IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v17y2016icp66-71.html
   My bibliography  Save this article

A test of the adaptive market hypothesis using a time-varying AR model in Japan

Author

Listed:
  • Noda, Akihiko

Abstract

This study examines the adaptive market hypothesis (AMH) in Japanese stock markets (TOPIX and TSE2). In particular, we measure the degree of market efficiency by using a time-varying model approach. The empirical results show that (1) the degree of market efficiency changes over time in the two markets, (2) the level of market efficiency of the TSE2 is lower than that of the TOPIX in most periods, and (3) the market efficiency of the TOPIX has evolved, but that of the TSE2 has not. We conclude that the results support the AMH for the more qualified stock market in Japan.

Suggested Citation

  • Noda, Akihiko, 2016. "A test of the adaptive market hypothesis using a time-varying AR model in Japan," Finance Research Letters, Elsevier, vol. 17(C), pages 66-71.
    • Handle: RePEc:eee:finlet:v:17:y:2016:i:c:p:66-71
    DOI: 10.1016/j.frl.2016.01.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612316000052
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2016.01.004?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 look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Kim, Jae H. & Shamsuddin, Abul, 2008. "Are Asian stock markets efficient? Evidence from new multiple variance ratio tests," Journal of Empirical Finance, Elsevier, vol. 15(3), pages 518-532, June.
    2. Rebecca Emerson & Stephen Hall & Anna Zalewska-Mitura, 1997. "Evolving Market Efficiency with an Application to Some Bulgarian Shares," Economic Change and Restructuring, Springer, vol. 30(2), pages 75-90, May.
    3. Gili Yen & Cheng-few Lee, 2008. "Efficient Market Hypothesis (EMH): Past, Present and Future," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 11(02), pages 305-329.
    4. Escanciano, J. Carlos & Velasco, Carlos, 2006. "Generalized spectral tests for the martingale difference hypothesis," Journal of Econometrics, Elsevier, vol. 134(1), pages 151-185, September.
    5. Escanciano, J. Carlos & Lobato, Ignacio N., 2009. "An automatic Portmanteau test for serial correlation," Journal of Econometrics, Elsevier, vol. 151(2), pages 140-149, August.
    6. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    7. Hansen, Bruce E., 1992. "Testing for parameter instability in linear models," Journal of Policy Modeling, Elsevier, vol. 14(4), pages 517-533, August.
    8. Lim, Kian-Ping & Kim, Jae H., 2011. "Trade openness and the informational efficiency of emerging stock markets," Economic Modelling, Elsevier, vol. 28(5), pages 2228-2238, September.
    9. Serena Ng & Pierre Perron, 2001. "LAG Length Selection and the Construction of Unit Root Tests with Good Size and Power," Econometrica, Econometric Society, vol. 69(6), pages 1519-1554, November.
    10. Zalewska-Mitura, Anna & Hall, Stephen G., 1999. "Examining the first stages of market performance: a test for evolving market efficiency," Economics Letters, Elsevier, vol. 64(1), pages 1-12, July.
    11. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2014. "International stock market efficiency: a non-Bayesian time-varying model approach," Applied Economics, Taylor & Francis Journals, vol. 46(23), pages 2744-2754, August.
    12. Choi, In, 1999. "Testing the Random Walk Hypothesis for Real Exchange Rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(3), pages 293-308, May-June.
    13. Ito, Mikio & Sugiyama, Shunsuke, 2009. "Measuring the degree of time varying market inefficiency," Economics Letters, Elsevier, vol. 103(1), pages 62-64, April.
    14. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    15. Kim, Jae H. & Shamsuddin, Abul & Lim, Kian-Ping, 2011. "Stock return predictability and the adaptive markets hypothesis: Evidence from century-long U.S. data," Journal of Empirical Finance, Elsevier, vol. 18(5), pages 868-879.
    16. 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.
    17. Kian-Ping Lim & Weiwei Luo & Jae H. Kim, 2013. "Are US stock index returns predictable? Evidence from automatic autocorrelation-based tests," Applied Economics, Taylor & Francis Journals, vol. 45(8), pages 953-962, March.
    18. Kian‐Ping Lim & Robert Brooks, 2011. "The Evolution Of Stock Market Efficiency Over Time: A Survey Of The Empirical Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 25(1), pages 69-108, February.
    19. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2016. "The evolution of stock market efficiency in the US: a non-Bayesian time-varying model approach," Applied Economics, Taylor & Francis Journals, vol. 48(7), pages 621-635, February.
    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. Kenichi Hirayama & Akihiko Noda, 2019. "Measuring the Time-Varying Market Efficiency in the Prewar Japanese Stock Market, 1924-1943," Papers 1911.04059, arXiv.org, revised Dec 2022.
    2. 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.
    3. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.
    4. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2016. "The evolution of stock market efficiency in the US: a non-Bayesian time-varying model approach," Applied Economics, Taylor & Francis Journals, vol. 48(7), pages 621-635, February.
    5. 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.
    6. Kim, Jae H. & Shamsuddin, Abul & Lim, Kian-Ping, 2011. "Stock return predictability and the adaptive markets hypothesis: Evidence from century-long U.S. data," Journal of Empirical Finance, Elsevier, vol. 18(5), pages 868-879.
    7. Dzung Phan Tran Trung & Hung Pham Quang, 2019. "Adaptive Market Hypothesis: Evidence from the Vietnamese Stock Market," JRFM, MDPI, vol. 12(2), pages 1-16, May.
    8. Akihiko Noda, 2021. "On the evolution of cryptocurrency market efficiency," Applied Economics Letters, Taylor & Francis Journals, vol. 28(6), pages 433-439, March.
    9. Maria Kulikova & Gennady Kulikov, 2023. "Estimation of market efficiency process within time-varying autoregressive models by extended Kalman filtering approach," Papers 2310.04125, arXiv.org.
    10. Charles, Amélie & Darné, Olivier & Kim, Jae H., 2012. "Exchange-rate return predictability and the adaptive markets hypothesis: Evidence from major foreign exchange rates," Journal of International Money and Finance, Elsevier, vol. 31(6), pages 1607-1626.
    11. Hill, Jonathan B. & Motegi, Kaiji, 2019. "Testing the white noise hypothesis of stock returns," Economic Modelling, Elsevier, vol. 76(C), pages 231-242.
    12. Urquhart, Andrew & McGroarty, Frank, 2016. "Are stock markets really efficient? Evidence of the adaptive market hypothesis," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 39-49.
    13. Mirzaee Ghazani, Majid & Khalili Araghi, Mansour, 2014. "Evaluation of the adaptive market hypothesis as an evolutionary perspective on market efficiency: Evidence from the Tehran stock exchange," Research in International Business and Finance, Elsevier, vol. 32(C), pages 50-59.
    14. Tran, Vu Le & Leirvik, Thomas, 2019. "A simple but powerful measure of market efficiency," Finance Research Letters, Elsevier, vol. 29(C), pages 141-151.
    15. Rahman, Md. Lutfur & Lee, Doowon & Shamsuddin, Abul, 2017. "Time-varying return predictability in South Asian equity markets," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 179-200.
    16. Jasman Tuyon & Zamri Ahmada, 2016. "Behavioural finance perspectives on Malaysian stock market efficiency," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 16(1), pages 43-61, March.
    17. Charfeddine, Lanouar & Khediri, Karim Ben & Aye, Goodness C. & Gupta, Rangan, 2018. "Time-varying efficiency of developed and emerging bond markets: Evidence from long-spans of historical data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 632-647.
    18. Mikio Ito & Kiyotaka Maeda & Akihiko Noda, 2018. "The futures premium and rice market efficiency in prewar Japan," Economic History Review, Economic History Society, vol. 71(3), pages 909-937, August.
    19. Nartea, Gilbert V. & Valera, Harold Glenn A. & Valera, Maria Luisa G., 2021. "Mean reversion in Asia-Pacific stock prices: New evidence from quantile unit root tests," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 214-230.
    20. Charfeddine, Lanouar & Khediri, Karim Ben, 2016. "Time varying market efficiency of the GCC stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 487-504.

    More about this item

    Keywords

    The adaptive market hypothesis; The efficient market hypothesis; Time-varying model approach; Degree of market efficiency;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • 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

    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:17:y:2016:i:c:p:66-71. 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.