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Jumps beyond the realms of cricket: India's performance in One Day Internationals and stock market movements

Author

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  • Konstantinos Gkillas
  • Rangan Gupta
  • Chi Keung Marco Lau
  • Muhammad Tahir Suleman

Abstract

We examine the impact of the Indian cricket team's performance in one-day international cricket matches on return, realized volatility and jumps of the Indian stock market, based on intraday data covering the period of 30th October, 2006 to 31st March, 2017. Using a nonparametric causality-in-quantiles test, we were able to detect evidence of predictability from wins or losses for primarily volatility and jumps, especially over the lower-quantiles of the conditional distributions, with losses having stronger predictability than wins. However, the impact on the stock return is weak and restricted towards the upper end of the conditional distribution.

Suggested Citation

  • Konstantinos Gkillas & Rangan Gupta & Chi Keung Marco Lau & Muhammad Tahir Suleman, 2020. "Jumps beyond the realms of cricket: India's performance in One Day Internationals and stock market movements," Journal of Applied Statistics, Taylor & Francis Journals, vol. 47(6), pages 1109-1127, April.
  • Handle: RePEc:taf:japsta:v:47:y:2020:i:6:p:1109-1127
    DOI: 10.1080/02664763.2019.1663157
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    1. Bert Scholtens & Wijtze Peenstra, 2009. "Scoring on the stock exchange? The effect of football matches on stock market returns: an event study," Applied Economics, Taylor & Francis Journals, vol. 41(25), pages 3231-3237.
    2. Corsi, Fulvio & Pirino, Davide & Renò, Roberto, 2010. "Threshold bipower variation and the impact of jumps on volatility forecasting," Journal of Econometrics, Elsevier, vol. 159(2), pages 276-288, December.
    3. Aigbe Akhigbe & Melinda Newman & Ann Marie Whyte, 2017. "Predictable Sports Sentiment and Local Trading," Financial Management, Financial Management Association International, vol. 46(2), pages 433-453, June.
    4. Ole E. Barndorff-Nielsen & Neil Shephard, 2006. "Econometrics of Testing for Jumps in Financial Economics Using Bipower Variation," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 4(1), pages 1-30.
    5. Christensen, Kim & Oomen, Roel & Podolskij, Mark, 2010. "Realised quantile-based estimation of the integrated variance," Journal of Econometrics, Elsevier, vol. 159(1), pages 74-98, November.
    6. Malcolm Baker & Jeffrey Wurgler, 2006. "Investor Sentiment and the Cross‐Section of Stock Returns," Journal of Finance, American Finance Association, vol. 61(4), pages 1645-1680, August.
    7. Andersen, Torben G. & Dobrev, Dobrislav & Schaumburg, Ernst, 2012. "Jump-robust volatility estimation using nearest neighbor truncation," Journal of Econometrics, Elsevier, vol. 169(1), pages 75-93.
    8. Bekaert, Geert & Hoerova, Marie, 2014. "The VIX, the variance premium and stock market volatility," Journal of Econometrics, Elsevier, vol. 183(2), pages 181-192.
    9. Konstantinos Gkillas & Rangan Gupta & Mark E. Wohar, 2020. "Oil shocks and volatility jumps," Review of Quantitative Finance and Accounting, Springer, vol. 54(1), pages 247-272, January.
    10. Hui-Chu Shu & Jung-Hsien Chang, 2015. "Investor Sentiment and Financial Market Volatility," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 16(3), pages 206-219, July.
    11. Massimiliano Caporin & Eduardo Rossi & Paolo Santucci de Magistris, 2016. "Volatility Jumps and Their Economic Determinants," Journal of Financial Econometrics, Oxford University Press, vol. 14(1), pages 29-80.
    12. Mishra, Vinod & Smyth, Russell, 2010. "An examination of the impact of India's performance in one-day cricket internationals on the Indian stock market," Pacific-Basin Finance Journal, Elsevier, vol. 18(3), pages 319-334, June.
    13. Hakan Berument & Esin Gšzpinar & Basak Ceylan, 2006. "Performance of Soccer on the Stock Market:Evidence from Turkey," Working Papers 0606, Department of Economics, Bilkent University.
    14. Christian Klein & Bernhard Zwergel & Sebastian Heiden, 2009. "On the existence of sports sentiment: the relation between football match results and stock index returns in Europe," Review of Managerial Science, Springer, vol. 3(3), pages 191-208, November.
    15. Cecilia Mancini, 2009. "Non‐parametric Threshold Estimation for Models with Stochastic Diffusion Coefficient and Jumps," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(2), pages 270-296, June.
    16. Jeong, Kiho & Härdle, Wolfgang K. & Song, Song, 2012. "A Consistent Nonparametric Test For Causality In Quantile," Econometric Theory, Cambridge University Press, vol. 28(4), pages 861-887, August.
    17. Dimic, Nebojsa & Neudl, Manfred & Orlov, Vitaly & Äijö, Janne, 2018. "Investor sentiment, soccer games and stock returns," Research in International Business and Finance, Elsevier, vol. 43(C), pages 90-98.
    18. Mehmet Balcilar & Riza Demirer & Rangan Gupta & Mark E. Wohar, 2018. "Differences of opinion and stock market volatility: evidence from a nonparametric causality-in-quantiles approach," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 42(2), pages 339-351, April.
    19. Kaustia, Markku & Rantapuska, Elias, 2016. "Does mood affect trading behavior?," Journal of Financial Markets, Elsevier, vol. 29(C), pages 1-26.
    20. Mehmet Balcilar & Rangan Gupta & Clement Kyei, 2018. "Predicting Stock Returns And Volatility With Investor Sentiment Indices: A Reconsideration Using A Nonparametric Causality†In†Quantiles Test," Bulletin of Economic Research, Wiley Blackwell, vol. 70(1), pages 74-87, January.
    21. Narayan, Paresh Kumar & Rath, Badri Narayan & Prabheesh, K.P., 2016. "What is the value of corporate sponsorship in sports?," Emerging Markets Review, Elsevier, vol. 26(C), pages 20-33.
    22. Pantzalis, Christos & Park, Jung Chul, 2014. "Exuberance out of left field: Do sports results cause investors to take their eyes off the ball?," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PB), pages 760-780.
    23. Dashan Huang & Fuwei Jiang & Jun Tu & Guofu Zhou, 2015. "Investor Sentiment Aligned: A Powerful Predictor of Stock Returns," Review of Financial Studies, Society for Financial Studies, vol. 28(3), pages 791-837.
    24. repec:hal:journl:peer-00741630 is not listed on IDEAS
    25. Georgios Kavetsos & Stefan Szymanski, 2008. "Olympic Games, Terrorism and their Impact on the London and Paris Stock Exchanges," Revue d'économie politique, Dalloz, vol. 118(2), pages 189-206.
    26. Kaplanski, Guy & Levy, Haim, 2010. "Sentiment and stock prices: The case of aviation disasters," Journal of Financial Economics, Elsevier, vol. 95(2), pages 174-201, February.
    27. CURATOLA, Giuliano & DONADELLI, Michael & KIZYS, Renatas & RIEDEL, Max, 2016. "Investor Sentiment and Sectoral Stock Returns: Evidence from World Cup Games," Finance Research Letters, Elsevier, vol. 17(C), pages 267-274.
    28. Kaplanski, Guy & Levy, Haim, 2010. "Exploitable Predictable Irrationality: The FIFA World Cup Effect on the U.S. Stock Market," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(2), pages 535-553, April.
    29. Diep Duong & Norman R. Swanson, 2011. "Volatility in Discrete and Continuous Time Models: A Survey with New Evidence on Large and Small Jumps," Departmental Working Papers 201117, Rutgers University, Department of Economics.
    30. Gkillas, Konstantinos & Gupta, Rangan & Wohar, Mark E., 2018. "Volatility jumps: The role of geopolitical risks," Finance Research Letters, Elsevier, vol. 27(C), pages 247-258.
    31. Alex Edmans & Diego García & Øyvind Norli, 2007. "Sports Sentiment and Stock Returns," Journal of Finance, American Finance Association, vol. 62(4), pages 1967-1998, August.
    32. Ser-Huang Poon & Clive W.J. Granger, 2003. "Forecasting Volatility in Financial Markets: A Review," Journal of Economic Literature, American Economic Association, vol. 41(2), pages 478-539, June.
    33. repec:hal:journl:peer-00732538 is not listed on IDEAS
    34. Duong, Diep & Swanson, Norman R., 2015. "Empirical evidence on the importance of aggregation, asymmetry, and jumps for volatility prediction," Journal of Econometrics, Elsevier, vol. 187(2), pages 606-621.
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    Cited by:

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    2. Yang, Kun & Wei, Yu & Li, Shouwei & Liu, Liang & Wang, Lei, 2021. "Global financial uncertainties and China’s crude oil futures market: Evidence from interday and intraday price dynamics," Energy Economics, Elsevier, vol. 96(C).

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    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G1 - Financial Economics - - General Financial Markets

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