Abstract
AbstractBased on monthly data covering the period from 1987 to 2021, we analyse whether cross‐sectional moments of stock market returns may provide information about the future position of the German business cycle. We apply in‐sample forecasting regressions with and without leading indicators as control variables, pseudo‐out‐of‐sample exercises, autoregressive distributed lag models, and impulse‐response functions estimated by local projections. We find in‐sample predictive power of the first and third cross‐section moments for the future growth of industrial production, even if one controls for well‐established leading indicators for the German business cycle. Out‐of‐sample tests show that these variables reduce the relative mean squared error compared with benchmark models. We do not find a long‐run relation between the moment series and industrial production. The dynamic response of industrial production to a shock on the cross‐section moments is in line with the other results.
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