IDEAS home Printed from https://ideas.repec.org/a/ods/journl/v9y2020i1p22-27.html
   My bibliography  Save this article

Testing the Binomial Model in the Indian Stock Market

Author

Listed:
  • Mihir Dash

    (Alliance University, India)

Abstract

This study examines a consequence of the Random Walk Hypothesis for stock prices. If stock price movements were random, it would imply that the number of forward movements of the stock price in the course of a week would follow a binomial distribution. This is the binomial model for stock price movements/returns. The study examines the binomial model for twenty major stocks from the Indian banking sector. The stock price data was collected from the National Stock Exchange (NSE). The study period selected was Apr. 1, 2009 to Mar. 31, 2019, a period of ten years. The results of the study do not support the RWH, as the Bin(n = 4, p = ½) distribution was rejected for a large proportion of sample stocks. However, the results may not be generalizable, as they are based on a small sample of stocks from the banking sector, for a period of only ten years, and perhaps they were affected by the ‘Modi Effects’ - both positive and negative. A more detailed study, with stocks from different industries, with a wider range of size/capitalisation, and for a longer study period, should be used to replicate/validate the results.

Suggested Citation

  • Mihir Dash, 2020. "Testing the Binomial Model in the Indian Stock Market," Journal of Applied Management and Investments, Department of Business Administration and Corporate Security, International Humanitarian University, vol. 9(1), pages 22-27, March.
    • Handle: RePEc:ods:journl:v:9:y:2020:i:1:p:22-27
    as

    Download full text from publisher

    File URL: http://www.jami.org.ua/Papers/JAMI_9_1_2020_22-27.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Smidt, Seymour, 1968. "A New Look at the Random Walk Hypothesis," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 3(3), pages 235-261, September.
    2. Vijai Anand & Tapal Dulababu, 2012. "The random walk hypothesis: a research study on selected banks," Journal of Applied Management and Investments, Department of Business Administration and Corporate Security, International Humanitarian University, vol. 1(1), pages 67-70.
    3. Yoon Hong & Ji-chul Lee & Guoping Ding, 2017. "Volatility Clustering, New Heavy-Tailed Distribution and the Stock Market Returns in South Korea," Journal of Applied Management and Investments, Department of Business Administration and Corporate Security, International Humanitarian University, vol. 6(3), pages 164-169, September.
    4. Dash, M., 2019. "Testing the Random Walk Hypothesis in the Indian Stock Market Using ARIMA Modelling," Journal of Applied Management and Investments, Department of Business Administration and Corporate Security, International Humanitarian University, vol. 8(2), pages 71-77, May.
    5. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    6. Jensen, Michael C & Bennington, George A, 1970. "Random Walks and Technical Theories: Some Additional Evidence," Journal of Finance, American Finance Association, vol. 25(2), pages 469-482, May.
    7. Evans, John L., 1968. "The Random Walk Hypothesis, Portfolio Analysis and the Buy-and-Hold Criterion*," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 3(3), pages 327-342, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dash, M., 2019. "Testing the Random Walk Hypothesis in the Indian Stock Market Using ARIMA Modelling," Journal of Applied Management and Investments, Department of Business Administration and Corporate Security, International Humanitarian University, vol. 8(2), pages 71-77, May.
    2. Kapil Gupta & Balwinder Singh, 2009. "Information Memory and Pricing Efficiency of Futures Contracts," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 8(2), pages 191-250, May.
    3. Meredith Beechey & David Gruen & James Vickery, 2000. "The Efficient Market Hypothesis: A Survey," RBA Research Discussion Papers rdp2000-01, Reserve Bank of Australia.
    4. Erdemlioglu, Deniz & Petitjean, Mikael & Vargas, Nicolas, 2021. "Market instability and technical trading at high frequency: Evidence from NASDAQ stocks," Economic Modelling, Elsevier, vol. 102(C).
    5. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, November.
    6. Michael McAleer & John Suen & Wing Keung Wong, 2016. "Profiteering from the Dot-Com Bubble, Subprime Crisis and Asian Financial Crisis," The Japanese Economic Review, Japanese Economic Association, vol. 67(3), pages 257-279, September.
    7. B.S. Bodla, 2005. "Efficiency of the Indian Capital Market: An Empirical Work," Vision, , vol. 9(3), pages 55-63, July.
    8. Jin, Xiaoye, 2021. "What do we know about the popularity of technical analysis in foreign exchange markets? A skewness preference perspective," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 71(C).
    9. Yi-Chi Tsai & Cheng-Yih Hong, 2017. "The Application of Genetic Programming on the Stock Movement Forecasting System," International Journal of Economics and Financial Issues, Econjournals, vol. 7(6), pages 68-73.
    10. Fengmin Xu & Jieao Ma, 2023. "Intelligent option portfolio model with perspective of shadow price and risk-free profit," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-28, December.
    11. Stefán B. Gunnlaugsson, 2018. "Trading Rules On A Small Stock Market," Oradea Journal of Business and Economics, University of Oradea, Faculty of Economics, vol. 3(1), pages 46-55, March.
    12. Taylor, Mark & Hsu, Po-Hsuan, 2014. "Forty Years, Thirty Currencies and 21,000 Trading Rules: A Large-scale, Data-Snooping Robust Analysis of Technical Trading in t," CEPR Discussion Papers 10018, C.E.P.R. Discussion Papers.
    13. Serafini, Daniel Guedine & Pereira, Pedro L. Valls, 2010. "Sistemas técnicos de trading no mercado de ações brasileiro: testando a hipótese de eficiência de mercado em sua forma fraca e avaliando se a análise técnica agrega valor," Textos para discussão 260, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    14. Marshall, Ben R. & Cahan, Rochester H., 2005. "Is technical analysis profitable on a stock market which has characteristics that suggest it may be inefficient?," Research in International Business and Finance, Elsevier, vol. 19(3), pages 384-398, September.
    15. Nauzer Balsara & Jason Chen & Lin Zheng, 2009. "Profiting from a contrarian application of technical trading rules in the US stock market," Journal of Asset Management, Palgrave Macmillan, vol. 10(2), pages 97-123, June.
    16. Terence Tai-Leung Chong & Wing-Kam Ng & Venus Khim-Sen Liew, 2014. "Revisiting the Performance of MACD and RSI Oscillators," JRFM, MDPI, vol. 7(1), pages 1-12, February.
    17. Kung, James J. & Wu, E-Ching, 2013. "An evaluation of some popular investment strategies under stochastic interest rates," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 96-108.
    18. 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.
    19. Yung-Ho Chang & Massoud Metghalchi & Chia-Chung Chan, 2006. "Technical trading strategies and cross-national information linkage: the case of Taiwan stock market," Applied Financial Economics, Taylor & Francis Journals, vol. 16(10), pages 731-743.
    20. Yi-Chein Chiang & Mei-Chu Ke & Tung Liang Liao & Cin-Dian Wang, 2012. "Are technical trading strategies still profitable? Evidence from the Taiwan Stock Index Futures Market," Applied Financial Economics, Taylor & Francis Journals, vol. 22(12), pages 955-965, June.

    More about this item

    Keywords

    Random Walk Hypothesis; binomial model; banking sector; National Stock Exchange;
    All these keywords.

    JEL classification:

    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ods:journl:v:9:y:2020:i:1:p:22-27. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Anatoliy G. Goncharuk (email available below). General contact details of provider: https://edirc.repec.org/data/dmonaua.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.