Insights from the (in)efficiency of Chinese sectoral indices during COVID-19.

This article evaluates the effects of the crisis caused by the new Coronavirus (COVID-19) on the Chinese sectoral indices. Using the complexity-entropy plane methodology, we find that the COVID-19 crisis caused increased inefficiency in most of China's equity sectors. We also find heterogeneous effects depending on the economic sector. Our results are useful for a better understanding the effect of global shocks on the stock markets and how their effects are distributed across economic sectors.

Fluctuations in interbank network dynamics.

This work investigates the scaling properties of fluctuations in the flux of individual agents with respect to their average flux in an interbank network. The analyzed data provide information on daily values of f(i)(asset), the credit provided by bank i in the interbank network, and f(i)(liab), the credit received by bank i from the other banks of the network. The investigation focuses on the scaling properties of the fluctuations in the raw data f(i)(asset), f(i)(liab), and f(R,i)(ext)(t) = f(i)(asset)-f(i)(liab), as well as on similar properties internal and external fluctuations f(i)(int) and f(i)(ext), which are derived according to a recently proposed methodology [M. Argollo de Menezes and A. L. Barabasi, Phys. Rev. Lett. 93, 068701 (2004)]. Finally, a "rolling sampling" approach is introduced in order to deal with the nonstationarity of the fluxes. The results suggest that exponents are time varying, hinting that the considered interbank network is changing with time.