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Financial Sector Volatility Connectedness and Equity Returns


  • Mert Demirer


  • Umut Gokcen

    (Koc University)

  • Kamil Yilmaz

    () (Koc University)


We apply the Diebold and Yilmaz (2014) methodology to daily stock prices of the largest 40 U.S. financial institutions to construct a volatility connectedness index. We then estimate the contemporaneous return sensitivity of every non-financial U.S. company to this index. We find that there is a large statistically significant difference between the returns of firms with positive and negative exposures to financial connectedness. The four-factor alpha of a strategy that goes long in the bottom decile and short in the top decile of stocks sorted on their connectedness betas is roughly 15% per annum. Bivariate portfolio tests reveal that abnormal returns are robust to market beta, size, book-to-market ratio, momentum, debt, illiquidity, and idiosyncratic volatility. Abnormal returns are asymmetric; they are primarily driven by firms whose returns covary negatively with the index. These firms tend to be young and small, with poor past performance and low credit quality.

Suggested Citation

  • Mert Demirer & Umut Gokcen & Kamil Yilmaz, 2018. "Financial Sector Volatility Connectedness and Equity Returns," Koç University-TUSIAD Economic Research Forum Working Papers 1803, Koc University-TUSIAD Economic Research Forum.
  • Handle: RePEc:koc:wpaper:1803

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    References listed on IDEAS

    1. FrancisX. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    2. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    3. Mert Demirer & Francis X. Diebold & Laura Liu & Kamil Yilmaz, 2018. "Estimating global bank network connectedness," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(1), pages 1-15, January.
    4. Billio, Monica & Getmansky, Mila & Lo, Andrew W. & Pelizzon, Loriana, 2012. "Econometric measures of connectedness and systemic risk in the finance and insurance sectors," Journal of Financial Economics, Elsevier, vol. 104(3), pages 535-559.
    5. Zhi Da & Umit G. Gurun & Mitch Warachka, 2014. "Frog in the Pan: Continuous Information and Momentum," Review of Financial Studies, Society for Financial Studies, vol. 27(7), pages 2171-2218.
    6. Pietro Bonaldi & Ali Hortaçsu & Jakub Kastl, 2015. "An Empirical Analysis of Funding Costs Spillovers in the EURO-zone with Application to Systemic Risk," NBER Working Papers 21462, National Bureau of Economic Research, Inc.
    7. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    8. Merton, Robert C, 1973. "An Intertemporal Capital Asset Pricing Model," Econometrica, Econometric Society, vol. 41(5), pages 867-887, September.
    9. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
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    Cited by:

    1. Islam, Raisul & Volkov, Vladimir, 2020. "Contagion or interdependence? Comparing signed and unsigned spillovers," Working Papers 2020-05, University of Tasmania, Tasmanian School of Business and Economics.
    2. Dungey, Mardi & Islam, Raisul & Volkov, Vladimir, 2020. "Crisis transmission: Visualizing vulnerability," Pacific-Basin Finance Journal, Elsevier, vol. 59(C).

    More about this item


    Cross-section of returns; Anomalies; Financial connectedness; Vector autoregressions.;

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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