PL EN


2020 | vol. 64, nr 4 | 101-114
Article title

Linkages between American and European publicly traded airline companies – evidence resulting from the Diebold-Yilmaz method

Authors
Content
Title variants
PL
Powiązania pomiędzy notowaniami amerykańskich i europejskich linii lotnicznych – wnioski z metody Diebolda i Yilmaza
Languages of publication
EN
Abstracts
EN
In this paper, the author implemented the Diebold and Yilmaz approach to analyse the connectedness between the major American and European publicly traded airline companies. The author calculated the return and volatility spillover index for the whole sample using a dynamic rolling sample analysis. The results show that all airlines are significantly linked but there is a clear division into two markets. It was found that return spillovers are more intensive than volatility spillovers. Moreover, the average connectedness level is higher in the U.S. market for returns as well as for volatility. An increase of connectedness occurred due to the certain events: issues linked with the condition of the global economy and long-term crude oil price changes.
PL
W artykule przedstawiono wyniki badania powiązań w świetle metody Diebolda i Yilmaza pomiędzy notowaniami najważniejszych linii lotniczych w Stanach Zjednoczonych i w Europie. Wyznaczono indeks powiązań dla dziennych zwrotów i zmienności dla całej próby oraz w ujęciu dynamicznym. Wyniki badania wskazują, że notowania wszystkich analizowanych linii lotniczych są ze sobą powiązane, ale istnieje wyraźny podział na dwa rynki. Powiązania między rynkiem europejskim a amerykańskim są znacznie słabsze niż efekty zarażania pomiędzy liniami lotniczymi z jednego rynku. Efekty zarażania są silniejsze dla zwrotów niż dla zmienności. Ponadto średni poziom indeksu powiązań jest wyższy w Stanach Zjednoczonych niż w Europie. Na zmiany poziomu powiązań w czasie miały wpływ wydarzenia z otoczenia makroekonomicznego i rynku kapitałowego oraz długotrwała zmiana poziomu ceny ropy naftowej.
References
  • Alter, A., and Beyer, A. (2014). The dynamics of spillover effects during the European sovereign debt turmoil. Journal of Banking & Finance, 42, 134-153.
  • Antonakakis, N. (2012). Exchange return co-movements and volatility spillovers before and after the introduction of euro. Journal of International Financial Markets, Institutions and Money, 22(5), 1091-1109.
  • Antonakakis, N., and Kizys, R. (2015). Dynamic spillovers between commodity and currency markets. International Review of Financial Analysis, 41, 303-319.
  • Awartani, B., and Maghyereh, A.I. (2013). Dynamic spillovers between oil and stock markets in the Gulf Cooperation Council Countries. Energy Economics, 36, 28-42.
  • Baruník, J., Kočenda, E., and Vácha, L. (2016). Asymmetric connectedness on the U.S. stock market: Bad and good volatility spillovers, Journal of Financial Markets, 27, 55-78.
  • Batten, J.A., Ciner, C., and Lucey, B.M. (2015). Which precious metals spill over on which, when and why? Some evidence. Applied Economics Letters, 22, 466-473.
  • Baumeister, Ch., Kilian, L. (2016). Understanding the Decline in the Price of Oil since June 2014. Journal of the Association of Environmental and Resource Economists, 3, 131-158.
  • Carter, D. A., and Simkins, B. J. (2004). The market’s reaction to unexpected, catastrophic events: the case of airline stock returns and the September 11th attacks. The Quarterly Review of Economics and Finance, 44(4), 539-558.
  • Demirer, M., Diebold, F. X., Liu, L., and Yilmaz, K (2018). Estimating Global Bank Network Connectedness. Journal of Applied Econometrics, 33, 1-15.
  • Diebold, F. X., and Yilmaz, K. (2009). Measuring financial asset return and volatility spillovers, with application to global equity markets. The Economic Journal, 119, 158-171.
  • Diebold, F. X., and Yilmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28, 57-66.
  • Diebold, F. X., and Yilmaz, K. (2014). On the network topology of variance decompositions: Measuring the connectedness of financial firms. Journal of Econometrics, 182(1), 119-134.
  • Diebold, F. X., and Yilmaz, K. (2016). Trans-Atlantic Equity Volatility Connectedness: U.S. and European Financial Institutions, 2004-2014. Journal of Financial Econometrics, 14(1), 81-127.
  • Gillen, D., and Lall, A. (2003). International transmission of shocks in the airline industry. Journal of Air Transport Management, 9(1), 37-49.
  • Gong, S. X. H., Firth, M., and Cullinane, K. (2008). International oligopoly and stock market linkages: The case of global airlines. Transportation Research Part E: Logistics and Transportation Review, 44(4), 621-636.
  • Hsu, C. (2017). How fuel price shocks affect airline stock returns: an empirical study of major US carriers. The International Journal of Business and Finance Research, 11(2), 51-59.
  • Kang, S. H., McIver, R., and Yoon, S-M. (2017). Dynamic spillover effects among crude oil, precious metal, and agricultural commodity futures markets. Energy Economics, 62, 19-32.
  • Killins, R. N. (2020). The impact of oil on equity returns of Canadian and U.S. Railways and airlines, North American Journal of Economics and Finance, 52.
  • Kliber, A., and Włosik, K., (2019). Isolated Islands or Communicating Vessels? – Bitcoin Price and Volume Spillovers Across Cryptocurrency Platforms. Czech Journal of Economics and Finance (Finance a uver), 69(4), 324-341.
  • Koop, G., Pesaran, M. H., and Potter, S. M. (1996). Impulse response analysis in non-linear multivariate models. Journal of Econometrics, 74, 119-147.
  • Kristjanpoller, W.D., and Concha, D. (2016). Impact of fuel price fluctuations on airline stock returns. Applied Energy, 178, 496-504.
  • Mohanty, S., Nandha, M., Habis, E., and Juhabi, E. (2014). Oil price risk exposure: The case of the US travel and leisure industry. Energy Economics, 41, 117-124.
  • Nandha, M., and Brooks, R. (2009). Oil prices and transport sector returns: An international analysis. Review of Quantitative Finance and Accounting, 33, 393-409.
  • Parkinson, M. (1980). The extreme value method for estimating the variance of the rate of return. The Journal of Business, 53(1), 61-65.
  • Pesaran, M.H., and Shin, Y., (1998). Generalized impulse response analysis in linear multivariate models. Economics Letters, 58, 17-29.
  • Stalnaker, T., Usman, K., Taylor, A., and Alport, G. (2018). Airline economic analysis. 2017-2018 Edition, Oliver Wyman. Retrieved from https://www.oliverwyman.com/content/dam/oliver-wyman/v2/publications/2018/January/Airline_Economic_Analysis_AEA_2017-18_web_FF.pdf
  • Yun, X., and Yoon, S. M. (2019). Impact of oil price change on airline’s stock price and volatility: Evidence from China and South Korea. Energy Economics, 78, 668-679.
  • Zhou, X., Zhang, W., and Zhang, J. (2012). Volatility spillovers between the Chinese and world equity markets. Pacific-Basin Finance Journal, 20(2), 247-270.
Document Type
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.desklight-068790cc-e11f-4203-b58b-cfef067dd97a
JavaScript is turned off in your web browser. Turn it on to take full advantage of this site, then refresh the page.