What is Wrong with Quantitative Standard d.?

Meera Sharma
2012 Social Science Research Network  
The purpose of this paper is to evaluate the quantitative standards laid down under the second Basel Accords for the implementation of internal market risk models by banks. The paper surveys available research to evaluate the standards. The standards don't prescribe a VaR method despite evidence that volatility of financial returns is conditional and financial returns are fat tailed. The requirement of a minimum historical period also runs contrary to the finding that volatility is time varying
more » ... ity is time varying and clustered resulting in banks being able to use weighting schemes conservatively only. The minimum horizon of ten days requires use of a scaling rule that is not accurate. The 99% confidence level requirement increases the inaccuracy when using a normal assumption on fat tailed data. The minimum updation period and minimum historical period requirements effectively smooth the market risk charge over and above the smoothing by the requirement of averaging VaR resulting in unresponsive market risk charges. The regulatory back testing framework is based on unconditional coverage and doesnot penalize clustered VaR exceptions. Basel Committee on Banking Supervision (2011) also reviews the available research on the quantitative standards. However, only three aspects are covered by them, namely (1) time horizon over which VaR is estimated; (2) the recognition of time-varying volatility in VaR risk factors; and (3) VaR backtesting. This paper discusses eight out of the eleven quantitative standards including these three. The revisions to the quantitative standard made under the Basel III provisions (Revisions to the Basel II Market Risk Framework, 2009) have also been incorporated in this paper. It is useful here to map the process of market risk charge generation because the final market risk capital charge is a combination of data inputs, models, assumptions and calculations. A bank has to make multiple choices resulting in a unique market risk generating model and every choice is constrained by the quantitative standards. Figure 1 maps the process and its inputs. Usually the process of market risk estimation starts with a volatility forecast. An exception to
doi:10.2139/ssrn.2045665 fatcat:gvi4j6dhpzgblhyc26oioba7uq