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In its October 2013’s consultative paper for a revised market risk framework (FRTB), and subsequent versions published thereafter, the Basel Committee suggests that non-securitization credit positions in the trading book be subject to a separate Default Risk Charge (DRC, formally Incremental Default Risk charge or IDR). This evolution is an attempt to overcome practical challenges raised by the current Basel 2.5 Incremental Risk Charge (IRC). Banks using the internal model approach would no longer have the choice of using either a single-factor or a multi-factor default risk model but instead, market risk rules would require the use of a two-factor simulation model and a 99.9%-VaR capital charge. In this article, we analyze the theoretical foundations of these proposals, particularly the link with the one-factor model used for the banking book and with a general J-factor setting. We thoroughly investigate the practical implications of the two-factor and the correlation calibration constraints through numerical applications. We introduce the Hoeffding decomposition of the aggregate unconditional loss to provide a systematic-idiosyncratic representation. Impacts of a J-factor correlation structure on risk measures and risk contributions are studied for long-only and long-short credit-sensitive portfolios.

We introduce a novel multilevel factor model that allows for the presence of global and pervasive factors, local factors and semi-pervasive factors, and that captures common features across subsets of the variables of interest. We develop a model estimation procedure and provide a simulation experiment addressing the consistency of our proposal. We complete the analyses by showing how our multilevel model might explain on the commonality across CDS premiums at the global level. In this respect, we cluster countries by either the Debt/GDP ratio or by sovereign ratings. We show that multilevel models are easier to interpret compared with factor models based on principal component analysis. Finally, we experiment how the multilevel model might allow the recovery of the risk contribution due to the latent factors within a basket of country CDS We introduce a novel multilevel factor model that allows for the presence of global and pervasive factors, local factors and semi-pervasive factors, and that captures common features across subsets of the variables of interest. We develop a model estimation procedure and provide a simulation experiment addressing the consistency of our proposal. We complete the analyses by showing how our multilevel model might explain on the commonality across CDS premiums at the global level. In this respect, we cluster countries by either the Debt/GDP ratio or by sovereign ratings. We show that multilevel models are easier to interpret compared with factor models based on principal component analysis. Finally, we experiment how the multilevel model might allow the recovery of the risk contribution due to the latent factors within a basket of country CDS.

We present a framework focused on the interdependence of high-dimensional tail events. This framework allows us to analyze and quantify tail interdependence at different levels of extremity, decompose it into systemic and residual part and to measure the contribution of a constituent to the interdependence of a system. In particular, tail interdependence can capture simultaneous distress of the constituents of a (financial or economic) system and measure its systemic risk. We investigate systemic distress in several financial datasets confirming some known stylized facts and discovering some new findings. Further, we devise statistical tests of interdependence in the tails and outline some additional extensions.

Modied Value at Risk (VaR) is an estimator of VaR based on the Cornish-Fisher expansion. It is fast to compute and reliable for non-normal returns. In this paper, we introduce modified Expected Shortfall as a new analytical estimator for Expected Shortfall (ES), another popular measure of downside risk. We give all the necessary formulas for computing portfolio modified VaR and ES and for decomposing these risk measures into the contributions made by each of the portfolio holdings. This new methodology is shown to be very useful for analyzing the risk properties of portfolios of alternative investments. ispartof: DTEW - KBI_0730 pages:1-30 status: published