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马里兰大学教授V.S. Subrahmanian:金融互联度有助于预测银行系统危机吗?

2015年05月22日 00:00
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【主讲】马里兰大学教授V.S. Subrahmanian

【题目】金融互联度有助于预测银行系统危机吗?

【时间】2015年5月22日(周五)16.30-17.30

【地点】清华经管学院伟伦楼453

【语言】英文

【主办】管理科学与工程系

【简历】V.S. Subrahmanian老师的简历

V.S. Subrahmanian is Professor of Computer Science at the University of Maryland and heads the Center for Digital International Government, having previously served as Director of the University of Maryland's Institute for Advanced Computer Studies. Prof. Subrahmanian is an expert on big data analytics, learning behavioral models from the data, forecasting actions/events, and influence behaviors. His work has been featured in numerous outlets such as the Baltimore Sun, the Economist, Science, Nature, the Washington Post, American Public Media. He serves on the editorial boards of numerous journals including Science, the Board of Directors of the Development Gateway Foundation (set up by the World Bank), SentiMetrix, Inc., and on the Research Advisory Board of Tata Consultancy Services. He previously served on DARPA's Executive Advisory Council on Advanced Logistics and as an ad-hoc member of the US Air Force Science Advisory Board (2001).

【Abstract】The global financial crisis has reignited interest in models of crisis prediction. It has also raisedthe question whether financial interconnectedness—a possible source of systemic risk—can serve as an early warning indicator of crises. In this paper, we examine the ability of connectedness in the global network of financial linkages to predict systemic banking crises during the 1978–2010 period. Our results indicate that increases in a country’s own connectedness and decreases in its neighbours’connectedness are associated with a higher probability of banking crises after controlling for macroeconomic fundamentals. Our findings suggest that financial interconnectedness has early warning potential, especially for the 2007–2010 wave of systemic banking crises. Joint work with Camelia Minoiu (IMF), Chanhyun Kang (Univ. of Md) and Anamaria Berea (George Mason Univ).