The incremental risk charge (IRC) is a new regulatory requirement from the Basel Committee in response
to the recent financial crisis. Notably few models for IRC have been developed in the literature. This
page proposes a methodology consisting of two Monte Carlo simulations. The first Monte Carlo simulation
simulates default, migration, and concentration in an integrated way. Combining with full re-valuation,
the loss distribution at the first liquidity horizon for a subportfolio can be generated. The second
Monte Carlo simulation is the random draws based on the constant level of risk assumption. It convolutes
the copies of the single loss distribution to produce one year loss distribution. The aggregation of
different subportfolios with different liquidity horizons is addressed.
The Basel Committee on Banking Supervision (see Basel [2009 a]) released the new guidelines for
Incremental Risk Charge (IRC) that are part of the new rules developed in response to the financial
crisis and is a key part of a series of regulatory enhancements being rolled out by regulators.
IRC supplements existing Value-at-Risk (VaR) and captures the loss due to default and migration events
at a 99.9% confidence level over a one-year capital horizon. The liquidity of position is explicitly
modeled in IRC through liquidity horizon and constant level of risk
The constant level of risk assumption in IRC reflects the view that securities and derivatives held
in the trading book are generally more liquid than those in the banking book and may be rebalanced
more frequently than once a year (see Aimone [2018]). IRC should assume a constant level of risk
over a one-year capital horizon which may contain shorter liquidity horizons. This constant level
of risk assumption implies that a bank would rebalance, or rollover, its positions over the one-year
capital horizon in a manner that maintains the initial risk level, as indicated by the profile of
exposure by credit rating and concentration.
We present a methodology for calculating IRC. First, a Merton-type model is introduced for simulating
default and migration. The model is modified to incorporate concentration. The calibration is also
elaborated. Second, a simple approach to determine market data, including equity, in response to
default and credit migration is presented. Next, a methodology toward constant level of risk is
described. The details of applying the constant level of risk assumption and aggregating different
subportfolios are addressed. Finally, the empirical and numerical results are presented.