In this paper, we propose a methodology to effectively capture credit risk from firms’ network. In short, our target is to numerically obtain additional credit risk from connected firms on network. Recently, commercial networks are available for investing and managing risk on professional information terminals like Bloomberg and Reuters. They enable us to check commercial connection of firms.We utilize them to assess positive and negative effect on observing firms from neighbor firms, especially, when the neighbor firms have any credit events. We propose a methodology to analyze/measure credit impact, which observing firms potentially receive from their neighbors. We applied Merton model (Merton and Robert in J Financ 29(2):449-470, 1974) which is generally utilized for credit risk management to calculate additional risk and simplified the formula for practicability/usability. Also, it enables us to escape from having any difficulties in computation time. We introduce our approach with over-viewing simple model guidance and explaining a few samples of numerical experiments.
CITATION STYLE
Kaneko, T., & Hisakado, M. (2019). Additional default probability in consideration of firm’s network. In Network Theory and Agent-Based Modeling in Economics and Finance (pp. 301–312). Springer Singapore. https://doi.org/10.1007/978-981-13-8319-9_15
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