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How profitable is the Indian stock market?

Author

Listed:
  • Narayan, Paresh Kumar
  • Ali Ahmed, Huson
  • Sharma, Susan Sunila
  • Prabheesh, K. P.

Abstract

In this paper, using a range of technical trading and momentum trading strategies, we show that the Indian stock market is profitable. We find robust evidence that investing in some sectors is relatively more profitable than investing in others. We show that sectoral heterogeneity with respect to profitability is a result of the gradual diffusion of information from the market to the sectors. Specifically, we show that while the market predicts returns of sectors, the magnitude of predictability varies with sectors. Our results are robust to a range of trading strategies.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Narayan, Paresh Kumar & Ali Ahmed, Huson & Sharma, Susan Sunila & Prabheesh, K. P., 2014. "How profitable is the Indian stock market?," Working Papers fe_2014_14, Deakin University, Department of Economics.
  • Handle: RePEc:dkn:ecomet:fe_2014_14
    DOI: 10.1016/j.pacfin.2014.07.001
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    Cited by:

    1. Xue, Wen-Jun & Zhang, Li-Wen, 2017. "Stock return autocorrelations and predictability in the Chinese stock market—Evidence from threshold quantile autoregressive models," Economic Modelling, Elsevier, vol. 60(C), pages 391-401.
    2. Chui, Andy & Ranganathan, Kavitha & Rohit, Abhishek & Veeraraghavan, Madhu, 2023. "Momentum, reversals and liquidity: Indian evidence," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).
    3. Narayan, Paresh Kumar & Ahmed, Huson Ali, 2014. "Importance of skewness in decision making: Evidence from the Indian stock exchange," Global Finance Journal, Elsevier, vol. 25(3), pages 260-269.
    4. 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.
    5. Rizvi, Syed Aun R. & Arshad, Shaista, 2018. "Understanding time-varying systematic risks in Islamic and conventional sectoral indices," Economic Modelling, Elsevier, vol. 70(C), pages 561-570.
    6. Narayan, Paresh Kumar & Bannigidadmath, Deepa, 2015. "Are Indian stock returns predictable?," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 506-531.
    7. Yang, Yunlin & Gebka, Bartosz & Hudson, Robert, 2019. "Momentum effects in China: A review of the literature and an empirical explanation of prevailing controversies," Research in International Business and Finance, Elsevier, vol. 47(C), pages 78-101.
    8. Bannigidadmath, Deepa & Narayan, Paresh Kumar, 2016. "Stock return predictability and determinants of predictability and profits," Emerging Markets Review, Elsevier, vol. 26(C), pages 153-173.
    9. Supriya Maheshwari & Raj S. Dhankar, 2017. "The Effect of Global Crises on Momentum Profitability: Evidence from the Indian Stock Market," Vision, , vol. 21(1), pages 1-12, March.
    10. Sarwar, Suleman & Tiwari, Aviral Kumar & Tingqiu, Cao, 2020. "Analyzing volatility spillovers between oil market and Asian stock markets," Resources Policy, Elsevier, vol. 66(C).
    11. Wen-Jun Xue & Li-Wen Zhang, 2016. "Stock Return Autocorrelations and Predictability in the Chinese Stock Market: Evidence from Threshold Quantile Autoregressive Models," Working Papers 1605, Florida International University, Department of Economics.
    12. Ahmad, Nasir & Rehman, Mobeen Ur & Vo, Xuan Vinh & Kang, Sang Hoon, 2022. "Does inter-region portfolio diversification pay more than the international diversification?," The Quarterly Review of Economics and Finance, Elsevier, vol. 83(C), pages 26-35.
    13. Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Tran, Vuong Thao, 2018. "Can economic policy uncertainty predict stock returns? Global evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 55(C), pages 134-150.
    14. Sharma, Susan Sunila, 2016. "Can consumer price index predict gold price returns?," Economic Modelling, Elsevier, vol. 55(C), pages 269-278.
    15. Nedumparambil, Elizabeth & Bhandari, Anup Kumar, 2020. "Credit risk – Return puzzle: Evidence from India," Economic Modelling, Elsevier, vol. 92(C), pages 195-206.
    16. Tan, Siow-Hooi & Lai, Ming-Ming & Tey, Eng-Xin & Chong, Lee-Lee, 2020. "Testing the performance of technical analysis and sentiment-TAR trading rules in the Malaysian stock market," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    17. Narayan, Paresh Kumar & Narayan, Seema & Westerlund, Joakim, 2015. "Do order imbalances predict Chinese stock returns? New evidence from intraday data," Pacific-Basin Finance Journal, Elsevier, vol. 34(C), pages 136-151.
    18. Bruce Vanstone & Tobias Hahn & Dean Earea, 2021. "Industry momentum: an exchange‐traded funds approach," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(3), pages 4007-4024, September.
    19. Narayan, Paresh Kumar & Phan, Dinh Hoang Bach & Bannigidadmath, Deepa, 2017. "Is the profitability of Indian stocks compensation for risks?," Emerging Markets Review, Elsevier, vol. 31(C), pages 47-64.
    20. Shah Saeed Hassan Chowdhury & Rashida Sharmin & M Arifur Rahman, 2019. "Presence and Sources of Contrarian Profits in the Bangladesh Stock Market," Global Business Review, International Management Institute, vol. 20(1), pages 84-104, February.
    21. Chen-Yin Kuo, 2018. "Are the forecast errors of stock prices related to the degree of accounting conservatism?," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 8(6), pages 1-9.

    More about this item

    Keywords

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    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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