Request Information
Implement Granularity Adjustment functionality to enhance the portfolioAnalytics library's credit portfolio modeling capabilities, addressing a gap in the current implementation for more accurate capital calculations.
Background
This feature request originates from community discussion on the Open Risk Commons forum where a user (@rdsk) inquired about GA implementation:
"How difficult would it be to add this to the Vasicek model? How does the GA change the loss distribution?"
The maintainer responded positively:
"Supporting with granularity adjustments is a good suggestion for some future development. There are now various methodologies for GA, some more natural to include in this library than others. Feel free to raise an issue as a feature request on github."
Problem statement
The current Vasicek base model in portfolioAnalytics assumes infinite granularity (infinitely many infinitesimally small exposures). In practice, credit portfolios have finite granularity, which means that the asymptotic approximation underestimates the true portfolio risk, Basel II/III frameworks require GA for Internal Ratings-Based (IRB) approaches, these were one of the things I spent a lot of time on while building www.crcreditum.com, accurate risk assessment is crucial for portfolio construction and economic capital allocation. This granularity adjustment corrects for this finite portfolio effect, particularly important for portfolios that are concentrated, we could say for small and medium-sized portfolios too, and the regulatory capital calculations under the IBR approach.
I want to propose that we implement implement the most widely-adopted GA methodologies:
Gordy's Single-Factor Model GA (Basel II approach)
Pykhtin-Dev Approach (2002)
Emmer-Tasche Approach (2005)
Integration Points would be the extention of the existing vasicek_base_ul function and addition of a new module: portfolioAnalytics/granularity.py.
These are the key works that dymistify this implementation, and i am quite familier with most of them.
Gordy, M. B. (2003). "A risk-factor model foundation for ratings-based bank capital rules"
Pykhtin, M., & Dev, A. (2002). "Credit risk in asset securitizations: An analytical model"
Emmer, S., & Tasche, D. (2005). "Calculating credit risk capital charges with the one-factor model"
Martin, R., & Wilde, T. (2002). "Unsystematic credit risk"
If this is worth an addition, I can draw up a roadmap, to implementing this.
Request Information
Implement Granularity Adjustment functionality to enhance the portfolioAnalytics library's credit portfolio modeling capabilities, addressing a gap in the current implementation for more accurate capital calculations.
Background
This feature request originates from community discussion on the Open Risk Commons forum where a user (@rdsk) inquired about GA implementation:
"How difficult would it be to add this to the Vasicek model? How does the GA change the loss distribution?"
The maintainer responded positively:
"Supporting with granularity adjustments is a good suggestion for some future development. There are now various methodologies for GA, some more natural to include in this library than others. Feel free to raise an issue as a feature request on github."
Problem statement
The current Vasicek base model in portfolioAnalytics assumes infinite granularity (infinitely many infinitesimally small exposures). In practice, credit portfolios have finite granularity, which means that the asymptotic approximation underestimates the true portfolio risk, Basel II/III frameworks require GA for Internal Ratings-Based (IRB) approaches, these were one of the things I spent a lot of time on while building www.crcreditum.com, accurate risk assessment is crucial for portfolio construction and economic capital allocation. This granularity adjustment corrects for this finite portfolio effect, particularly important for portfolios that are concentrated, we could say for small and medium-sized portfolios too, and the regulatory capital calculations under the IBR approach.
I want to propose that we implement implement the most widely-adopted GA methodologies:
Gordy's Single-Factor Model GA (Basel II approach)
Pykhtin-Dev Approach (2002)
Emmer-Tasche Approach (2005)
Integration Points would be the extention of the existing vasicek_base_ul function and addition of a new module: portfolioAnalytics/granularity.py.
These are the key works that dymistify this implementation, and i am quite familier with most of them.
Gordy, M. B. (2003). "A risk-factor model foundation for ratings-based bank capital rules"
Pykhtin, M., & Dev, A. (2002). "Credit risk in asset securitizations: An analytical model"
Emmer, S., & Tasche, D. (2005). "Calculating credit risk capital charges with the one-factor model"
Martin, R., & Wilde, T. (2002). "Unsystematic credit risk"
If this is worth an addition, I can draw up a roadmap, to implementing this.