The value of financial instruments within a portfolio or account is driven by a combination of three factors: market conditions, counterparty status, and the behavioural characteristics of the two aforementioned factors.
Current market prices and yields are defined based on factual analytics, however, their future characteristics are driven by expectations – or in other words by ‘fictional assumptions’. The quality of counterparties is defined by credit risk characteristics and is commonly expressed as ratings, again a factual measurement. However, ratings also reflect the willingness of the counterparty to fulfil contractual obligations – fictional assumptions.
This mix of facts and fictional expectations is included in credit spreads used in financial instruments and thus the portfolio valuation process. Finally, the market and counterparty behaviour, such as the recovery process, in case of default, or the funding liquidity for selling the financial contracts/instruments, also impacts the value of a portfolio. Behaviour is not always driven by the facts but in many cases by emotional characteristics. Such emotions under stress conditions could even go beyond the universe of reality; for instance the rational behaviour of the counterparties, investors or portfolio managers can change the value of instruments unexpectedly.
These three financial analysis elements, market risk factors, counterparty credit risk and behaviour, are correlated between themselves and reinforced by interactions among each other. Thus, the degrees of such correlations and interactions must be identified and considered in the valuation process of the financial instruments within a portfolio. Such complex process under the current stress conditions can be analysed on the counterparties’ systemic risk.
Systemic risk is where the failure of individual or a small number of counterparties can impact the majority of the other counterparties which are all linked to the instruments of the portfolio. This implication can range from the downgrade of a credit rating to a credit default event, which could result in a collapse of the entire value of a portfolio. As we all know, during the ccurrent eurozone crisis, the great majority of portfolios had significant losses mainly due to downgrading and not to default events. But what should we consider in systemic risk portfolio value analysis and where do market and behaviour characteristics play a role?
In systemic risk analysis the degree of correlations among the counterparties in regards to their creditability, expressed as ratings, must be identified. In such correlation analysis we need to identify whether and how an event of a counterparty’s downgrade or default will impact the other counterparties’ creditability status. The most applicable way to do this is by considering the common market risk factors where counterparties are linked to. This linkage is defined by analysing the counterparties’ sensitivities1 to market risk factors.
In this case the corresponding volatilities and correlations between market risk factors are also considered. Note that the idiosyncratic sensitivities must also be considered. The future correlations are driven by simulating the market evolution, i.e. based on what-if market scenarios. High correlation indicates high probability of credit systemic losses. Even a portfolio where the majority of the interconnected counterparties have low probability of downgrades or default, events could result under stress conditions in a high degree of systemic risk losses. This is due to the fact that a small number of counterparties could be vulnerable to stress conditions and thus could directly impact the correlated counterparties.
As mentioned earlier the probability of downgrades or default events are expressed with credit ratings. However, in the valuation process the actual credit spreads are used and are applied as an add-on factor to market risk free curves. Typically the credit spreads include the assumption of the collaterals and recoveries where the former can be actually measured or estimated, and the latter implies the counterparty’s willingness of future behaviour to cover the credit losses. In fact, this is a mix of the actual and assumed factors; one of the purposes for doing this is to keep the spread steady. In this case the systemic risk analysis may fail to reflect the actual systemic loss of portfolio value even when such risk appears.
Credit spreads, together with the market factors, are used in valuation process and exposures of financial instruments. The current and potential future credit exposure of the portfolio’s instruments linked to the counterparties must be also measured. In fact these exposures can be distinguished as the ones where counterparties are holding and the ones that are exchanged. The former indicates the implications in losses of the portfolio value in case the counterparty defaults or downgrades. The latter, which is not always available, indicates the degree of systemic exposure inter-dependency between the counterparty. In a portfolio with governmental bonds the information referring to both types of exposures is available. The analysis of such exposures indicates the corresponding systemic risk losses.
Future credit exposures can be defined based on stochastic process analysis or deterministic assumed values of market and credit risk factors. Any fluctuation of the exposures due to market volatilities should also be considered to define the degree of haircut that should be applied. Future systemically correlated exposures can be used to estimate the potential systemic losses; thus they can be used to define the collaterals that could be provided for absorbing future systemic losses. It is important to bear in mind, however, that the consideration of gross exposures could help to avoid the implications from general and/or specific ‘wrong way’ risk. Experience shows that in many portfolios where the net exposures were small they did result in a big amount of systemic credit losses.
The rating or spread correlation among the counterparties, together with the degree of the above mentioned exposures, should define the portfolio diversification and re-adjustment by minimising the portfolio losses due to systemic risk. High systemic correlation and exposure indicates high systemic risk losses and vice versa. An optimal portfolio should be balanced based on these two systemic parameters. As systemic risk analysis is based on integrated market, counterparty credit and behaviour risk, the resulting diversified portfolio that minimises the systemic risk is based on a holistic risk management approach.
1Such credit sensitivity analysis is applied in credit value-at-risk (VaR) approaches, for example, CreditMetrics, where the counterparties are correlated to each other via their common linked-with-market indices.
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