive analytics All too often risk management books focus on risk measurement details without taking a broader view. Quantitative Risk Management delivers a synthesis of common sense management together with the cutting-edge tools of modern theory. This book presents a road map for tactical and strategic decision making designed to control risk and capitalize on opportunities. Most provocatively it challenges the conventional wisdom that "risk management" is or ever should be delegated to a separate department. Good managers have always known that managing risk is central to a financial firm and must be the responsibility of anyone who contributes to the profit of the firm. A guide to risk management for financial firms and managers in the post-crisis world, Quantitative Risk Management updates the techniques and tools used to measure and monitor risk. These are often mathematical and specialized, but the ideas are simple. The book starts with how we think about risk and uncertainty, then turns to a practical explanation of how risk is measured in today's complex financial markets. Covers everything from risk measures, probability, and regulatory issues to portfolio risk analytics and reporting Includes interactive graphs and computer code for portfolio risk and analytics Explains why tactical and strategic decisions must be made at every level of the firm and portfolio Providing the models, tools, and techniques firms need to build the best risk management practices, Quantitative Risk Management is an essential volume from an experienced manager and quantitative analyst.
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.
Singh introduces valuable techniques for weighing and evaluating alternatives in decision making with a focus on risk analysis for identifying, quantifying, and mitigating risks associated with construction projects.
Developed over 20 years of teaching academic courses, the Handbook of Financial Risk Management can be divided into two main parts: risk management in the financial sector; and a discussion of the mathematical and statistical tools used in risk management. This comprehensive text offers readers the chance to develop a sound understanding of financial products and the mathematical models that drive them, exploring in detail where the risks are and how to manage them. Key Features: Written by an author with both theoretical and applied experience Ideal resource for students pursuing a master’s degree in finance who want to learn risk management Comprehensive coverage of the key topics in financial risk management Contains 114 exercises, with solutions provided online at www.crcpress.com/9781138501874
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.
STRATEGIC RISK MANAGEMENT Having just experienced a global pandemic that sent equity markets into a tailspin in March 2020, risk management is a more relevant topic than ever. It remains, however, an often poorly understood afterthought. Many portfolios are designed without any thought given to risk management before they are handed off to a dedicated—but separate—risk management team. In Strategic Risk Management: Designing Portfolios and Managing Risk, Campbell R. Harvey, Sandy Rattray, and Otto Van Hemert deliver a reimagining of the risk management process. The book envisions a marriage between the investment and risk processes, an approach that has proven successful at the world’s largest publicly listed hedge fund, Man Group. The authors provide readers with a new framework for portfolio design that includes defensive strategies, drawdown risk controls, volatility targeting, and actively timing rebalancing trades. You will learn about how the book’s new approach to risk management fared during the recent market drawdown at the height of the COVID-19 pandemic. You will also discover why the traditional risk weighting approach only works on certain classes of assets. The book shows you how to accurately evaluate the costs of defensive strategies and which ones offer the best and most cost-effective protection against market downturns. Finally, you will learn how to obtain a more balanced return stream by targeting volatility rather than a constant notional exposure and gain a deeper understanding of concepts like portfolio rebalancing. Perfect for people working in the asset management industry and financial policy makers, Strategic Risk Management: Designing Portfolios and Managing Risk will also earn a place in the libraries of economics and finance scholars, as well as casual readers who take an active approach to investing in their savings or pension assets. PRAISE FOR STRATEGIC RISK MANAGEMENT “Strategic Risk Management shows how to fully embed risk management into the portfolio management process as an equal partner to alpha. This should clearly be best practice for all asset managers.” —Jase Auby, Chief Investment Officer, the Teacher Retirement System of Texas “This book shows the power of integrating risk and investment management, rather than applying risk management as an afterthought to satisfy set limits. I was pleased to shepherd some of the key ideas in this book through the publication process at The Journal of Portfolio Management.” —Frank J. Fabozzi, Editor, The Journal of Portfolio Management “Financial markets today are quite different from those of the last century. Understanding leverage, correlations, tails, and other risk parameters of a portfolio is at least as important as work on signals and alpha. In that sense, bringing risk management from ‘control’ to ‘front office’ should be a priority for asset managers. This book explains how to do it.” —Marko Kolanovic, Chief Global Market Strategist, J.P. Morgan A powerful new approach to risk management in volatile and uncertain markets While the COVID-19 pandemic threw the importance of effective risk management into sharp relief, many investment firms hang on to a traditional and outdated model of risk management. Using siloed and independent portfolio management and risk monitoring teams, these firms miss out on the opportunities presented by integrated risk management. Strategic Risk Management: Designing Portfolios and Managing Risk delivers a fresh approach to risk management in difficult market conditions. The accomplished author team advocates for the amalgamation of portfolio design and risk monitoring teams, incorporating risk management into every aspect of portfolio design. The book provides a roadmap for the crucial aspects of portfolio design, including defensive strategies, drawdown risk controls, volatility targeting, and actively timing rebalancing trades. You will discover how these techniques helped the authors achieve remarkable results during the market drawdown in the midst of the COVID-19 pandemic and how they can help you protect your assets against unpredictable—but inevitable—future bear markets. Ideal for professionals in the asset management industry, Strategic Risk Management: Designing Portfolios and Managing Risk is a valuable resource for financial policy makers, economics and finance scholars, and anyone with even a passing interest in taking an active role in investing for their future.
Introduces risk assessment with key theories, proven methods, and state-of-the-art applications Risk Assessment: Theory, Methods, and Applications remains one of the few textbooks to address current risk analysis and risk assessment with an emphasis on the possibility of sudden, major accidents across various areas of practice—from machinery and manufacturing processes to nuclear power plants and transportation systems. Updated to align with ISO 31000 and other amended standards, this all-new 2nd Edition discusses the main ideas and techniques for assessing risk today. The book begins with an introduction of risk analysis, assessment, and management, and includes a new section on the history of risk analysis. It covers hazards and threats, how to measure and evaluate risk, and risk management. It also adds new sections on risk governance and risk-informed decision making; combining accident theories and criteria for evaluating data sources; and subjective probabilities. The risk assessment process is covered, as are how to establish context; planning and preparing; and identification, analysis, and evaluation of risk. Risk Assessment also offers new coverage of safe job analysis and semi-quantitative methods, and it discusses barrier management and HRA methods for offshore application. Finally, it looks at dynamic risk analysis, security and life-cycle use of risk. Serves as a practical and modern guide to the current applications of risk analysis and assessment, supports key standards, and supplements legislation related to risk analysis Updated and revised to align with ISO 31000 Risk Management and other new standards and includes new chapters on security, dynamic risk analysis, as well as life-cycle use of risk analysis Provides in-depth coverage on hazard identification, methodologically outlining the steps for use of checklists, conducting preliminary hazard analysis, and job safety analysis Presents new coverage on the history of risk analysis, criteria for evaluating data sources, risk-informed decision making, subjective probabilities, semi-quantitative methods, and barrier management Contains more applications and examples, new and revised problems throughout, and detailed appendices that outline key terms and acronyms Supplemented with a book companion website containing Solutions to problems, presentation material and an Instructor Manual Risk Assessment: Theory, Methods, and Applications, Second Edition is ideal for courses on risk analysis/risk assessment and systems engineering at the upper-undergraduate and graduate levels. It is also an excellent reference and resource for engineers, researchers, consultants, and practitioners who carry out risk assessment techniques in their everyday work.
The quantitative modeling of complex systems of interacting risks is a fairly recent development in the financial and insurance industries. Over the past decades, there has been tremendous innovation and development in the actuarial field. In addition to undertaking mortality and longevity risks in traditional life and annuity products, insurers face unprecedented financial risks since the introduction of equity-linking insurance in 1960s. As the industry moves into the new territory of managing many intertwined financial and insurance risks, non-traditional problems and challenges arise, presenting great opportunities for technology development. Today's computational power and technology make it possible for the life insurance industry to develop highly sophisticated models, which were impossible just a decade ago. Nonetheless, as more industrial practices and regulations move towards dependence on stochastic models, the demand for computational power continues to grow. While the industry continues to rely heavily on hardware innovations, trying to make brute force methods faster and more palatable, we are approaching a crossroads about how to proceed. An Introduction to Computational Risk Management of Equity-Linked Insurance provides a resource for students and entry-level professionals to understand the fundamentals of industrial modeling practice, but also to give a glimpse of software methodologies for modeling and computational efficiency. Features Provides a comprehensive and self-contained introduction to quantitative risk management of equity-linked insurance with exercises and programming samples Includes a collection of mathematical formulations of risk management problems presenting opportunities and challenges to applied mathematicians Summarizes state-of-arts computational techniques for risk management professionals Bridges the gap between the latest developments in finance and actuarial literature and the practice of risk management for investment-combined life insurance Gives a comprehensive review of both Monte Carlo simulation methods and non-simulation numerical methods Runhuan Feng is an Associate Professor of Mathematics and the Director of Actuarial Science at the University of Illinois at Urbana-Champaign. He is a Fellow of the Society of Actuaries and a Chartered Enterprise Risk Analyst. He is a Helen Corley Petit Professorial Scholar and the State Farm Companies Foundation Scholar in Actuarial Science. Runhuan received a Ph.D. degree in Actuarial Science from the University of Waterloo, Canada. Prior to joining Illinois, he held a tenure-track position at the University of Wisconsin-Milwaukee, where he was named a Research Fellow. Runhuan received numerous grants and research contracts from the Actuarial Foundation and the Society of Actuaries in the past. He has published a series of papers on top-tier actuarial and applied probability journals on stochastic analytic approaches in risk theory and quantitative risk management of equity-linked insurance. Over the recent years, he has dedicated his efforts to developing computational methods for managing market innovations in areas of investment combined insurance and retirement planning.