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Financial Risk Forecasting

Author: Jon Danielsson
Publisher: Wiley
ISBN: 9780470669433
Size: 42.55 MB
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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.

Quantitative Financial Risk Management

Author: Desheng Dash Wu
Publisher: Springer Science & Business Media
ISBN: 9783642193392
Size: 62.35 MB
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The bulk of this volume deals with the four main aspects of risk management: market risk, credit risk, risk management - in macro-economy as well as within companies. It presents a number of approaches and case studies directed at applying risk management to diverse business environments. Included are traditional market and credit risk management models such as the Black-Scholes Option Pricing Model, the Vasicek Model, Factor models, CAPM models, GARCH models, KMV models and credit scoring models.

Autokorrelationen In Der Historischen Simulation

Author: Noel Boka
Publisher: Springer-Verlag
ISBN: 3658211083
Size: 44.77 MB
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Ausgehend von der Definition und Vorstellung barwertiger Konzepte der Zinsrisikomessung führt Noel Boka durch die Problematik von Autokorrelationen in der historischen Simulation. Nach der Verknüpfung der grundlegenden statistischen Eigenschaften mit der praktischen Anwendung folgt eine umfassende empirische Analyse zu den verschiedenen Ausprägungen und Einflussfaktoren. So kann zusammengefasst werden, dass die Differenzenmethode eine ausreichende Prognosegüte gewährleistet. Für niveauunabhängige Verfahren kann hingegen ein Kausalzusammenhang aus geminderter Prognosegüte und Autokorrelationen festgestellt werden.

Quantifying Systemic Risk

Author: Joseph G. Haubrich
Publisher: University of Chicago Press
ISBN: 0226921964
Size: 75.26 MB
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In the aftermath of the recent financial crisis, the federal government has pursued significant regulatory reforms, including proposals to measure and monitor systemic risk. However, there is much debate about how this might be accomplished quantitatively and objectively—or whether this is even possible. A key issue is determining the appropriate trade-offs between risk and reward from a policy and social welfare perspective given the potential negative impact of crises. One of the first books to address the challenges of measuring statistical risk from a system-wide persepective, Quantifying Systemic Risk looks at the means of measuring systemic risk and explores alternative approaches. Among the topics discussed are the challenges of tying regulations to specific quantitative measures, the effects of learning and adaptation on the evolution of the market, and the distinction between the shocks that start a crisis and the mechanisms that enable it to grow.

Measuring Market Risk

Author: Kevin Dowd
Publisher: John Wiley & Sons
ISBN: 0470016515
Size: 71.22 MB
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Fully revised and restructured, Measuring Market Risk, Second Edition includes a new chapter on options risk management, as well as substantial new information on parametric risk, non-parametric measurements and liquidity risks, more practical information to help with specific calculations, and new examples including Q&A’s and case studies.

Uneconomic Economics And The Crisis Of The Model World

Author: M. Watson
Publisher: Springer
ISBN: 1137385499
Size: 16.28 MB
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What has gone wrong with economics? Economists now routinely devise highly sophisticated abstract models that score top marks for theoretical rigour but are clearly divorced from observable activities in the current economy. This creates an 'uneconomic economics', where models explain relationships in blackboard rather than real-life markets.

Handbook Of Economic Forecasting

Author: Graham Elliott
Publisher: Elsevier
ISBN: 0444513957
Size: 71.48 MB
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Research on forecasting methods has made important progress over recent years and these developments are brought together in the Handbook of Economic Forecasting. The handbook covers developments in how forecasts are constructed based on multivariate time-series models, dynamic factor models, nonlinear models and combination methods. The handbook also includes chapters on forecast evaluation, including evaluation of point forecasts and probability forecasts and contains chapters on survey forecasts and volatility forecasts. Areas of applications of forecasts covered in the handbook include economics, finance and marketing. Addresses economic forecasting methodology, forecasting models, forecasting with different data structures, and the applications of forecasting methods. Insights within this volume can be applied to economics, finance and marketing disciplines.