Techniques for Verifying the Accuracy of Risk Measurement Models
Author: Paul H. Kupiec
Publisher:
Published: 1995
Total Pages: 72
ISBN-13:
DOWNLOAD EBOOKRead and Download eBook Full
Author: Paul H. Kupiec
Publisher:
Published: 1995
Total Pages: 72
ISBN-13:
DOWNLOAD EBOOKAuthor: Paul Kupiec (Economiste.)
Publisher:
Published: 1995
Total Pages: 29
ISBN-13:
DOWNLOAD EBOOKAuthor: Paul Kupiec
Publisher:
Published: 1998
Total Pages:
ISBN-13:
DOWNLOAD EBOOKRisk exposures are typically quantified in terms of a quot;Value at Riskquot; (VaR) estimate. A VaR estimate corresponds to a specific critical value of a portfolio's potential one-day profit and loss probability distribution. Given their function both as internal risk management tools and as potential regulatory measures of risk exposure, it is important to quantify the accuracy of an institution's VaR estimates. This study shows that the formal statistical procedures that would typically be used in performance-based VaR verification tests require large samples to produce a reliable assessment of a model's accuracy in predicting the size and likelihood of very low probability events. Verification test statistics based on historical trading profits and losses have very poor power in small samples, so it does not appear possible for a bank or its supervisor to verify the accuracy of a VaR estimate unless many years of performance data are available. Historical simulation-based verification test statistics also require long samples to generate accurate results: Estimates of 0.01 critical values exhibit substantial errors even in samples as large as ten years of daily data.
Author: Paul H. Kupiec
Publisher:
Published: 1995
Total Pages: 29
ISBN-13:
DOWNLOAD EBOOKAuthor: David Lynch
Publisher: Cambridge University Press
Published: 2022-12-31
Total Pages: 489
ISBN-13: 1108756484
DOWNLOAD EBOOKFinancial models are an inescapable feature of modern financial markets. Yet it was over reliance on these models and the failure to test them properly that is now widely recognized as one of the main causes of the financial crisis of 2007–2011. Since this crisis, there has been an increase in the amount of scrutiny and testing applied to such models, and validation has become an essential part of model risk management at financial institutions. The book covers all of the major risk areas that a financial institution is exposed to and uses models for, including market risk, interest rate risk, retail credit risk, wholesale credit risk, compliance risk, and investment management. The book discusses current practices and pitfalls that model risk users need to be aware of and identifies areas where validation can be advanced in the future. This provides the first unified framework for validating risk management models.
Author: George Anastassiou
Publisher: CRC Press
Published: 2019-06-03
Total Pages: 1056
ISBN-13: 9781420036053
DOWNLOAD EBOOKWorking computationally in applied mathematics is the very essence of dealing with real-world problems in science and engineering. Approximation theory-on the borderline between pure and applied mathematics- has always supplied some of the most innovative ideas, computational methods, and original approaches to many types of problems. The f
Author: Georg Bol
Publisher: Springer Science & Business Media
Published: 2012-12-06
Total Pages: 316
ISBN-13: 3642582729
DOWNLOAD EBOOKThis book comprises the articles of the 6th Econometric Workshop in Karlsruhe, Germany. In the first part approaches from traditional econometrics and innovative methods from machine learning such as neural nets are applied to financial issues. Neural Networks are successfully applied to different areas such as debtor analysis, forecasting and corporate finance. In the second part various aspects from Value-at-Risk are discussed. The proceedings describe the legal framework, review the basics and discuss new approaches such as shortfall measures and credit risk.
Author: Burcu Adıgüzel Mercangöz
Publisher: Springer Nature
Published: 2021-02-17
Total Pages: 465
ISBN-13: 3030541088
DOWNLOAD EBOOKThis handbook presents emerging research exploring the theoretical and practical aspects of econometric techniques for the financial sector and their applications in economics. By doing so, it offers invaluable tools for predicting and weighing the risks of multiple investments by incorporating data analysis. Throughout the book the authors address a broad range of topics such as predictive analysis, monetary policy, economic growth, systemic risk and investment behavior. This book is a must-read for researchers, scholars and practitioners in the field of economics who are interested in a better understanding of current research on the application of econometric methods to financial sector data.
Author: Graham Elliott
Publisher: Elsevier
Published: 2013-08-23
Total Pages: 667
ISBN-13: 0444627405
DOWNLOAD EBOOKThe highly prized ability to make financial plans with some certainty about the future comes from the core fields of economics. In recent years the availability of more data, analytical tools of greater precision, and ex post studies of business decisions have increased demand for information about economic forecasting. Volumes 2A and 2B, which follows Nobel laureate Clive Granger's Volume 1 (2006), concentrate on two major subjects. Volume 2A covers innovations in methodologies, specifically macroforecasting and forecasting financial variables. Volume 2B investigates commercial applications, with sections on forecasters' objectives and methodologies. Experts provide surveys of a large range of literature scattered across applied and theoretical statistics journals as well as econometrics and empirical economics journals. The Handbook of Economic Forecasting Volumes 2A and 2B provide a unique compilation of chapters giving a coherent overview of forecasting theory and applications in one place and with up-to-date accounts of all major conceptual issues. - Focuses on innovation in economic forecasting via industry applications - Presents coherent summaries of subjects in economic forecasting that stretch from methodologies to applications - Makes details about economic forecasting accessible to scholars in fields outside economics
Author: Van-Nam Huynh
Publisher: Springer
Published: 2015-12-28
Total Pages: 626
ISBN-13: 3319272845
DOWNLOAD EBOOKThis book is devoted to the analysis of causal inference which is one of the most difficult tasks in data analysis: when two phenomena are observed to be related, it is often difficult to decide whether one of them causally influences the other one, or whether these two phenomena have a common cause. This analysis is the main focus of this volume. To get a good understanding of the causal inference, it is important to have models of economic phenomena which are as accurate as possible. Because of this need, this volume also contains papers that use non-traditional economic models, such as fuzzy models and models obtained by using neural networks and data mining techniques. It also contains papers that apply different econometric models to analyze real-life economic dependencies.