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How rewarding is technical analysis in the Indian stock market?

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  • Subrata Kumar Mitra

Abstract

This paper analyses the profitability of moving average based trading rules in the Indian stock market using four stock index series. The study finds that most technical trading rules are able to capture the direction of market movements reasonably well and give significant positive returns both in long and short positions. But these returns cannot be exploited fully due to real world transaction costs. Although the transaction cost has come down over the years, various components of transaction costs due to the bid-ask spread, brokerage, etc. will never be zero. The trading rules based on short term moving averages may be able to detect trends in financial series very quickly, but those rules also generate a large number of trades causing higher transaction costs. Thus technical traders have to pay more attention to minimizing transaction costs while choosing a trading rule. Nevertheless, profit opportunities from technical analysis continue to remain an interesting and debatable issue in the Indian stock market.

Suggested Citation

  • Subrata Kumar Mitra, 2011. "How rewarding is technical analysis in the Indian stock market?," Quantitative Finance, Taylor & Francis Journals, vol. 11(2), pages 287-297.
    • Handle: RePEc:taf:quantf:v:11:y:2011:i:2:p:287-297
    DOI: 10.1080/14697680903493581
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    Citations

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    Cited by:

    1. Ghada A. Altarawneh & Ahmad B. Hassanat & Ahmad S. Tarawneh & Ahmad Abadleh & Malek Alrashidi & Mansoor Alghamdi, 2022. "Stock Price Forecasting for Jordan Insurance Companies Amid the COVID-19 Pandemic Utilizing Off-the-Shelf Technical Analysis Methods," Economies, MDPI, vol. 10(2), pages 1-18, February.
    2. Shangkun Deng & Zhihao Su & Yanmei Ren & Haoran Yu & Yingke Zhu & Chenyang Wei, 2022. "Can Japanese Candlestick Patterns be Profitable on the Component Stocks of the SSE50 Index?," SAGE Open, , vol. 12(3), pages 21582440221, August.
    3. 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.
    4. Wang, Lijun & An, Haizhong & Liu, Xiaojia & Huang, Xuan, 2016. "Selecting dynamic moving average trading rules in the crude oil futures market using a genetic approach," Applied Energy, Elsevier, vol. 162(C), pages 1608-1618.
    5. Salma Khand & Vivake Anand & Mohammad Nadeem Qureshi, 2020. "The Predictability and Profitability of Simple Moving Averages and Trading Range Breakout Rules in the Pakistan Stock Market," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 23(01), pages 1-38, March.
    6. Tsung-Hsun Lu & Yung-Ming Shiu, 2016. "Can 1-day candlestick patterns be profitable on the 30 component stocks of the DJIA?," Applied Economics, Taylor & Francis Journals, vol. 48(35), pages 3345-3354, July.
    7. Flavio Ivo Riedlinger & João Nicolau, 2020. "The Profitability in the FTSE 100 Index: A New Markov Chain Approach," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 27(1), pages 61-81, March.
    8. Eero P䴤ri & Mika Vilska, 2014. "Performance of moving average trading strategies over varying stock market conditions: the Finnish evidence," Applied Economics, Taylor & Francis Journals, vol. 46(24), pages 2851-2872, August.
    9. Farias Nazário, Rodolfo Toríbio & e Silva, Jéssica Lima & Sobreiro, Vinicius Amorim & Kimura, Herbert, 2017. "A literature review of technical analysis on stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 66(C), pages 115-126.
    10. Liu, Xiaojia & An, Haizhong & Wang, Lijun & Jia, Xiaoliang, 2017. "An integrated approach to optimize moving average rules in the EUA futures market based on particle swarm optimization and genetic algorithms," Applied Energy, Elsevier, vol. 185(P2), pages 1778-1787.
    11. Zhu, Hong & Jiang, Zhi-Qiang & Li, Sai-Ping & Zhou, Wei-Xing, 2015. "Profitability of simple technical trading rules of Chinese stock exchange indexes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 439(C), pages 75-84.

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