A one-stop reference pulling together leading published research and analysis about VaR and market risk. An invaluable summary for practitioners and researchers looking for an independent evaluation of VaR and insight into how and when it should be used.
An increasing number of institutions in both developed and developing markets are adopting quantitative risk models for both competitive and regulatory reasons. For market risk, such models are based on value-at-risk (VaR) techniques. VaR is commonly used to measure how much the market value of an asset or a portfolio of assets is likely to decrease over a certain time period.
As banks and financial institutions increasingly rely on VaR to measure the market risk of their asset portfolios, these companies need an ever larger number of employees with experience in such models. In many cases, staff with technical experience are promoted to market risk functions with minimal knowledge of the subject.
The VaR Reference pulls together leading published research and analysis about VaR and market risk, making this a one-stop reference for both practitioners and researchers. The eminent contributors present a broad spectrum of outlooks and discuss the pros and cons of the various methods for market risk modelling. This is an invaluable summary for practitioners looking for an independent evaluation of VaR and how and when it should be used.
This in-depth volume focuses on regulations, modelling, and methodologies. Key areas discussed include:
Essential reading for risk managers, traders, quants and financial engineers working in banks, investment firms, asset
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Jon Danielsson has a PhD in the economics of financial markets, and is currently a reader in finance at the London School of Economics. His research areas include financial risk, regulation of financial markets, market volatility, models of extreme market movements, and microstructure of foreign exchange markets. He has published his work in a range of academic and practitioners journals, and discussed his work in a number of universities, financial institutions and government agencies.
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