Stress testing and “Incorrect” Signs

Original by Moody’s analytics, 2013, 5 pagesHamster_gagarin_linkedin
hamster writter This summary note was posted on 7 January 2017, by in Finance Stress Testing
  • Variables displaying a wrong way sign contribution to a model are too often dismissed without further consideration
  • If sign remains wrong after all due diligence it should be welcomed as an opportunity to deepen our understanding of the model
Long run multiplier effects
  • Takes the example of the unemployment rate as unique factor to model delinquency
  • The initial impact of rising unemployment rate is larger than the long term impact of unemployment on default probability
    • Should thus expect the lagged unemployment terms to take negative signs compared to the instantaneous unemployment variable which takes a larger positive coefficient
    • by including the lagged effects we can boost the scale of the short term effect giving higher stressed projections
  • In many situations it is enough to demonstrate that the total effect of a shock “goes the right way” and that the model fits the observed data well
Omitted variables
  • Management actions related variables are correlated with economic outcomes
  • Omitting those variables will bias the effect of the economic variables on performance
  • Moody’s view is that they should be included for stress testing and model should take into account of past management shifts
Ceteris paribus conditions
  • Multicollinearity is a fact of life
  • The FED’s scenario reflect the fact that a rapidly rising unemployment rate will be accompanied by commensurate shifts in all other aspects of the economy.
  • The direct result of rising cost of money should be to increase losses
  • Intuitively we should see positive signs on interest rate variables in as standard PD regression model
  • Higher interest rates are symptoms of a booming economy
  • Strong correlations are generally far more effective in reducing prediction errors than weak causations
  • Interest rates in credit loss models have the advantage of being reasonably easy to forecast
  • Model with negative interest rate coefficients should not overly trouble stress-test model validators
  • Banks generally do not move in lock step with the economic cycle
  • Models that are not permitted to capture these timing effects and casual relationships are next to useless for assessing bank capital adequacy
  • In a situation where model validators and Fed regulators are insisting on tiny models that assume coincidence with the economic cycle is an elaborate form of economic window dressing
  • We need to move to a situation where stress test models at least attempt to shine light on sometimes complex underlying processes even if the ban manager
  • s are sometimes left scratching their heads about the data.