Engle demonstrates the role of correlations in financial decision making, and addresses the economic underpinnings and theoretical properties of correlations and their relation to other measures of dependence. He compares DCC with other correlation estimators such as historical correlation, exponential smoothing, and multivariate GARCH, and he presents a range of important applications of DCC. Engle presents the asymmetric model and illustrates it using a multicountry equity and bond return model. He introduces the new FACTOR DCC model that blends factor models with the DCC to produce a model with the best features of both, and illustrates it using an array of U.S. large-cap equities. Engle shows how overinvestment in collateralized debt obligations, or CDOs, lies at the heart of the subprime mortgage crisis--and how the correlation models in this book could have foreseen the risks. A technical chapter of econometric results also is included.
Based on the Econometric and Tinbergen Institutes Lectures, Anticipating Correlations puts powerful new forecasting tools into the hands of researchers, financial analysts, risk managers, derivative quants, and graduate students.
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.
Since the first edition of Enterprise Risk Management: From Incentives to Controls was published a decade ago, much has changed in the worlds of business and finance. That's why James Lam has returned with a new edition of this essential guide. Written to reflect today's dynamic market conditions, the Second Edition of Enterprise Risk Management: From Incentives to Controls clearly puts this discipline in perspective.
Engaging and informative, it skillfully examines both the art as well as the science of effective enterprise risk management practices. Along the way, it addresses the key concepts, processes, and tools underlying risk management, and lays out clear strategies to manage what is often a highly complex issue.Offers in-depth insights, practical advice, and real-world case studies that explore the various aspects of ERM Based on risk management expert James Lam's thirty years of experience in this field Discusses how a company should strive for balance between risk and return
Failure to properly manage risk continues to plague corporations around the world. Don't let it hurt your organization. Pick up the Second Edition of Enterprise Risk Management: From Incentives to Controls and learn how to meet the enterprise-wide risk management challenge head on, and succeed.
Despite enterprise risk management's relative newness as a recognized business discipline, the marketplace is replete with guides and references for ERM practitioners. Yet, until now, few case studies illustrating ERM in action have appeared in the literature. One reason for this is that, until recently, there were many disparate, even conflicting definitions of what, exactly ERM is and, more importantly, how organizations can use it to utmost advantage. With efforts underway, internationally, to mandate ERM and to standardize ERM standards and practices, the need has never been greater for an authoritative resource offering risk management professionals authoritative coverage of the full array of contemporary ERM issues and challenges. Written by two recognized international thought leaders in the field, ERM-Enterprise Risk Management provides that and much more.Packed with international cases studies illustrating ERM best practices applicable across all industry sectors and business models Explores contemporary issues, including quantitative and qualitative measures, as well as potential pitfalls and challenges facing today's enterprise risk managers Includes interviews with leading risk management theorists and practitioners, as well as risk managers from a variety of industries An indispensable working resource for risk management practitioners everywhere and a valuable reference for researchers, providing the latest empirical evidence and an exhaustive bibliography
Stephen Taylor provides a comprehensive introduction to the dynamic behavior of asset prices, relying on finance theory and statistical evidence. He uses stochastic processes to define mathematical models for price dynamics, but with less mathematics than in alternative texts. The key topics covered include random walk tests, trading rules, ARCH models, stochastic volatility models, high-frequency datasets, and the information that option prices imply about volatility and distributions.
Asset Price Dynamics, Volatility, and Prediction is ideal for students of economics, finance, and mathematics who are studying financial econometrics, and will enable researchers to identify and apply appropriate models and methods. It will likewise be a valuable resource for quantitative analysts, fund managers, risk managers, and investors who seek realistic expectations about future asset prices and the risks to which they are exposed.
Based on Sharpe's Princeton Lectures in Finance, Investors and Markets presents a method of analyzing asset prices that accounts for the real behavior of investors. Sharpe makes this technique accessible through a new, one-of-a-kind computer program (available for free on his Web site, at http://www.stanford.edu/~wfsharpe/apsim/index.html) that enables users to create virtual markets, setting the starting conditions and then allowing trading until equilibrium is reached and trading stops. Program users can then analyze the final portfolios and asset prices, see expected returns, and measure risk.
In addition to popularizing the most sophisticated form of asset-price analysis, Investors and Markets summarizes much of Sharpe's most important previous work and reflects a lifetime of thinking about investing by one of the leading minds in financial economics. Any serious investment professional will benefit from Sharpe's unique insights.
In addition to econometric essentials, Mostly Harmless Econometrics covers important new extensions--regression-discontinuity designs and quantile regression--as well as how to get standard errors right. Joshua Angrist and Jörn-Steffen Pischke explain why fancier econometric techniques are typically unnecessary and even dangerous. The applied econometric methods emphasized in this book are easy to use and relevant for many areas of contemporary social science.
Rebonato begins by presenting the conceptual foundations for the application of the LIBOR market model to the pricing of interest-rate derivatives. Next he treats in great detail the calibration of this model to market prices, asking how possible and advisable it is to enforce a simultaneous fitting to several market observables. He does so with an eye not only to mathematical feasibility but also to financial justification, while devoting special scrutiny to the implications of market incompleteness.
Much of the book concerns an original extension of the LIBOR market model, devised to account for implied volatility smiles. This is done by introducing a stochastic-volatility, displaced-diffusion version of the model. The emphasis again is on the financial justification and on the computational feasibility of the proposed solution to the smile problem. This book is must reading for quantitative researchers in financial houses, sophisticated practitioners in the derivatives area, and students of finance.