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Management - Risk Management - Value at Risk

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Directory

Introduction

FAQs
Implementation	The authors describe how to implement VaR, the risk measurement technique widely used in financial risk management. Pdf-file
Introduction to VaR	Short introduction: Definition, How can I compute VAR? What is the effect of VAR parameters? How can we convert VAR parameters? How can I use VAR?
Introduction to VaR  II

Articles and Scientific Papers

Algorithms for Optimization of Value-at-Risk	This paper suggests two new heuristic algorithms for optimization of Value-at- Risk (VaR). By definition, VaR is an estimate of the maximum portfolio loss during a standardized period with some confidence level. Pdf-file
An Improved Methodology for Measuring VaR	The purpose of this article is to describe a RiskMetrics VaR methodology that allows for a more realistic model of financial return tail distributions. Pdf-file
Analyzing Perceived Downside Risk: the Component Value-at-Risk Framework	We develop the ‘Component Value-at-Risk (VaR)’ framework for companies to identify downside risk as perceived by shareholders. This framework allows for decomposition into components attributable to the underlying risk factors. (pdf-file available for download)
Approximations	Approximations for the Value-at-Risk approach to risk-return analysis. Pdf-file
Basic Methodes and Implementation	The authors describe how to implement VaR. Mathematica is used to demonstrate the basic methods for calculation of VaR for a hypothetical portfolio of a stock and a foreign bond. Pdf-file
Comparative analyses ...	... of expected shortfall and value-at-risk under market stress. Pdf-file
Credit Risk Contributions	Credit Risk Contributions to Value-at-Risk and Expected Shortfall. Pdf-file
Credit Risk Optimization with Conditional Value-At-Risk Criterion	The model is based on the Conditional Value-at-Risk (CVaR) risk measure, the expected loss exceeding Value-at-Risk. CVaR is also known as Mean Excess, Mean Shortfall, or Tail VaR. Pdf-file 2000
Credit Value-at-Risk Constraints	Credit Value-at-Risk Constraints, Pension and Insurance Fund Capital Requirements, Credit Rationing and Monetary Policy. Pdf-file 2002
Dynamic Value-at-Risk	The purpose of this study is to describe dynamic Value-at-Risk and to estimated the advantages and disadvantages of using it in portfolio management.
Efficient Monte Carlo methods for value-at-risk	The calculation of value-at-risk (VAR) for large portfolios of complex derivative securities presents a tradeoff between speed and accuracy. The fastest methods rely on simplifying assumptions about changes in underlying risk factors and about how a portfolio’s value responds to these changes in the risk factors. pdf-file
Forecasting Economic and Financial Variables with Global VARs	This paper considers the problem of forecasting real and financial macroeconomic variables across a large number of countries in the global economy. Building on the forecast combination literature, the effects of model and estimation uncertainty on forecast outcomes are examined by pooling forecasts obtained from different GVAR models estimated over alternative sample periods. Given the size of the modeling problem, and the heterogeneity of economies considered — industrialised, emerging, and less developed countries — as well as the very real likelihood of possibly multiple structural breaks, averaging forecasts across both models and windows makes a significant difference. Indeed the double-averaged GVAR forecasts performed better than the benchmark competitors, especially for output, inflation and real equity prices. Abstract, full text available for download
Long-Term Value at Risk	This paper investigates the estimation of long-term VaR. It also suggests a simple approach to the estimation of long-term VaR that avoids problems associated with the square-root rule for extrapolating VaR, as well as those associated with attempts to extrapolate day-to-day volatility forecasts over longer horizons. pdf-file 2003
Optimization of Conditional Value-at-Risk	A new approach to optimizing or hedging a portfolio of  financial instruments to reduce risk is presented and tested on applications. It focuses on minimizing Conditional Value-at-Risk (CVaR) rather than minimizing Value-at-Risk (VaR), but portfolios with low CVaR necessarily have low VaR as well. pdf-file
Portfolio Optimization with Conditional Value-At-Risk Objective and Constraints	pdf-file 2001
Remarks on the value-at-risk and the conditional value-at-risk	The value-at-risk (VaR) and the conditional value-at-risk (CVaR) are two commonly used risk measures. We state some of their properties and make a comparison. Moreover, the structure of the portfolio optimization problem using the VaR and CVaR is studied. pdf-file
Sensitivity Analysis of Values at Risk	The aim of this paper is to analyze the sensitivity of Value at Risk (VaR) with respect to portfolio allocation. Pdf-file
Using Value-at-Risk to Control Risk Taking: How Wrong Can you Be?	We study a source of bias in value-at-risk estimates that has not previously been recognized. Because value-at-risk estimates are based on past data, a trader will often have a good understanding of the errors in the value-at-risk estimate, and it will be possible for her to choose portfolios for which she knows that the value-at-risk estimate is less than the “true” value at risk. pdf-file
Value At Risk and Maximum Loss Optimization	The risk measure \Value At Risk" (VAR) is presented from a new point of view and a general de nition of VAR is derived. Next, "Maximum Loss" (ML) is formulated as a mathematical optimization problem and its modelling is described. Pdf-file 1995
Value At Risk Models In Finance	The  main objective of this paper  is  to  survey and  evaluate the performance of the most popular  univariate VaR methodologies, paying particular attention to their underlying assumptions and to their logical flaws. Pdf-file 2001
Value at Risk: A methodology for Information Security Risk Assessment	This paper presents Value at Risk (VAR), a new methodology for Information Security Risk Assessment. VAR summarizes the worst loss due to a security breach over a target horizon, with a given level of confidence. Pdf-file
Value-at-Risk Based Risk Management	Optimal Policies and Asset Prices. Pdf-file
Variance Reduction Techniques for Estimating Value-at-Risk	This paper describes, analyzes and evaluates an algorithm for estimating portfolio loss probabilities using Monte Carlo simulation. Pdf-file

Econometric Modeling of Value at Risk
by Timotheos Angelidis, Stavros Degiannakis
This book provides a selective survey of the risk management techniques that have been applied and discusses potential improvements in estimating, evaluating and adjusting Value-at-Risk and Expected Shortfall.

Value at Risk: The New Benchmark for Managing Financial Risk
by Philippe Jorion
To accommodate sweeping global economic changes, the risk management field has evolved substantially since the first edition of Value at Risk, making this revised edition a must. Updates include a new chapter on liquidity risk, information on the latest risk instruments and the expanded derivatives market, recent developments in Monte Carlo methods, and more. Value at Risk, Second Edition, will help professional risk managers understand, and operate within, today’s dynamic new risk environment.

Value-at-Risk: Theory and Practice
by Glyn Holton
Value-at-risk (VaR) is a measure of market risk that has been widely adopted since the mid-1990s for use on trading floors. This is the first advanced book published on VaR. It describes how to design, implement, and use scalable production VaR measures on actual trading floors. It takes readers from the basics of VaR to the most advanced techniques, many of which have never been published in book form.
Practical, detailed examples are drawn from markets around the world, including: Euro deposits, Pacific Basin equities, physical coffees, and North American natural gas.

Mastering Value at Risk: A Step-by-Step Guide to Understanding and Applying VAR
by Cormac Butler
This book provides an objective view of VAR, analyzing its pitfalls as well as its benefits.