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Quantitative Risk Reporting
As the low Interest Rates environment persists and equity returns narrowing in European capital markets, private debt investment funds are gaining traction with institutional investors looking for higher domestic yields and mid-term duration.
Structuring, managing and distributing a debt fund come associated with its lot of unique challenges, legal, tax, risk, oversight, and of course regulatory and institutional reporting. From a risk measurement perspective, this goes beyond the traditional market Value-at-Risk approach to measure portfolio risk of liquid investment bond funds for instance. For such strategies, we believe focus should be made on the fair estimation of credit risk (and potential credit losses) in addition to the more traditional sensitivity based market risk. Appropriate risk measures could include Credit Risk analytics such as Credit Value-at-Risk or Expected Shortfall and a credit losses distribution over different mid and long term holding periods.
Despite a gradual loss of interest in the wake of the last financial crisis, copulas, when wielded with care, still prove to be well suited to reflect tail default events. Be it based on a mono-factorial or multi-factorial approach, copula based Credit VaR provide an in depth view of the risk of default and joint default in a loan portfolio. They allow for Monte Carlo simulations and the construction of a full distribution of estimated credit losses over different holding periods, for instance 6 or 12 months. Model parameters such as default intensities / probabilities, recovery rates and defaults correlations can be implied from market prices or estimated from historical realizations. Stress testing could be performed through parametric shocks on default probabilities or recovery rates for instance, or through the estimation of model parameters during historical stressed periods (e.g. 2007-2008, 2011, etc.).
Liquidity risk should not be overlooked as well, for which proximity with market participants is key to assess potential asset liquidity and appetite for a particular asset. Design of liquidity matrices based on number of recent transactions, number of broker quotes and quoted spreads, ranking of the debt instrument and size of the position held, are quite common in the industry. For investor liquidity analyses, please refer to our previous pulse (hyperlink to add).
No doubt debt funds will continue to increase in number and assets. Risk managers must follow this trend and embrace appropriate risk measurement and monitoring techniques.
Don’t hesitate to contact us should you wish to learn more about credit risk measurement for debt funds or our quantitative risk reporting services.