Goto Hayato, Takayasu Hideki, Takayasu Misako
Department of Computational Intelligence and Systems Science, Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology, 4259, Nagatsuta-cho, Yokohama 226-8502, Japan.
Institute of Innovative Research, Tokyo Institute of Technology, 4259, Nagatsuta-cho, Yokohama 226-8502, Japan.
PLoS One. 2017 Oct 3;12(10):e0185712. doi: 10.1371/journal.pone.0185712. eCollection 2017.
We derive a stochastic function of risk propagation empirically from comprehensive data of chain-reaction bankruptcy events in Japan from 2006 to 2015 over 5,000 pairs of firms. The probability is formulated by firm interaction between the pair of firms; it is proportional to the product of α-th power of the size of the first bankrupt firm and β-th power of that of the chain-reaction bankrupt firm. We confirm that α is positive and β is negative throughout the observing period, meaning that the probability of cascading failure is higher between a larger first bankrupt firm and smaller trading firm. We additionally introduce a numerical model simulating the whole ecosystem of firms and show that the interaction kernel is a key factor to express complexities of spreading bankruptcy risks on real ecosystems.
我们从2006年至2015年日本连锁反应破产事件的综合数据中，以实证方式推导出了一个风险传播的随机函数，涉及5000多对公司。该概率由一对公司之间的公司互动来确定；它与第一家破产公司规模的α次方与连锁反应破产公司规模的β次方的乘积成正比。我们证实，在整个观察期内，α为正，β为负，这意味着在规模较大的第一家破产公司和规模较小的交易公司之间，级联故障的概率更高。我们还引入了一个模拟公司整个生态系统的数值模型，并表明相互作用核是表达真实生态系统中破产风险传播复杂性的关键因素。
