In this paper, we propose a new approach to studying the spread of financial crises, their effects, and origins. To do this, an empirical measure of the degree of crisis transmission is introduced in the context of a crisis propagation model that corresponds to a multifactorial switching model with random endogenous transition variable. The latter is modeled as a diffusion process and allows us to determine whether crisis transmission is perfect, partial, or weak and whether it is due to contagion or interdependence effects. In addition, the model takes into account the relative impact of idiosyncratic and global factors in crisis and non-crisis periods, as well as any lag in the crisis transmission process. We used the genetic algorithm as an empirical method, because it uses probabilistic rather than deterministic transition rules, which is appropriate for our work. Our results suggest that the subprime crisis is perfectly or partially transmitted to developed markets and interdependence effects are due to most of them. However, the transmission to emerging markets is only partial or weak and, in most cases, due to contagion effects. Moreover, the significance of the coefficients of idiosyncratic factors was not related to crisis effects. For many countries, these coefficients were higher than the coefficients of the global factors, while crisis transmission was due to contagion effects. Our results exceed those of alternative studies on crisis transmission and provide important portfolio and risk management insights. By understanding the crisis transmission mechanism, investors and risk managers can make appropriate decisions to hedge against market downturns and reduce risk out of the country.
Supplementary information: The online version contains supplementary material available at 10.1007/s43546-022-00361-9.
Keywords: Crisis effects; Crisis transmission; Crisis transmission degree; Crisis transmission magnitude; Developed, emerging and frontiers markets; Diffusion process; Idiosyncratic and global factors; Multifactorial switching regimes model.
© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.