Adrián Fernández Pérez, Fernando Fernández Rodríguez, Simón Sosvilla Rivero
We present a model to forecast the probability of bear markets in the Spanish IBEX 35 with a congruent and concise parameterization which selects the explanatory factors from a wide set of variables like the yield curve of Spain, US and Europe, as well as several macro variables, and numerous leading indicators.
To this end, we first use a data-guided algorithm to select an in-sample optimal Probit model that is employed as a benchmark. We then form alternative Probit models obtained from combinations of levels, slopes and/or curvatures in the yield curve of Spain, US and Europe, as well as several macro variables and compare their estimated probability of bear markets in the out-of-sample period with that from the benchmark model. Our results suggest that the slopes of US and Europe yield curves have some 2 information content (not implicitly present in the slope of the Spanish yield curve) that helps to better forecast the probability of bear markets in the IBEX 35.
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