IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v19y2016icp173-180.html
   My bibliography  Save this article

Testing the adaptive market hypothesis and its determinants for the Indian stock markets

Author

Listed:
  • Hiremath, Gourishankar S.
  • Narayan, Seema

Abstract

We examine the adaptive market hypothesis using the Generalized Hurst exponent, derived using fixed and rolling windows. We find that the Indian stock market is moving towards efficiency. We also ascertain a positive and significant link between the Indian market's efficiency gap and financial crises, other international shocks and major domestic policy and crisis-related events. Net foreign institutional investment increases the efficiency gap, although the impact is less for international events. Foreign institutional investment and market microstructure factors do not influence efficiency in an emerging market. This evidence would benefit a stock market liberalization policy review.

Suggested Citation

  • Hiremath, Gourishankar S. & Narayan, Seema, 2016. "Testing the adaptive market hypothesis and its determinants for the Indian stock markets," Finance Research Letters, Elsevier, vol. 19(C), pages 173-180.
    • Handle: RePEc:eee:finlet:v:19:y:2016:i:c:p:173-180
    DOI: 10.1016/j.frl.2016.07.009
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612316301271
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2016.07.009?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Swati Ghosh & Ernesto Revilla, 2008. "Enhancing the efficiency of securities markets in East Asia," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 1(2), pages 249-268.
    2. Lei Jiang, 2011. "Order Imbalance, Liquidity, and Market Efficiency: Evidence from the Chinese Stock Market," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 32, pages 469-480, October.
    3. Cochrane, John H., 1991. "Volatility tests and efficient markets : A review essay," Journal of Monetary Economics, Elsevier, vol. 27(3), pages 463-485, June.
    4. Kaminsky, Graciela L. & Schmukler, Sergio L., 1999. "What triggers market jitters?: A chronicle of the Asian crisis," Journal of International Money and Finance, Elsevier, vol. 18(4), pages 537-560, August.
    5. Shiller, Robert J, 1981. "Do Stock Prices Move Too Much to be Justified by Subsequent Changes in Dividends?," American Economic Review, American Economic Association, vol. 71(3), pages 421-436, June.
    6. Reboredo, Juan C. & Rivera-Castro, Miguel A. & Miranda, José G.V. & García-Rubio, Raquel, 2013. "How fast do stock prices adjust to market efficiency? Evidence from a detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(7), pages 1631-1637.
    7. T. Di Matteo, 2007. "Multi-scaling in finance," Quantitative Finance, Taylor & Francis Journals, vol. 7(1), pages 21-36.
    8. Szafarz, Ariane, 2012. "Financial crises in efficient markets: How fundamentalists fuel volatility," Journal of Banking & Finance, Elsevier, vol. 36(1), pages 105-111.
    9. Chordia, Tarun & Roll, Richard & Subrahmanyam, Avanidhar, 2008. "Liquidity and market efficiency," Journal of Financial Economics, Elsevier, vol. 87(2), pages 249-268, February.
    10. Lagoarde-Segot, Thomas & Lucey, Brian M., 2008. "Efficiency in emerging markets--Evidence from the MENA region," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(1), pages 94-105, February.
    11. Graham, Michael & Peltomäki, Jarkko & Sturludóttir, Hildur, 2015. "Do capital controls affect stock market efficiency? Lessons from Iceland," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 82-88.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ashok Chanabasangouda Patil & Shailesh Rastogi, 2019. "Time-Varying Price–Volume Relationship and Adaptive Market Efficiency: A Survey of the Empirical Literature," JRFM, MDPI, vol. 12(2), pages 1-18, June.
    2. Shi, Yanlin & Ho, Kin-Yip, 2021. "News sentiment and states of stock return volatility: Evidence from long memory and discrete choice models," Finance Research Letters, Elsevier, vol. 38(C).
    3. Boya, Christophe M., 2019. "From efficient markets to adaptive markets: Evidence from the French stock exchange," Research in International Business and Finance, Elsevier, vol. 49(C), pages 156-165.
    4. Kumari, Jyoti & Mahakud, Jitendra & Hiremath, Gourishankar S., 2017. "Determinants of idiosyncratic volatility: Evidence from the Indian stock market," Research in International Business and Finance, Elsevier, vol. 41(C), pages 172-184.
    5. Jha, Chandan Kumar & Bhuyan, Rafiqul, 2020. "Do financial reforms promote entrepreneurship?," Finance Research Letters, Elsevier, vol. 34(C).
    6. Subhamitra Patra & Gourishankar S. Hiremath, 2022. "An Entropy Approach to Measure the Dynamic Stock Market Efficiency," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(2), pages 337-377, June.
    7. Deniz Erer & Elif Erer & Selim Güngör, 2023. "The aggregate and sectoral time-varying market efficiency during crisis periods in Turkey: a comparative analysis with COVID-19 outbreak and the global financial crisis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-25, December.
    8. Xiong, Xiong & Meng, Yongqiang & Li, Xiao & Shen, Dehua, 2019. "An empirical analysis of the Adaptive Market Hypothesis with calendar effects:Evidence from China," Finance Research Letters, Elsevier, vol. 31(C).
    9. Shahid, Muhammad Naeem & Azmi, Wajahat & Ali, Mohsin & Islam, Muhammad Umar & Rizvi, Syed Aun R., 2023. "Uncovering risk transmission between socially responsible investments, alternative energy investments and the implied volatility of major commodities," Energy Economics, Elsevier, vol. 120(C).
    10. Khuntia, Sashikanta & Pattanayak, J.K., 2020. "Adaptive long memory in volatility of intra-day bitcoin returns and the impact of trading volume," Finance Research Letters, Elsevier, vol. 32(C).
    11. Biswabhusan Bhuyan & Subhamitra Patra & Ranjan Kumar Bhuian, 2020. "Market Adaptability and Evolving Predictability of Stock Returns: An Evidence from India," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 27(4), pages 605-619, December.
    12. Liu, Jian & Cheng, Cheng & Yang, Xianglin & Yan, Lizhao & Lai, Yongzeng, 2019. "Analysis of the efficiency of Hong Kong REITs market based on Hurst exponent," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    13. Ferreira, Joaquim & Morais, Flávio, 2023. "Predict or to be predicted? A transfer entropy view between adaptive green markets, structural shocks and sentiment index," Finance Research Letters, Elsevier, vol. 56(C).
    14. Pınar Evrim Mandacı & F. Dilvin Taskın & Zeliha Can Ergun, 2019. "Adaptive Market Hypothesis," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(4), pages 84-101.
    15. Vogl, Markus, 2023. "Hurst exponent dynamics of S&P 500 returns: Implications for market efficiency, long memory, multifractality and financial crises predictability by application of a nonlinear dynamics analysis framewo," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    16. Ghazani, Majid Mirzaee & Ebrahimi, Seyed Babak, 2019. "Testing the adaptive market hypothesis as an evolutionary perspective on market efficiency: Evidence from the crude oil prices," Finance Research Letters, Elsevier, vol. 30(C), pages 60-68.
    17. Sashikanta Khuntia & J. K. Pattanayak, 2020. "Evolving Efficiency of Exchange Rate Movement: An Evidence from Indian Foreign Exchange Market," Global Business Review, International Management Institute, vol. 21(4), pages 956-969, August.
    18. Ailie Charteris & Conrad Alexander Steyn, 2023. "The Bank of Japan’s exchange traded fund purchases: a help or hindrance to market efficiency?," Journal of Asset Management, Palgrave Macmillan, vol. 24(3), pages 225-240, May.
    19. Mushinada, Venkata Narasimha Chary, 2020. "Are individual investors irrational or adaptive to market dynamics?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 25(C).
    20. Jitender Kumar & Neha Prince, 2022. "Overconfidence bias in the Indian stock market in diverse market situations: an empirical study," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(6), pages 3031-3047, December.
    21. Jiang, Jinjin & Li, Haiqi, 2020. "A new measure for market efficiency and its application," Finance Research Letters, Elsevier, vol. 34(C).
    22. Mostafa Raeisi Sarkandiz & Robabeh Bahlouli, 2019. "The Stock Market between Classical and Behavioral Hypotheses: An Empirical Investigation of the Warsaw Stock Exchange," Econometric Research in Finance, SGH Warsaw School of Economics, Collegium of Economic Analysis, vol. 4(2), pages 67-88, December.
    23. Khuntia, Sashikanta & Pattanayak, J.K., 2018. "Adaptive market hypothesis and evolving predictability of bitcoin," Economics Letters, Elsevier, vol. 167(C), pages 26-28.

    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. Hiremath, Gourishankar S. & Kattuman, Paul, 2017. "Foreign portfolio flows and emerging stock market: Is the midnight bell ringing in India?," Research in International Business and Finance, Elsevier, vol. 42(C), pages 544-558.
    2. Ryuichi Yamamoto, 2022. "Predictor Choice, Investor Types, and the Price Impact of Trades on the Tokyo Stock Exchange," Computational Economics, Springer;Society for Computational Economics, vol. 59(1), pages 325-356, January.
    3. Ariane Szafarz, 2015. "Market Efficiency and Crises:Don’t Throw the Baby out with the Bathwater," Bankers, Markets & Investors, ESKA Publishing, issue 139, pages 20-26, November-.
    4. John H. Cochrane, 1999. "New facts in finance," Economic Perspectives, Federal Reserve Bank of Chicago, vol. 23(Q III), pages 36-58.
    5. Campbell, John Y., 2001. "Why long horizons? A study of power against persistent alternatives," Journal of Empirical Finance, Elsevier, vol. 8(5), pages 459-491, December.
    6. Eugene N. White, 2004. "Bubbles and Busts: The 1990s in the Mirror of the 1920s," FRU Working Papers 2004/09, University of Copenhagen. Department of Economics. Finance Research Unit.
    7. David Gruen, 1995. "Financial Market Volatility and the World-wide Fall in Inflation," RBA Research Discussion Papers rdp9513, Reserve Bank of Australia.
    8. Nathan S. Balke & Mark E. Wohar, 2006. "What Drives Stock Prices? Identifying the Determinants of Stock Price Movements," Southern Economic Journal, John Wiley & Sons, vol. 73(1), pages 55-78, July.
    9. Wang, Yuming & Ma, Jinpeng, 2014. "Excess volatility and the cross-section of stock returns," The North American Journal of Economics and Finance, Elsevier, vol. 27(C), pages 1-16.
    10. John H. Cochrane, 2017. "Macro-Finance," Review of Finance, European Finance Association, vol. 21(3), pages 945-985.
    11. Adam Karp & Gary Van Vuuren, 2019. "Investment Implications Of The Fractal Market Hypothesis," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 14(01), pages 1-27, March.
    12. John Y. Campbell & John Cochrane, 1999. "Force of Habit: A Consumption-Based Explanation of Aggregate Stock Market Behavior," Journal of Political Economy, University of Chicago Press, vol. 107(2), pages 205-251, April.
    13. Brière, Marie & Chapelle, Ariane & Szafarz, Ariane, 2012. "No contagion, only globalization and flight to quality," Journal of International Money and Finance, Elsevier, vol. 31(6), pages 1729-1744.
    14. John H. Cochrane, 2008. "The Dog That Did Not Bark: A Defense of Return Predictability," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1533-1575, July.
    15. Bernard Dumas & Alexander Kurshev & Raman Uppal, 2005. "What Can Rational Investors Do About Excessive Volatility and Sentiment Fluctuations?," NBER Working Papers 11803, National Bureau of Economic Research, Inc.
    16. Tim Bollerslev & Robert J. Hodrick, 1992. "Financial Market Efficiency Tests," NBER Working Papers 4108, National Bureau of Economic Research, Inc.
    17. Berardi, Michele, 2021. "Uncertainty, sentiments and time-varying risk premia," MPRA Paper 106922, University Library of Munich, Germany.
    18. Matthijs Lof, 2015. "Rational Speculators, Contrarians, and Excess Volatility," Management Science, INFORMS, vol. 61(8), pages 1889-1901, August.
    19. Iwatsubo, Kentaro & Watkins, Clinton & Xu, Tao, 2018. "Intraday seasonality in efficiency, liquidity, volatility and volume: Platinum and gold futures in Tokyo and New York," Journal of Commodity Markets, Elsevier, vol. 11(C), pages 59-71.
    20. Garcia, M.M. & Machado Pereira, A.C. & Acebal, J.L. & Bosco de Magalhães, A.R., 2020. "Forecast model for financial time series: An approach based on harmonic oscillators," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).

    More about this item

    Keywords

    Time-varying efficiency; Adaptive market hypothesis; Financial liberalization; Economic crisis; Market microstructure; International capital flows; India;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

    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:eee:finlet:v:19:y:2016:i:c:p:173-180. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .

    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.