Each of the three methods of calculating value-at-risk has its pros and cons. Brian Shydlo of Sirius Solutions examines them
It has become standard to account for non-normality when estimating portfolio value-at-risk, but there are few methods available to calculate the risk contributions of each component in a non-normal portfolio. Brian Peterson and Kris Boudt present a method...
Given the large number of assumptions made in calculating a value-at-risk, how can we have confidence in the quality of the resulting calculation? Brett Humphreys looks at using backtesting to evaluate quality.
Brett Humphreys discusses the many decisions associated with the calculation of a Monte Carlo value-at-risk.
A delta-normal value-at-risk is one of the basic tools of risk management. Brett Humphreys discusses the assumptions associated with this calculation.
With increasing challenges to measure value-at-risk and meet high regulatory requirements, the focus has turned to back testing as a way of assuring models' adequacy. Carsten S Wehn proposes a new regime of back testing, combining state-of-the-art methodologies...
Correlation measures are major drivers of value-at-risk. Brett Humphreys and Eric Raleigh review assumptions associated with calculating correlation.
Banks reported a surge in the number of value-at-risk exceptions during the third quarter of last year following extreme turbulence in the financial markets. Are risk models breaking down? What are banks doing to fine-tune risk management practices and...
Risk Awards 2008
Rising defaults in the US subprime mortgage market, plunging prices in the credit sector and a sharp squeeze in liquidity all contributed to make the third quarter very difficult for banks. Risk compares the value-at-risk figures of the major banks in...
Risk Awards 2008
Risk management units alone cannot avoid the damage from periodic bouts of irrational exuberance. That responsibility lies with the chief executive, argues David Rowe
Investment banks reported increased numbers of high trading losses in the third quarter of this year, highlighting the volatility in the financial markets and casting doubt on their risk modelling.
A 'one distribution fits all' approach is not the best option for op risk models. Carsten Steinhoff and Rainer Baule explain why a tailor-made model is therefore vital to the accuracy of loss distribution models
Value-at-risk analysis has become a key measure of portfolio risk in recent years, but how can we calculate the contribution of some portfolio component? Eduardo Epperlein and Alan Smillie show how kernel estimators can be used to provide a fast, accurate...