Concepts and Measurement of Risk - Article by Borio, Furfine, Lowe
May 4, 2008 – 7:51 pmClaudio Borio, Craig Furfine and Philip Lowe discuss concepts of risks in their article “Pro-cyclicality of the financial system and financial stability: issues and policy options“:
They distinguish several types of risk:
- expected and unexpected losses (in the statistical sense)
- “Expected losses” refer to the average or mean losses anticipated over a particular period
- “Unexpected losses” refer to a measure of the dispersion, or degree of uncertainty that surrounds that outcome
- relative and absolute risk
- Relative risk relates to the risk, in a cross section, of a particular financial instrument, portfolio or institution (“Bond A is riskier than Bond B”)
- Absolute risk relates to the specific value that the measure of risk takes at a particular point in time (“Portfolio X is more risky today than it was last year”)
- idiosyncratic and systematic risk
- Systematic risk is associated with the correlation between components of a financial system arising from exposures to common factors, such as specific industries or the business cycle.
- risk of individual portfolios and risk of the financial system as a whole.
According to the authors, measuring risk is difficult because it entails
- assessing the riskiness of each individual borrower
- assessing how the correlations between borrowers are changing
- assessing how the institutions collectively affect the health of the economy
- assessing how the health of the economy affects the collective health of individual institutions.
The authors also claim that systemic risk is often related to a common exogenous shock resulting from a change in the business/financial cycle:
Widespread financial system stress rarely arises from the contagion or domino effects associated with the failure of an individual institution owing to purely institution-specific factors. More often, financial system problems have their roots in financial institutions underestimating their exposure to a common factor, most notably the financial/business cycle in the economy as a whole.
Risk measurement in banks often falsely assesses the development of risk:
Many of the risk measurement methodologies used by banks, rating agencies and bank supervisors imply that risk falls during booms and periods of financial market stability and increases only during recessions and periods of financial turmoil. But it is better to think of risk as increasing in booms, not recessions, and that the increase in defaults in recessions simply reflects the materialisation of risk built up in the boom.
The business-cycle has an impact on the emergence of systemic risk, at least in the long-run:
Despite recent research suggesting that a number of financial variables are useful in predicting recessions, macroeconomic forecasters have a poor record in predicting the exact timing of recessions or turning points in the business cycle. Being able to predict the exact timing of a downturn is by no means necessary to design an appropriate response to it. Using longer horizons would help lessen some of the emphasis on short-term forecasting, and promote a more thorough analysis of financial vulnerabilities associated with business and financial cycles. This would promote better assessments of systematic risk.
The set of factors that can result in either misperceptions of risk are:
- Use of the “wrong” model of the economy to interpret developments
- Disaster myopia = tendency to underestimate the likelihood of high-loss low-probability
- Cognitive dissonance = tendency to interpret information in a biased way, so that it reinforces the prevailing belief entertained by the economic agent.23
The set of factors that can result in inappropriate responses to risk are:
- failure to internalise the consequences of the actions of others
- the impossibility of coordinating responses
- costs borne by other groups in society
- “herding behaviour” = agents conform their behaviour to that of their peers
- shortcomings in contractualarrangements stressing short-term performance