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Forecasting crash risk in U.S. bank returns—The role of credit booms

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  • Mihai, Marius M.
  • Mansur, Iqbal

Abstract

We propose a new credit variable called probability of aggregate loan trend deviations (pltd) that forecasts crash risk in U.S. bank stock returns. Compared to more classic measures of credit, the main innovation in pltd is that it incorporates a large amount of macroeconomic information in the form of money and interest rate variables known to drive the aggregate loan supply. Positive changes in pltd increase the level of systemic risk in the economy and also trigger lower bank returns and cash flows up to horizons of one year. To disentangle the effect our credit variable has on future bank returns we break down the total variance into individual components and estimate series for news of discount-rates and cash flows. We find that pltd only leads the cash-flow news component without significant effects on the discount-rate news. Finally, we show that pltd is not only useful for predicting the mean of future bank stock returns in-sample and out-of-sample but is also an important driver of the tail of the return distribution proxied by CATFIN.

Suggested Citation

  • Mihai, Marius M. & Mansur, Iqbal, 2022. "Forecasting crash risk in U.S. bank returns—The role of credit booms," Journal of Corporate Finance, Elsevier, vol. 76(C).
    • Handle: RePEc:eee:corfin:v:76:y:2022:i:c:s092911992200116x
    DOI: 10.1016/j.jcorpfin.2022.102273
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