This book gives an overview of one of the most widespread Value at Risk Models in use in most of risk management departments across the financial industry. VaR calculates the worst expected loss over a given horizon at a given confidence level under normal market conditions. VaR estimates can be calculated for various types of risk: market, credit, operational, etc. I focused only on Market Risk. Market risk is the risk that the value of an investment will decrease due to moves in market factors such as prices, rates, volatilities and other relevant market parameters. In such a context, VaR provides a single number summarizing the organization’s exposure to market risk and the likelihood of an unfavorable move. There are mainly three groups of VaR: Analytical (also called Parametric), Historical Simulations, and Monte Carlo Simulations. Non Parametric: GARCH, EGARCH. Semi Parametric: CaVaR, Extreme Value Theory etc. Here I have used parametric and non parametric VaR models for NSE daily and intraday data.
This book gives an overview of evaluation of the most widespread Value at Risk (VaR)Models in use in most of risk management departments across the financial industry.Value at Risk (VaR) has become the standard measure that financial analysts use to quantify market risk. VaR is defined as the maximum potential change in value of a portfolio of financial instruments with a given probability over a certain horizon. VaR measures can have many applications, such as in risk management, to evaluate the performance of risk takers and for regulatory requirements, and hence it is very important to develop methodologies that provide accurate estimates.The main objective of this book is to survey the most popular univariate VaR methodologies, paying particular attention to their underlying assumptions. The great popularity that this instrument has achieved is essentially due to its conceptual simplicity: VaR reduces the (market) risk associated with any portfolio to just one number, the loss associated to a given probability. VaR can also be applied to governance of endowments, trusts, and pension plans. Essentially trustees adopt portfolio VaR metrics for the entire pooled account.
A risk measurement and management framework that takes model risk seriously Most financial risk models assume the future will look like the past, but effective risk management depends on identifying fundamental changes in the marketplace as they occur. Bayesian Risk Management details a more flexible approach to risk management, and provides tools to measure financial risk in a dynamic market environment. This book opens discussion about uncertainty in model parameters, model specifications, and model-driven forecasts in a way that standard statistical risk measurement does not. And unlike current machine learning-based methods, the framework presented here allows you to measure risk in a fully-Bayesian setting without losing the structure afforded by parametric risk and asset-pricing models. Recognize the assumptions embodied in classical statistics Quantify model risk along multiple dimensions without backtesting Model time series without assuming stationarity Estimate state-space time series models online with simulation methods Uncover uncertainty in workhorse risk and asset-pricing models Embed Bayesian thinking about risk within a complex organization Ignoring uncertainty in risk modeling creates an illusion of mastery and fosters erroneous decision-making. Firms who ignore the many dimensions of model risk measure too little risk, and end up taking on too much. Bayesian Risk Management provides a roadmap to better risk management through more circumspect measurement, with comprehensive treatment of model uncertainty.
Financial risk has become a focus of financial and nonfinancial firms, individuals, and policy makers. But the study of risk remains a relatively new discipline in finance and continues to be refined. The financial market crisis that began in 2007 has highlighted the challenges of managing financial risk. Now, in Financial Risk Management, author Allan Malz addresses the essential issues surrounding this discipline, sharing his extensive career experiences as a risk researcher, risk manager, and central banker. The book includes standard risk measurement models as well as alternative models that address options, structured credit risks, and the real-world complexities or risk modeling, and provides the institutional and historical background on financial innovation, liquidity, leverage, and financial crises that is crucial to practitioners and students of finance for understanding the world today. Financial Risk Management is equally suitable for firm risk managers, economists, and policy makers seeking grounding in the subject. This timely guide skillfully surveys the landscape of financial risk and the financial developments of recent decades that culminated in the crisis. The book provides a comprehensive overview of the different types of financial risk we face, as well as the techniques used to measure and manage them. Topics covered include: Market risk, from Value-at-Risk (VaR) to risk models for options Credit risk, from portfolio credit risk to structured credit products Model risk and validation Risk capital and stress testing Liquidity risk, leverage, systemic risk, and the forms they take Financial crises, historical and current, their causes and characteristics Financial regulation and its evolution in the wake of the global crisis And much more Combining the more model-oriented approach of risk management-as it has evolved over the past two decades-with an economist's approach to the same issues, Financial Risk Management is the essential guide to the subject for today's complex world.
Introduces a powerful new approach to financial risk modeling with proven strategies for its real-world applications The 2008 credit crisis did much to debunk the much touted powers of Value at Risk (VaR) as a risk metric. Unlike most authors on VaR who focus on what it can do, in this book the author looks at what it cannot. In clear, accessible prose, finance practitioners, Max Wong, describes the VaR measure and what it was meant to do, then explores its various failures in the real world of crisis risk management. More importantly, he lays out a revolutionary new method of measuring risks, Bubble Value at Risk, that is countercyclical and offers a well-tested buffer against market crashes. Describes Bubble VaR, a more macro-prudential risk measure proven to avoid the limitations of VaR and by providing a more accurate risk exposure estimation over market cycles Makes a strong case that analysts and risk managers need to unlearn our existing «science» of risk measurement and discover more robust approaches to calculating risk capital Illustrates every key concept or formula with an abundance of practical, numerical examples, most of them provided in interactive Excel spreadsheets Features numerous real-world applications, throughout, based on the author’s firsthand experience as a veteran financial risk analyst
Never before has risk management been so important. Now in its third edition, this seminal work by Joël Bessis has been comprehensively revised and updated to take into account the changing face of risk management. Fully restructured, featuring new material and discussions on new financial products, derivatives, Basel II, credit models based on time intensity models, implementing risk systems and intensity models of default, it also includes a section on Subprime that discusses the crisis mechanisms and makes numerous references throughout to the recent stressed financial conditions. The book postulates that risk management practices and techniques remain of major importance, if implemented in a sound economic way with proper governance. Risk Management in Banking, Third Edition considers all aspects of risk management emphasizing the need to understand conceptual and implementation issues of risk management and examining the latest techniques and practical issues, including: Asset-Liability Management Risk regulations and accounting standards Market risk models Credit risk models Dependencies modeling Credit portfolio models Capital Allocation Risk-adjusted performance Credit portfolio management Building on the considerable success of this classic work, the third edition is an indispensable text for MBA students, practitioners in banking and financial services, bank regulators and auditors alike.
Value at Risk (VaR) and conditional value at Risk (CVaR) are frequently used risk measures. Finding optimal portfolio using VaR or CVaR as a risk measure is computationally intensive especially when number of instruments and scenarios size is huge. This problem was analyzed and a computational efficient method, beating the industry's best methods, was proposed in this work. Parallel computing techniques were further applied to attain even higher computational efficiencies. Also models were built to find sensitivities in VaR and CVaR for different set of parameters like risk free interest rates on stocks, Market interest rates on bonds, volatilities in stocks and bonds and portfolio allocation weights. Illustrated ways to overcome limitations in finite difference methods to find sensitivities in VaR and CVaR. Finally an application of our work is presented using a portfolio of different types of options, bonds and stocks.
The long-awaited, comprehensive guide to practical credit risk modeling Credit Risk Analytics provides a targeted training guide for risk managers looking to efficiently build or validate in-house models for credit risk management. Combining theory with practice, this book walks you through the fundamentals of credit risk management and shows you how to implement these concepts using the SAS credit risk management program, with helpful code provided. Coverage includes data analysis and preprocessing, credit scoring; PD and LGD estimation and forecasting, low default portfolios, correlation modeling and estimation, validation, implementation of prudential regulation, stress testing of existing modeling concepts, and more, to provide a one-stop tutorial and reference for credit risk analytics. The companion website offers examples of both real and simulated credit portfolio data to help you more easily implement the concepts discussed, and the expert author team provides practical insight on this real-world intersection of finance, statistics, and analytics. SAS is the preferred software for credit risk modeling due to its functionality and ability to process large amounts of data. This book shows you how to exploit the capabilities of this high-powered package to create clean, accurate credit risk management models. Understand the general concepts of credit risk management Validate and stress-test existing models Access working examples based on both real and simulated data Learn useful code for implementing and validating models in SAS Despite the high demand for in-house models, there is little comprehensive training available; practitioners are left to comb through piece-meal resources, executive training courses, and consultancies to cobble together the information they need. This book ends the search by providing a comprehensive, focused resource backed by expert guidance. Credit Risk Analytics is the reference every risk manager needs to streamline the modeling process.
A classic book on credit risk management is updated to reflect the current economic crisis. Credit Risk Management In and Out of the Financial Crisis dissects the 2007-2008 credit crisis and provides solutions for professionals looking to better manage risk through modeling and new technology. This book is a complete update to Credit Risk Measurement: New Approaches to Value at Risk and Other Paradigms, reflecting events stemming from the recent credit crisis. Authors Anthony Saunders and Linda Allen address everything from the implications of new regulations to how the new rules will change everyday activity in the finance industry. They also provide techniques for modeling-credit scoring, structural, and reduced form models-while offering sound advice for stress testing credit risk models and when to accept or reject loans.
Practical tools and advice for managing financial risk, updated for a post-crisis world Advanced Financial Risk Management bridges the gap between the idealized assumptions used for risk valuation and the realities that must be reflected in management actions. It explains, in detailed yet easy-to-understand terms, the analytics of these issues from A to Z, and lays out a comprehensive strategy for risk management measurement, objectives, and hedging techniques that apply to all types of institutions. Written by experienced risk managers, the book covers everything from the basics of present value, forward rates, and interest rate compounding to the wide variety of alternative term structure models. Revised and updated with lessons from the 2007-2010 financial crisis, Advanced Financial Risk Management outlines a framework for fully integrated risk management. Credit risk, market risk, asset and liability management, and performance measurement have historically been thought of as separate disciplines, but recent developments in financial theory and computer science now allow these views of risk to be analyzed on a more integrated basis. The book presents a performance measurement approach that goes far beyond traditional capital allocation techniques to measure risk-adjusted shareholder value creation, and supplements this strategic view of integrated risk with step-by-step tools and techniques for constructing a risk management system that achieves these objectives. Practical tools for managing risk in the financial world Updated to include the most recent events that have influenced risk management Topics covered include the basics of present value, forward rates, and interest rate compounding; American vs. European fixed income options; default probability models; prepayment models; mortality models; and alternatives to the Vasicek model Comprehensive and in-depth, Advanced Financial Risk Management is an essential resource for anyone working in the financial field.
A classic book on credit risk management is updated to reflect the current economic crisis Credit Risk Management In and Out of the Financial Crisis dissects the 2007-2008 credit crisis and provides solutions for professionals looking to better manage risk through modeling and new technology. This book is a complete update to Credit Risk Measurement: New Approaches to Value at Risk and Other Paradigms, reflecting events stemming from the recent credit crisis. Authors Anthony Saunders and Linda Allen address everything from the implications of new regulations to how the new rules will change everyday activity in the finance industry. They also provide techniques for modeling-credit scoring, structural, and reduced form models-while offering sound advice for stress testing credit risk models and when to accept or reject loans. Breaks down the latest credit risk measurement and modeling techniques and simplifies many of the technical and analytical details surrounding them Concentrates on the underlying economics to objectively evaluate new models Includes new chapters on how to prevent another crisis from occurring Understanding credit risk measurement is now more important than ever. Credit Risk Management In and Out of the Financial Crisis will solidify your knowledge of this dynamic discipline.
An easy to implement, practical, and proven risk management methodology for project managers and decision makers Drawing from the author's work with several major and mega capital projects for Royal Dutch Shell, TransCanada Pipelines, TransAlta, Access Pipeline, MEG Energy, and SNC-Lavalin, Project Risk Management: Essential Methods for Project Teams and Decision Makers reveals how to implement a consistent application of risk methods, including probabilistic methods. It is based on proven training materials, models, and tools developed by the author to make risk management plans accessible and easily implemented. Written by an experienced risk management professional Reveals essential risk management methods for project teams and decision makers Packed with training materials, models, and tools for project management professionals Risk Management has been identified as one of the nine content areas for Project Management Professional (PMP®) certification. Yet, it remains an area that can get bogged down in the real world of project management. Practical and clearly written, Project Risk Management: Essential Methods for Project Teams and Decision Makers equips project managers and decision makers with a practical understanding of the basics of risk management as they apply to project management. (PMP and Project Management Professional are registered marks of the Project Management Institute, Inc.)
This book puts forward Value-at-Risk (VaR) models based on Monte Carlo Simulation (MCS) that are integrated with two volatility representations to estimate the market risk for the non-financial sectors traded on the first board of the Malaysian stock exchange which is now known as Bursa Malaysia. Quantified at selected parameters, the reliabilities of the VaR models are tested from three different perspectives; conservatism, accuracy and efficiency. This book provides some indications of the applicability of a suitable VaR model for the sectors involved besides confirming that data and computational choices affect risk measurement qualities.
A comprehensive overview of trading and risk management in the energy markets Energy Trading and Risk Management provides a comprehensive overview of global energy markets from one of the foremost authorities on energy derivatives and quantitative finance. With an approachable writing style, Iris Mack breaks down the three primary applications for energy derivatives markets – Risk Management, Speculation, and Investment Portfolio Diversification – in a way that hedge fund traders, consultants, and energy market participants can apply in their day to day trading activities. Moving from the fundamentals of energy markets through simple and complex derivatives trading, hedging strategies, and industry-specific case studies, Dr. Mack walks readers through energy trading and risk management concepts at an instructive pace, supporting her explanations with real-world examples, illustrations, charts, and precise definitions of important and often-misunderstood terms. From stochastic pricing models for exotic derivatives, to modern portfolio theory (MPT), energy portfolio management (EPM), to case studies dealing specifically with risk management challenges unique to wind and hydro-electric power, the bookguides readers through the complex world of energy trading and risk management to help investors, executives, and energy professionals ensure profitability and optimal risk mitigation in every market climate. Energy Trading and Risk Management is a great resource to help grapple with the very interesting but oftentimes complex issues that arise in energy trading and risk management.
Balanced, practical risk management for post – financial crisis institutions Fundamentals of Risk Management fills a critical gap left by existing risk management texts. Instead of focusing only on quantitative risk analysis or only on institutional risk management, this book takes a comprehensive approach. The disasters of the recent financial crisis taught us that managing risk is both an art and a science, and it is critical for practitioners to understand how individual risks are integrated at the enterprise level. This book is the only resource of its kind to introduce all of the key risk management concepts in a cohesive case study spanning each chapter. A hypothetical bank drawn from elements of several real world institutions serves as a backdrop for topics from credit risk and operational risk to understanding big-picture risk exposure. You will be able to see exactly how each rigorous concept is applied in actual risk management contexts. Fundamentals of Risk Management includes: Supplemental Excel-based Visual Basic (VBA) modules, so you can interact directly with risk models Clear explanations of the importance of risk management in preventing financial disasters Real world examples and lessons learned from past crises Risk policies, infrastructure, and activities that balance limited quantitative models This book provides the element of hands-on application necessary to put enterprise risk management into effective practice. The very best risk managers rely on a balanced approach that leverages every aspect of financial operations for an integrative risk management strategy. With Fundamentals of Risk Management, you can identify and control risk at an expert level.