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Can Technical Indicators Provide Information for Future Volatility: International Evidence

Author

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  • Shi Yafeng

    (School of Science, Ningbo University of Technology, Ningbo, 315211, China)

  • Tao Xiangxing

    (School of Science, Zhejiang University of Science and Technology, Hangzhou, 310023, China)

  • Shi Yanlong

    (Zhejiang Pharmaceutical College, Ningbo, 315100, China)

  • Zhu Nenghui

    (School of Applied Mathematics, Xiamen University of Technology, Xiamen, 361024, China)

  • Ying Tingting

    (Nottingham University Business School, University of Nottingham Ningbo China, Ningbo, 315100, China)

  • Peng Xun

    (GuangDong Guangya High School, Guangzhou, 510160, China)

Abstract

We employ the static and dynamic copula models to investigate whether technical indicators provide information on volatility in the next trading day, where the volatility is measured by daily realized volatility. Our empirical results, based on long samples of 8 well-known stock indexes, suggest that a significant and asymmetric tail dependence between the technical indicators based on moving average and the next day volatility. The level of dependence change over time in a persistent manner. And the dependence structure presents some distinct differences between emerging market indexes and developed market indexes. These results indicate that the technical indicators can provide information on the next day volatility at extremes, and are less informative at normal market.

Suggested Citation

  • Shi Yafeng & Tao Xiangxing & Shi Yanlong & Zhu Nenghui & Ying Tingting & Peng Xun, 2020. "Can Technical Indicators Provide Information for Future Volatility: International Evidence," Journal of Systems Science and Information, De Gruyter, vol. 8(1), pages 53-66, February.
    • Handle: RePEc:bpj:jossai:v:8:y:2020:i:1:p:53-66:n:4
    DOI: 10.21078/JSSI-2020-053-14
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    References listed on IDEAS

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    1. John Knight & Colin Lizieri & Stephen Satchell, 2005. "Diversification When It Hurts? The Joint Distributions of Real Estate and Equity Markets," Real Estate & Planning Working Papers rep-wp2005-16, Henley Business School, University of Reading.
    2. Ole E. Barndorff‐Nielsen & Neil Shephard, 2002. "Econometric analysis of realized volatility and its use in estimating stochastic volatility models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(2), pages 253-280, May.
    3. Andrew W. Lo & Harry Mamaysky & Jiang Wang, 2000. "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation," Journal of Finance, American Finance Association, vol. 55(4), pages 1705-1765, August.
    4. Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2014. "Forecasting the Equity Risk Premium: The Role of Technical Indicators," Management Science, INFORMS, vol. 60(7), pages 1772-1791, July.
    5. Bollerslev, Tim & Jubinski, Dan, 1999. "Equity Trading Volume and Volatility: Latent Information Arrivals and Common Long-Run Dependencies," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 9-21, January.
    6. Andersen, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Ebens, Heiko, 2001. "The distribution of realized stock return volatility," Journal of Financial Economics, Elsevier, vol. 61(1), pages 43-76, July.
    7. Jones, Charles M & Kaul, Gautam & Lipson, Marc L, 1994. "Transactions, Volume, and Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 7(4), pages 631-651.
    8. Dong-Hyun Ahn & Jennifer Conrad & Robert F. Dittmar, 2003. "Risk Adjustment and Trading Strategies," The Review of Financial Studies, Society for Financial Studies, vol. 16(2), pages 459-485.
    9. Zhu, Yingzi & Zhou, Guofu, 2009. "Technical analysis: An asset allocation perspective on the use of moving averages," Journal of Financial Economics, Elsevier, vol. 92(3), pages 519-544, June.
    10. Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2008. "Designing Realized Kernels to Measure the ex post Variation of Equity Prices in the Presence of Noise," Econometrica, Econometric Society, vol. 76(6), pages 1481-1536, November.
    11. Christian M. Hafner & Hans Manner, 2012. "Dynamic stochastic copula models: estimation, inference and applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(2), pages 269-295, March.
    12. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
    13. Conrad, Jennifer & Kaul, Gautam, 1998. "An Anatomy of Trading Strategies," The Review of Financial Studies, Society for Financial Studies, vol. 11(3), pages 489-519.
    14. John Knight & Colin Lizieri & Stephen Satchell, 2005. "Diversification when It Hurts? The Joint Distributions of Real Estate and Equity Markets1," Journal of Property Research, Taylor & Francis Journals, vol. 22(4), pages 309-323, December.
    15. Brock, William & Lakonishok, Josef & LeBaron, Blake, 1992. "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns," Journal of Finance, American Finance Association, vol. 47(5), pages 1731-1764, December.
    16. Ning, Cathy & Xu, Dinghai & Wirjanto, Tony S., 2008. "Modeling the leverage effect with copulas and realized volatility," Finance Research Letters, Elsevier, vol. 5(4), pages 221-227, December.
    17. Andrew J. Patton, 2006. "Modelling Asymmetric Exchange Rate Dependence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(2), pages 527-556, May.
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