I was reading about the regulatory consistency assessment program of Basel committee. The assessment program is conducted on three levels:
1: Ensuring the timely adoption of Basel III;
2: Ensuring regulatory consistency with Basel III; and
3: Ensuring consistency of risk-weighted asset (RWA) outcomes
For the third assessment committee conducted RWA analysis, separately for banking and trading book , for designed hypothetical portfolios. Many big global banks participated in this exercise. The hypothetical test portfolio exercise indicated that, using a hypothetical diversified portfolio consisting primarily of simple long and short positions, there can be a substantial difference between the bank reporting the lowest mRWAs (Market risk RWA) and the bank reporting the highest.
VaR , stressed VaR and IRC was calculated and reported for these portfolio. RWA for trading assets gets calculated from VaR and stressed VaR. As graphed in below figure there is huge variability in mRWA numbers for participated banks.
The X axis here shows the various portfolios, and the Y axis shows the VaR of those portfolios – which more or less linearly determines RWAs – calculated by different banks, normalized to 100%. Take portfolio 18, a credit portfolio. The different banks computed a VaR for this portfolio ranging from, say, 0.4x to 1.5x This portfolio was: long protection on Itraxx index. How much capital should you have to support this portfolio ? Banks have report RWA from this portfolio in range of 0.4x to 15.x. So actually it looks like a guess work as we can't say which bank's model is better than other.
Reasons behind this wide dispersion -
1) Time series data period that is used in historical simulation method. Banks that are using 4 years historical data tend to have higher var then that are using 3 years historical data
2) How 10 day holding period var is getting calculated. There are two method to calculate the 10 day var first is directly calculating 10 day var using 10 day returns or scaling 1 day var to 10 day by multiplying square root of 10.
3) Aggregation approach of positions and general and specific risk.
4)Valuation model ( Full valuation ,Partial revaluation or sensitivities approximation)
5) Risk factor granularity
Centralization of Calculation-
Author in his blog post suggested to have centralized VaR calculation approach. All banks will use the same approach and models. I do not agree on this, it will be like going back to Basel 1 standard approach. Internal methods have been institutionalized to give benefit to banks that can develop robust and good risk engines. From the blog of Streetsmart professor-
"We want to diversify model risk, not concentrate it. Centralized calculation concentrates it. I actually see an evolutionary benefit in the wide range of model risk weights. That represents a diverse ecosystem of entities with divergent views that is less vulnerable to a single shock. Yeah, that shock will crater some banks, but not all of them."
1: Ensuring the timely adoption of Basel III;
2: Ensuring regulatory consistency with Basel III; and
3: Ensuring consistency of risk-weighted asset (RWA) outcomes
For the third assessment committee conducted RWA analysis, separately for banking and trading book , for designed hypothetical portfolios. Many big global banks participated in this exercise. The hypothetical test portfolio exercise indicated that, using a hypothetical diversified portfolio consisting primarily of simple long and short positions, there can be a substantial difference between the bank reporting the lowest mRWAs (Market risk RWA) and the bank reporting the highest.
VaR , stressed VaR and IRC was calculated and reported for these portfolio. RWA for trading assets gets calculated from VaR and stressed VaR. As graphed in below figure there is huge variability in mRWA numbers for participated banks.
Reasons behind this wide dispersion -
1) Time series data period that is used in historical simulation method. Banks that are using 4 years historical data tend to have higher var then that are using 3 years historical data
2) How 10 day holding period var is getting calculated. There are two method to calculate the 10 day var first is directly calculating 10 day var using 10 day returns or scaling 1 day var to 10 day by multiplying square root of 10.
3) Aggregation approach of positions and general and specific risk.
4)Valuation model ( Full valuation ,Partial revaluation or sensitivities approximation)
5) Risk factor granularity
Centralization of Calculation-
Author in his blog post suggested to have centralized VaR calculation approach. All banks will use the same approach and models. I do not agree on this, it will be like going back to Basel 1 standard approach. Internal methods have been institutionalized to give benefit to banks that can develop robust and good risk engines. From the blog of Streetsmart professor-
"We want to diversify model risk, not concentrate it. Centralized calculation concentrates it. I actually see an evolutionary benefit in the wide range of model risk weights. That represents a diverse ecosystem of entities with divergent views that is less vulnerable to a single shock. Yeah, that shock will crater some banks, but not all of them."
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