Two-stage risk-neutral stochastic optimization problem has been widely studied recently. The goals of our research are to construct a two-stage distributionally robust optimization model with risk aversion and to extend it to multi-stage case. We use a coherent risk measure, Conditional Value-at-Risk, to describe risk. Due to the computational complexity of the nonlinear objective function of the proposed model, two decomposition methods based on cutting planes algorithm are proposed to solve the two-stage and multi-stage distributional robust optimization problems, respectively. To verify the validity of the two models, we give two applications on multi-product assembly problem and portfolio selection problem, respectively. Compared with the risk-neutral stochastic optimization models, the proposed models are more robust.

Our knowledge about the evolution of guarantee network in downturn period is limited due to the lack of comprehensive data of the whole credit system. Here we analyze the dynamic Chinese guarantee network constructed from a comprehensive bank loan dataset that accounts for nearly 80% total loans in China, during 01/2007-03/2012. The results show that, first, during the 2007-2008 global financial crisis, the guarantee network became smaller, less connected and more stable because of many bankruptcies; second, the stimulus program encouraged mutual guarantee behaviors, resulting in highly reciprocal and fragile network structure; third, the following monetary policy adjustment enhanced the resilience of the guarantee network by reducing mutual guarantees. Interestingly, our work reveals that the financial crisis made the network more resilient, and conversely, the government bailout degenerated network resilience. These counterintuitive findings can provide new insight into the resilience of real-world credit system under external shocks or rescues.

Recently, China’s energy industry has been continuously depressed due to a slowdown in its economic development. China’s energy companies have made considerable efforts to promote their corporate performance to mitigate this performance decline and to ensure the sustainable development of China’s energy industry, macro economy, society and environment. In this paper, the effects of two business strategies—industrial diversification and international diversification—on the performance of listed energy firms are empirically investigated. The empirical results show the following: (1) industrial diversification hinders corporate performance; (2) for industrially-diversified energy companies, related diversified strategies are more effective than unrelated diversified strategies; and (3) international diversification improves the performance of renewable energy firms, but hinders the performance of conventional energy firms. These results suggest that as economic conditions are not currently optimal, China’s energy companies should pay more attention to their main businesses and generate more products to satisfy market demand.