IDEAS home Printed from https://ideas.repec.org/p/koc/wpaper/1803.html
   My bibliography  Save this paper

Financial Sector Volatility Connectedness and Equity Returns

Author

Listed:
  • Mert Demirer

    (MIT)

  • Umut Gokcen

    (Koc University)

  • Kamil Yilmaz

    () (Koc University)

Abstract

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
    as

    Download full text from publisher

    File URL: http://eaf.ku.edu.tr/sites/eaf.ku.edu.tr/files/erf_wp_1803.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    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, 2015. "Estimating Global Bank Network Connectedness," Koç University-TUSIAD Economic Research Forum Working Papers 1512, Koc University-TUSIAD Economic Research Forum.
    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.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:koc:wpaper:1803. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sumru Oz). General contact details of provider: http://edirc.repec.org/data/dekoctr.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.