In this paper, a Probit model proposed by Estrella and Mishkin (1998) and Resnick and Shoesmith (2002) has been used to forecast the probability of bear markets, one month ahead, in the IBEX 35 index, during the period February 1991 to December 2009. During this period Spain's main equity index experienced both extreme rises (outperforming other main markets) and severe falls (especially in 2008 when it was hit by liquidity tensions of an unprecedented magnitude, generating enormous uncertainty in a context of economic downturn).
We have used the in-sample (February 1991–January 2003) optimal Probit model, selected by GASIC algorithm, as a benchmark. Alternatively, several Probit models formed by combinations of levels, slopes and/or curvatures in yield curve of Spain, US and Europe, in addition, several macro variables as in Chen (2009), have been employed to forecast the probability of bear markets in out-of-sample period (February 2003–December 2009) and compared with that from the benchmark model. In addition, the dynamic Probit model proposed by Nyberg (2010) and Bismans and Majetti (2013) has also been evaluated.
Our results indicate that the optimal Probit model rendered the second-best in-sample goodness of fit (only outperformed by a Probit model with the lagged endogenous variable) but the worst out-of-sample performance. On the other hand, the optimal Probit model in a dynamic framework obtains a better out-of-sample performance. In this sense, Probit models formed by slopes of Spain, US and Europe and slopes of Spain and Europe offered the best goodness in prediction, as well as the highest Sharpe ratio in a naïve trading strategy based on their predictions of bear markets.
Our findings suggest that to combine slopes in yield curve of Spain, US and Europe does improve the prediction of the probability of bear markets, one month ahead, in the IBEX 35. Thus, we have proved that the slopes of US and mainly Europe have some information content (not implicitly present in the slope of the Spanish yield curve), related to the former probability. This result could be reflecting that more than half of billing of the IBEX 35 companies corresponds to the external sector, distributed more or less evenly among the European Union and the rest of the European Union or OECD world (the latter proxied by the US). Besides, the use of these predictions in a naïve trading strategy in the IBEX 35 renders better performance than a B&H strategy.
We consider that our results are of interest, not only for the Spanish experience in the 1991–2009 period, but also for the analysis of other European peripheral countries, as well as for investigating other episodes of strong bear markets in a context of severe recession registered during the last global crisis in many countries and regions around the world.
Facts found here might have both some practical meaning for investors and some theoretical insights for academic scholars interested in the role of the yield curve as a leading indicator of the stock market behavior.
Further research could extend this analysis to other countries checking, somehow, the globalization level in the world economy. Also, it could be interesting to analyze what the most influential economies are worldwide, or by regions, through slopes in yield curve of those economies.