RiXtrema: When swans are grey: VaR as an early warning signal
Posted: 23 September 2010 | Source: RiXtrema
The market events of 2008 will be remembered as much for their extreme volatility as for a widespread failure of the risk management, which contributed to the near collapse of many firms thought to be among the leaders in that field. This paper identifies a key deficiency in the way that the historical data are currently utilised in the estimation of risk. This deficiency stems from the conception of the marketplace as an equilibrium-seeking and continuous system and it led to the financial firms’ unpreparedness for sudden market reversals. A different framework for risk estimation is proposed based on linking the risk modelling with the existing literature on financial instability. One possible application of the proposed method to the estimation of value-at-risk (VaR) is demonstrated, and empirical tests comparing it with the traditional methods are performed using S&P 500’s history from 1989 to 2010. The new measure, called the instability VaR, is shown to dominate all traditional methods of calculation.
Market events of 2008 will be remembered as much for their extreme volatility as for a widespread failure of the risk management, which contributed to near collapse of many firms, had various causes and went far beyond deficiencies in risk measurement techniques. Nevertheless, underestimation of risk played a real part and the obvious lesson of that disaster should be that the financial industry must look for significant improvements in the performance of risk estimates. This analysis proposes a fundamental change to the way that historical data are used in the estimation of risk. It will show how the accuracy of one common metric called value-at-risk (VaR) can be significantly improved with the application of this new method, which is boom-bust patterns and their relation to pricing of risk. While the paper will focus on VaR, the ideas presented here are general and can be applied to the estimation of any risk statistic.motivated by the idea of self-sustaining.