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Determinants of Systemic Risk and Information Dissemination

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  • Marcelo Bianconi
  • Xiaxin Hua
  • Chih Ming Tan

Abstract

We study the effects of two measures of information dissemination on the determination of systemic risk. One measure is print-media consumer sentiment based while the other is volatility based. We find evidence that while the volatility measure (VIX) of future expectations has a more significant direct impact upon systemic risk of financial firms under distress, a consumer sentiment measure based on print-media news does impact upon firm's financial stress via the externality of other firm's financial stress. This latter effect is robust even though the VIX and the consumer sentiment have dynamic feedback in the short one and two-day horizon in levels, and contemporaneously in volatility. In reference to the internet bubble of the 1990s, the consumer sentiment measure predicts larger systemic risk in the whole period of exuberance while the VIX predicts a sharp larger systemic risk in the height of the bubble. Our evidence suggests that print-media consumer sentiment might be dominated by the VIX when predicting systemic risk.

Suggested Citation

  • Marcelo Bianconi & Xiaxin Hua & Chih Ming Tan, 2013. "Determinants of Systemic Risk and Information Dissemination," Discussion Papers Series, Department of Economics, Tufts University 0776, Department of Economics, Tufts University.
  • Handle: RePEc:tuf:tuftec:0776
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    2. Madhavi Latha Challa & Venkataramanaiah Malepati & Siva Nageswara Rao Kolusu, 2018. "Forecasting risk using auto regressive integrated moving average approach: an evidence from S&P BSE Sensex," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 4(1), pages 1-17, December.
    3. Boubaker, Sabri & Karim, Sitara & Naeem, Muhammad Abubakr & Rahman, Molla Ramizur, 2024. "On the prediction of systemic risk tolerance of cryptocurrencies," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    4. Shan Jiang & Hsinchun Chen, 2019. "Examining patterns of scientific knowledge diffusion based on knowledge cyber infrastructure: a multi-dimensional network approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(3), pages 1599-1617, December.
    5. Yao, Yanzhen & Li, Jianping & Zhu, Xiaoqian & Wei, Lu, 2017. "Expected default based score for identifying systemically important banks," Economic Modelling, Elsevier, vol. 64(C), pages 589-600.
    6. Song, Jianhua & Zhang, Zhepei & So, Mike K.P., 2021. "On the predictive power of network statistics for financial risk indicators," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    7. Hikmet Akyol & Selim Basar, 2024. "Empirical Analysis of Turkish Banking Sector Institutional and Macroeconomic Determinants of Risks," Istanbul Journal of Economics-Istanbul Iktisat Dergisi, Istanbul University, Faculty of Economics, vol. 73(74-1), pages 59-98, June.
    8. Shuting Liu & Qifa Xu & Cuixia Jiang, 2021. "Systemic risk of China’s commercial banks during financial turmoils in 2010-2020: A MIDAS-QR based CoVaR approach," Applied Economics Letters, Taylor & Francis Journals, vol. 28(18), pages 1600-1609, October.
    9. Tom Marty & Bruce Vanstone & Tobias Hahn, 2020. "News media analytics in finance: a survey," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(2), pages 1385-1434, June.
    10. Silva, Walmir & Kimura, Herbert & Sobreiro, Vinicius Amorim, 2017. "An analysis of the literature on systemic financial risk: A survey," Journal of Financial Stability, Elsevier, vol. 28(C), pages 91-114.

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    More about this item

    Keywords

    conditional value-at-risk; VIX; externality; consumer sentiment;
    All these keywords.

    JEL classification:

    • G00 - Financial Economics - - General - - - General
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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