The Pricepoint RRE and CARS modules offer real-time bottom-up monitoring of automotive loan and mortgage collateral value in a rigorous time series filtering framework. The Pricepoint estimation engine quickly responds to movements in the underlying market and continues to deliver optimal linear out-of-sample projections even under severe stress. However, such tools are not designed to capture extreme tail events. This is a deliberate choice, as there is a trade-off between estimating the central tendency and the tail, and a system optimized to capture sudden shifts would by definition work less well in relatively balanced market conditions. So it is logical to address the task of monitoring potential crisis dynamics of each respective asset market in a different framework, and the most appropriate approach is by systematic stress testing.
Comprehensive stress tests have been a mandatory part of the regulatory regime since Basel II, and banks with sophisticated risk management are faced with the task of giving the concept of “downturn” a clear meaning in the context of LGD estimation. With the advent of Basel III, the importance of stress tests has only increased, and so have their practical implications for the operation of financial institutions, as stress test hurdles have been imposed by regulators on both sides of the Atlantic to dictate capital levels, as a condition of dividends and performance related payments, and as part of recovery and resolution planning.
The unique advantage of Invector Pricepoint with respect to stress testing asset-backed portfolios and determining downturn LGD, is that it provides a credible link between the two regimes through the asset portfolio co-variance structure. To take an example, an overall 10% to nominal real-estate prices is not a plausible stress scenario for mortgage portfolios, as different regions and locations will be hit very differently. Inferences regarding such patterns can be made from their historical downturn co-variances. Given the issues at stake in a strategic and regulatory perspective, the true implications of systemic swings for LGD can not be taken lightly.
Exceptionally large losses originate in systemic factors almost by definition, as they could otherwise be averted through modest amounts of diversification. This means that to understand the tail risk associated with a particular portfolio, one has to shed light on the relationship between its value on one hand, and the dynamics of the surrounding macro-financial system on the other. Now the macro-models most commonly used by academics and central bankers are prone to making unrealistic assumptions, that make many of them by definition incapable of accounting for systemic financial risk. Cases in point are the DSGE models almost invariably in use in central banks, that assume neutrality of money and banking, homogeneity of agents, perfect foresight and, obviously: no default. In fact, the “real” dynamics expressed in such models are only indirectly relevant to asset prices, and deviations from demographic trends in the markets for asset-backed loan collateral are much more immediately affected by nominal and financial variables, such as the flow of credit for residential real estate and exchange rates for personal vehicles.
The Invector approach to macro-economic stress testing permits a financial institution to explore the effect of a range of systemic financial scenarios on the value of its collateral portfolios, and distribute the effects across assets according to an empirical or appropriately stylised correlation structure. The results can be applied consistently to the whole portfolio, to specific sub-segments or asset by asset, taking into account more or less diversification and higher or lower initial deviation from trend by region.
The significant drivers and relevant scenarios will vary across assets and locations, but the interaction of significant household asset markets such as housing and personal vehicles with the financial system and the economy as a whole is an issue that credit institutions need to address. Invector Pricepoint provides a framework to consistently map this interaction, and this is a vital aid in containing risk and formulating a competitive commercial strategy through the cycle.