medium · FRM Part 1 Valuation and Risk Models

An analyst calculates a Durbin-Watson (DW) statistic of 0.85 for a time-series regression of credit spreads.

What is the most likely diagnosis and its consequence for the model's hypothesis tests?

  1. Negative serial correlation is present; standard errors look overstated, making the model appear too conservative.
  2. Multicollinearity is present; the model cannot separate the effects of the different explanatory variables.
  3. Heteroskedasticity is present; variance is not constant, though the standard errors stay unbiased.
  4. Positive serial correlation; standard errors are likely understated, and t-statistics are falsely inflated.

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