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Measuring Market Risk with Value at Risk

Measuring Market Risk with Value at Risk
Author: Pietro Penza
Publisher: John Wiley & Sons
Total Pages: 324
Release: 2001
Genre: Business & Economics
ISBN: 9780471393139

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"This book, Measuring Market Risk with Value at Risk by Vipul Bansal and Pietro Penza, has three advantages over earlier works on the subject. First, it takes a decidedly global approach-an essential ingredient for any comprehensive work on market risk. Second, it ties the scientifically grounded, yet intuitively appealing, VaR measure to earlier, more idiosyncratic measures of market risk that are used in specific market environs (e.g., duration in fixed income). Finally, it encompasses all of the accepted approaches to calculating a VaR measure and presents them in a clearly explained fashion with supporting illustrations and completely worked-out examples." -from the Foreword by John F. Marshall, PhD, Principal, Marshall, Tucker & Associates, LLC "Measuring Market Risk with Value at Risk offers a much-needed intellectual bridge, a translation from the esoteric realm of mathematical finance to the domain of financial managers who seek guidance in applying developments from this important field of research as well as that of MBA-level graduate instruction. I believe the authors have done a commendable job of providing a carefully crafted, highly readable, and most useful work, and intend to recommend it to all those involved in business risk management applications." -Anthony F. Herbst, PhD, Professor of Finance and C.R. and D.S. Carter Chair, The University of Texas, El Paso and Founding editor of The Journal of Financial Engineering (1991-1998) "Finally there's a book that strikes a balance between rigor and application in the area of risk management in the banking industry. This innovative book is a MUST for both novices and professionals alike." -Robert P. Yuyuenyongwatana, PhD, Associate Professor of Finance, Cameron University "Measuring Market Risk with Value at Risk is one of the most complete discussions of this emerging topic in finance that I have seen. The authors develop a logical and rigorous framework for using VaR models, providing both historical references and analytical applications." -Kevin Wynne, PhD, Associate Professor of Finance, Lubin School of Business, Pace University


Evaluating Value at Risk Methodologies

Evaluating Value at Risk Methodologies
Author: Matt Pritsker
Publisher:
Total Pages:
Release: 1998
Genre:
ISBN:

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Recent research has shown that different methods of computing Value at Risk (VAR) generate widely varying results, suggesting the choice of VAR methods is very important. This paper examines six VAR methods, and compares their computational time requirements and their accuracy when the sole source of inaccuracy is errors in approximating nonlinearity. Simulations using portfolios of foreign exchange options show showed fairly wide variation in accuracy and unsurprisingly wide variation in computational time. When the computational time and the accuracy of the methods were examined together, four methods were superior to the others. The paper also presents a new method for using order statistics to create confidence intervals for the errors and errors as a percent of true value at risk for each VAR method. This makes it possible to easily interpret the implications of VAR errors for the size of shortfalls or surpluses in a firm's risk based capital.


Estimating the Accuracy of Value-at-Risk (VAR) in Measuring Risk in Equity Investment in India

Estimating the Accuracy of Value-at-Risk (VAR) in Measuring Risk in Equity Investment in India
Author: Vanita Tripathi
Publisher:
Total Pages: 31
Release: 2008
Genre:
ISBN:

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Over the past few years, the Value-at-Risk (VaR) has become a standard measure of market risk embraced by banks, trading firms, mutual funds and others, including even the non financial firms. But any risk measure is useful and reliable only insofar as it can be verified for its accuracy. This paper attempts to evaluate the accuracy of VaR in estimating the risk in equity investment in India. For this purpose we have used daily data for 30 securities comprising BSE-Sensex and two major stock indices- BSE Sensex and NSE Nifty for the period January 2006 to February 2007 and portfolio-normal method (parametric approach to VaR calculation) for calculation of VaR. The hypothesis regarding accuracy of VaR estimates has been tested using Chi-square test. The results show that VaR estimate does not accurately measure the risk in equity investment in India as VaR overestimates the loss in 24 securities out of 30 securities. It is only in case of 4 securities that the observed number of violations is exactly equal to the expected number. These results may be attributed to non-normal distribution of equity returns in Indian securities market as against the normally distributed returns assumed under portfolio-normal method. All the securities are showing excess kurtosis estimate, exhibiting the leptokurtic returns' distribution and also, out of 30 securities, 20 are showing negatively skewed returns and 10 are showing positively skewed returns. Moreover the assumption of past representing the future is also not validated in the present case in the context of stock volatility observed during the period. We have also observed that portfolio- normal method of VaR computation is a better risk measure for estimating portfolio risk as compared to risk on individual securities.


Report on Analysis of the 260-Day Value at Risk (VAR) of Portfolio of Shares

Report on Analysis of the 260-Day Value at Risk (VAR) of Portfolio of Shares
Author: Calvin Monroe
Publisher: GRIN Verlag
Total Pages: 19
Release: 2014-02-28
Genre: Business & Economics
ISBN: 365660536X

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Scientific Essay from the year 2012 in the subject Business economics - Investment and Finance, grade: B, King`s College London, language: English, abstract: For quite a long time now the main concern for investors as well as regulators of financial markets has been the risk of catastrophic market and the sufficiency of capital needed to counter such kind of risk when it occurs. Many institutions have undergone loses despite their gigantic nature and good forecasting and this has been associated with inappropriate forms of pricing and poor management together with the fraudulent cases, factors that have always brought the issue of managing risk and regulating these financial markets to the level of public policy as well as discussion. A basic tool that has been identified as being effective in the assessment of financial risk is the Value at Risk (VaR) process (Artzner, et al., 1997). The VaR has been figured out as being an amount that is lost on a given form of portfolio including a small probability in a certain fixed period of time counted in terms of days. VaR however poses a major challenge during its implementation and this has more to do with the specification of the kind of probability distribution having extreme returns that is made use of during the calculation of the estimates used in the VaR analysis (Mahoney, 1996; McNeil & Frey, 2000; Dowd, 2001). As has been noted, the nature of VaR estimation majorly does depend on the accurate predictions of some uncommon events or risks that are catastrophic. This is attributed to the fact that VaR is a calculation made from the lowest portfolio returns. For this reason, any form of calculation that is employed in the estimation of VaR must be able to encompass the tail events’ prediction and make this its primary goal (Chiang, et al., 2007; Engle, 2002; Engle & Kroner, 1995; Engle & Rothschild, 1990; Francis, et al., 2001). There have been statistical techniques as well as thumb rules that many researchers argue as having been very instrumental in the prediction and analysis of intra-day and in most cases day-to-day risk. These are however; not appropriate for the analysis of VaR. The predictions of VaR now fall under parametric predictions that encompass conditional volatilities and non-parametric prediction that incorporate the unconditional volatilities (Jorion, 2006; Jorion, 2007).


Evaluation of Value at Risk Models

Evaluation of Value at Risk Models
Author: P.A. Naidu
Publisher: LAP Lambert Academic Publishing
Total Pages: 140
Release: 2013
Genre:
ISBN: 9783659483769

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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.


Value at Risk, 3rd Ed.

Value at Risk, 3rd Ed.
Author: Philippe Jorion
Publisher: McGraw Hill Professional
Total Pages: 624
Release: 2006-11-09
Genre: Business & Economics
ISBN: 0071736921

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Since its original publication, Value at Risk has become the industry standard in risk management. Now in its Third Edition, this international bestseller addresses the fundamental changes in the field that have occurred across the globe in recent years. Philippe Jorion provides the most current information needed to understand and implement VAR-as well as manage newer dimensions of financial risk. Featured updates include: An increased emphasis on operational risk Using VAR for integrated risk management and to measure economic capital Applications of VAR to risk budgeting in investment management Discussion of new risk-management techniques, including extreme value theory, principal components, and copulas Extensive coverage of the recently finalized Basel II capital adequacy rules for commercial banks, integrated throughout the book A major new feature of the Third Edition is the addition of short questions and exercises at the end of each chapter, making it even easier to check progress. Detailed answers are posted on the companion web site www.pjorion.com/var/. The web site contains other materials, including additional questions that course instructors can assign to their students. Jorion leaves no stone unturned, addressing the building blocks of VAR from computing and backtesting models to forecasting risk and correlations. He outlines the use of VAR to measure and control risk for trading, for investment management, and for enterprise-wide risk management. He also points out key pitfalls to watch out for in risk-management systems. The value-at-risk approach continues to improve worldwide standards for managing numerous types of risk. Now more than ever, professionals can depend on Value at Risk for comprehensive, authoritative counsel on VAR, its application, and its results-and to keep ahead of the curve.


Structured Risk Assessment and Value-at-Risk

Structured Risk Assessment and Value-at-Risk
Author: Robert Brooks
Publisher:
Total Pages: 23
Release: 2003
Genre:
ISBN:

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An important question for corporate finance officers is whether risk management systems, such as Value at Risk (VaR), currently are producing accurate results. In contrast to previous research on assessing the accuracy of risk systems or VaR, which has focused on backtesting a large sample of historical observations, we provide tools for real-time assessment, using a time window that varies adaptively with the data. The objective is to quickly signal if the estimation process is systematically biased, subject to a specified rate of false detections. For example, if the volatility is systematically underestimated by 25 percent our procedure detects this in an average of 25 observations. Previous techniques have often backtested thousands of observations.We also discuss the trade-off between increasing detection power at the risk of detecting meaningless errors and suggest a parameter to specify the balance desired for a specific application.


An Introduction to Value-at-Risk

An Introduction to Value-at-Risk
Author: Moorad Choudhry
Publisher: John Wiley & Sons
Total Pages: 194
Release: 2007-01-11
Genre: Business & Economics
ISBN: 0470033770

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The value-at-risk measurement methodology is a widely-used tool in financial market risk management. The fourth edition of Professor Moorad Choudhry’s benchmark reference text An Introduction to Value-at-Risk offers an accessible and reader-friendly look at the concept of VaR and its different estimation methods, and is aimed specifically at newcomers to the market or those unfamiliar with modern risk management practices. The author capitalises on his experience in the financial markets to present this concise yet in-depth coverage of VaR, set in the context of risk management as a whole. Topics covered include: Defining value-at-risk Variance-covariance methodology Monte Carlo simulation Portfolio VaR Credit risk and credit VaR Topics are illustrated with Bloomberg screens, worked examples, exercises and case studies. Related issues such as statistics, volatility and correlation are also introduced as necessary background for students and practitioners. This is essential reading for all those who require an introduction to financial market risk management and value-at-risk.