Meaning
Financial exposures that lack sufficient historical data or liquidity to be captured by standard internal models require separate capital charges under banking regulations. A risk manager identifies non-modellable risk factors by testing the quality and frequency of the price observations available for an asset. These items are often found in niche markets or for complex products where trading is infrequent.
Capital Provision
Regulations require institutions to hold a conservative amount of funds to cover the potential losses from these specific risks. The charge for non-modellable risk factors is calculated using a stress scenario rather than a statistical distribution. This approach ensures that the bank is protected even when the normal models fail to provide an accurate estimate of the danger.
Data Scarcity
Gaps in the historical record prevent the use of standard volatility and correlation measures for these instruments. When price data for non-modellable risk factors is missing, the institution must use alternative methods to value the position for regulatory reporting. This difficulty in measurement leads to higher capital requirements to account for the uncertainty.
Regulatory Treatment
Oversight bodies perform regular reviews to determine which market variables must be excluded from the internal model approval process. Treatment of non-modellable risk factors is a key part of the Fundamental Review of the Trading Book standards. Banks are encouraged to improve their data collection and market participation to transition these factors into the modellable category over time.
Reducing the number of these factors can significantly lower the total capital a firm is required to maintain. This incentive drives investments in better technology and more transparent trading platforms.