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What Do We Learn from Daily Leaders and Laggards in Stock Investment? Do They Help Outperform the Market Average?

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  • Doh-Khul Kim
  • Sung-Min Kim

Abstract

Investors generally believe that rising stocks are more likely to maintain their trend and rise going forward, whereas the losing stocks look more price attractive. This belief can lead the investors to expect that they can outperform the average market by trading the stocks purely based on the price movements. However, this research finds that this simple trading strategy does not effectively outperform the market. Nonetheless, we find five sectors of rising stocks and three sectors of declining stocks that outperform the average market in this limited study.

Suggested Citation

  • Doh-Khul Kim & Sung-Min Kim, 2022. "What Do We Learn from Daily Leaders and Laggards in Stock Investment? Do They Help Outperform the Market Average?," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 14(2), pages 1-44, February.
  • Handle: RePEc:ibn:ijefaa:v:14:y:2022:i:2:p:44
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    References listed on IDEAS

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    1. Wing-Keung Wong & Meher Manzur & Boon-Kiat Chew, 2003. "How rewarding is technical analysis? Evidence from Singapore stock market," Applied Financial Economics, Taylor & Francis Journals, vol. 13(7), pages 543-551.
    2. Matheus José Silva de Souza & Danilo Guimarães Franco Ramos & Marina Garcia Pena & Vinicius Amorim Sobreiro & Herbert Kimura, 2018. "Examination of the profitability of technical analysis based on moving average strategies in BRICS," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 4(1), pages 1-18, December.
    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. Andrey Kudryavtsev, 2019. "The Effect Of Trading Volumes On Stock Returns Following Large Price Moves," Economic Annals, Faculty of Economics and Business, University of Belgrade, vol. 64(220), pages 85-116, January –.
    5. R. Rosillo & D. de la Fuente & J. A. L. Brugos, 2013. "Technical analysis and the Spanish stock exchange: testing the RSI, MACD, momentum and stochastic rules using Spanish market companies," Applied Economics, Taylor & Francis Journals, vol. 45(12), pages 1541-1550, April.
    6. Andrey Kudryavtsev, 2018. "The Availability Heuristic and Reversals Following Large Stock Price Changes," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 19(2), pages 159-176, April.
    7. Hung-Wei Lai & Cheng-Wei Chen & Chin-Sheng Huang, 2010. "Technical Analysis, Investment Psychology, and Liquidity Provision: Evidence from the Taiwan Stock Market," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 46(5), pages 18-38, September.
    8. Vasile Bratian & Claudiu Opreana & Amelia Bucur, 2017. "Evaluation of the Stock Quote Stochastic Approach, Market Efficiency and Technical Analysis," International Journal of Economics and Financial Issues, Econjournals, vol. 7(5), pages 307-316.
    9. Andrey Kudryavtsev, 2017. "The Effect of Preceding Sequences on Stock Returns," European Financial and Accounting Journal, Prague University of Economics and Business, vol. 2017(4), pages 83-96.
    10. J. Kung, James & Wong, Wing-Keung, 2009. "Profitability of Technical Analysis in the Singapore Stock Market: before and after the Asian Financial Crisis," Journal of Economic Integration, Center for Economic Integration, Sejong University, vol. 24, pages 135-150.
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    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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