Numerical Technologies ready to support requirement with NtInsight®, its flagship financial risk management software, which has been designed to calculate both VaR and expected shortfall (also known as CVaR or tail-VaR) with fat-tail awareness.
SINGAPORE – 4 MAY 2012 – Yesterday, the Basel Committee on Banking Supervision (BCBS) has published a consultative document which presents the Basel Committee’s initial proposals with regards to trading book capital requirement policies. A key element of the proposal is moving the quantitative risk metrics system from VaR to expected shortfall.
Key messages include:
- A more objective boundary between the trading book and the banking book that materially reduces the scope for regulatory arbitrage
- Moving from value-at-risk to expected shortfall, a risk measure that better captures “tail risk”
- Calibrating the revised framework in both the standardized and internal models-based approaches to a period of significant financial stress, consistent with the stressed value-at-risk approach adopted in Basel 2.5
- Comprehensively incorporating the risk of market illiquidity, again consistent with the direction taken in Basel 2.5
- Measures to reduce model risk in the internal models-based approach, including a more granular models approval process and constraints on diversification
- A revised standardised approach that is intended to be more risk-sensitive and act as a credible fallback to internal models
- Specific proposal about CVA overhaul has been deferred
The Basel Committee pointed that “a number of weaknesses have been identified with using value-at-risk (VaR) for determining regulatory capital requirements, including its inability to capture tail risk.” For this reason, the Committee considered using expected shortfall (ES). ES is a coherent risk measure and has already become common in the insurance industry, though not in the banking industry. Artzner et al. (1997) proposed the use of expected shortfall to alleviate the problems inherent in VaR. ES considers loss beyond the VaR level and is shown to be sub-additive, while VaR disregards loss beyond the percentile and is not sub-additive. However, although ES is mathematically superior to VaR, its practical implementation and large calculation requirements pose operational challenges to financial firms.
Numerical Technologies understands the advantages of measuring expected shortfall. Even 14 years ago, Numerical Technologies’ NtInsight® risk management software has already featured both VaR and ES calculations. NtInsight® uses massive parallel programming and applies faster codes when processing the transaction-level, 1 million Monte Carlo iterations needed to precisely capture the non-linear behavior of tail risk. It has been tested by major financial institutions in Japan where reporting expected shortfall is part of the regulatory requirement.
