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Mikio Ito

Personal Details

First Name:Mikio
Middle Name:
Last Name:Ito
Suffix:
RePEc Short-ID:pit28
[This author has chosen not to make the email address public]

Affiliation

Faculty of Economics
Keio University

Tokyo, Japan
http://www.econ.keio.ac.jp/

: 81-3-3453-4511

2-15-45, Mita, Minato-ku, Tokyo 108-8345
RePEc:edi:fekeijp (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Mikio Ito & Kiyotaka Maeda & Akihiko Noda, 2016. "Market Integration in the Prewar Japanese Rice Markets," Papers 1604.00148, arXiv.org, revised Sep 2017.
  2. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2016. "Time-Varying Comovement of Foreign Exchange Markets," Papers 1610.04334, arXiv.org.
  3. Mikio Ito & Kiyotaka Maeda & Akihiko Noda, 2014. "Market Efficiency and Government Interventions in Prewar Japanese Rice Futures Markets," Papers 1404.1164, arXiv.org, revised Feb 2017.
  4. Mikio Ito & Kiyotaka Maeda & Akihiko Noda, 2014. "The Futures Premium and Rice Market Efficiency in Prewar Japan," Papers 1404.5381, arXiv.org, revised Sep 2017.
  5. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2012. "International Stock Market Efficiency: A Non-Bayesian Time-Varying Model Approach," Papers 1203.5176, arXiv.org, revised May 2014.
  6. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2012. "The Evolution of Stock Market Efficiency in the US: A Non-Bayesian Time-Varying Model Approach," Papers 1202.0100, arXiv.org, revised Aug 2015.
  7. Mikio Ito & Akihiko Noda, 2010. "The GEL Estimates Resolve the Risk-free Rate Puzzle in Japan," Keio/Kyoto Joint Global COE Discussion Paper Series 2010-007, Keio/Kyoto Joint Global COE Program.

Articles

  1. 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.
  2. 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.
  3. Mikio Ito & Akihiko Noda, 2012. "The GEL estimates resolve the risk-free rate puzzle in Japan," Applied Financial Economics, Taylor & Francis Journals, vol. 22(5), pages 365-374, March.
  4. Ito, Mikio & Sugiyama, Shunsuke, 2009. "Measuring the degree of time varying market inefficiency," Economics Letters, Elsevier, vol. 103(1), pages 62-64, April.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Mikio Ito & Kiyotaka Maeda & Akihiko Noda, 2014. "Market Efficiency and Government Interventions in Prewar Japanese Rice Futures Markets," Papers 1404.1164, arXiv.org, revised Feb 2017.

    Cited by:

    1. 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.

  2. Mikio Ito & Kiyotaka Maeda & Akihiko Noda, 2014. "The Futures Premium and Rice Market Efficiency in Prewar Japan," Papers 1404.5381, arXiv.org, revised Sep 2017.

    Cited by:

    1. Mikio Ito & Kiyotaka Maeda & Akihiko Noda, 2017. "Discretion versus Policy Rules in Futures Markets: A Case of the Osaka-Dojima Rice Exchange, 1914-1939," Papers 1704.00985, arXiv.org, revised Jan 2018.
    2. Mikio Ito & Kiyotaka Maeda & Akihiko Noda, 2016. "Market Integration in the Prewar Japanese Rice Markets," Papers 1604.00148, arXiv.org, revised Sep 2017.

  3. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2012. "International Stock Market Efficiency: A Non-Bayesian Time-Varying Model Approach," Papers 1203.5176, arXiv.org, revised May 2014.

    Cited by:

    1. Vieito, João Paulo & Wong, Wing-Keung & Zhu, Zhenzhen, 2015. "Could the global financial crisis improve the performance of the G7 stocks markets?," MPRA Paper 66521, University Library of Munich, Germany.
    2. 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.
    3. 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.
    4. Dzung Phan Tran Trung & Hung Pham Quang, 2019. "Adaptive Market Hypothesis: Evidence from the Vietnamese Stock Market," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 12(2), pages 1-16, May.
    5. 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.
    6. 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.
    7. Achal Awasthi & Oleg Malafeyev, 2015. "Is the Indian Stock Market efficient - A comprehensive study of Bombay Stock Exchange Indices," Papers 1510.03704, arXiv.org.
    8. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2017. "An Alternative Estimation Method of a Time-Varying Parameter Model," Papers 1707.06837, arXiv.org, revised Dec 2017.
    9. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2016. "Time-Varying Comovement of Foreign Exchange Markets," Papers 1610.04334, arXiv.org.

  4. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2012. "The Evolution of Stock Market Efficiency in the US: A Non-Bayesian Time-Varying Model Approach," Papers 1202.0100, arXiv.org, revised Aug 2015.

    Cited by:

    1. Richard S.Grossman, 2017. "Stocks for the Long Run: New Monthly Indices of British Equities, 1869-1929," Wesleyan Economics Working Papers 2017-004, Wesleyan University, Department of Economics.
    2. Taylor, Nick, 2014. "The rise and fall of technical trading rule success," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 286-302.
    3. 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.
    4. 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.
    5. Mikio Ito & Kiyotaka Maeda & Akihiko Noda, 2017. "Discretion versus Policy Rules in Futures Markets: A Case of the Osaka-Dojima Rice Exchange, 1914-1939," Papers 1704.00985, arXiv.org, revised Jan 2018.
    6. Campbell, Gareth & Grossman, Richard S. & Turner, John D., 2019. "Before the cult of equity: New monthly indices of the British share market, 1829-1929," QUCEH Working Paper Series 2019-01, Queen's University Belfast, Queen's University Centre for Economic History.
    7. Dzung Phan Tran Trung & Hung Pham Quang, 2019. "Adaptive Market Hypothesis: Evidence from the Vietnamese Stock Market," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 12(2), pages 1-16, May.
    8. Mikio Ito & Kiyotaka Maeda & Akihiko Noda, 2014. "Market Efficiency and Government Interventions in Prewar Japanese Rice Futures Markets," Papers 1404.1164, arXiv.org, revised Feb 2017.
    9. 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.
    10. 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.
    11. Kalugala Vidanalage Aruna Shantha, 2019. "Individual Investors’ Learning Behavior and Its Impact on Their Herd Bias: An Integrated Analysis in the Context of Stock Trading," Sustainability, MDPI, Open Access Journal, vol. 11(5), pages 1-24, March.
    12. Gareth Campbell & Richard S.Grossman & John D. Turner, 2019. "Before the Cult of Equity:New Monthly Indices of the British Share Market, 1829-1929," Wesleyan Economics Working Papers 2019-003, Wesleyan University, Department of Economics.
    13. 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.
    14. Campbell, Gareth & Grossman, Richard & Turner, John, 2019. "Before the Cult of Equity: New Monthly Indices of the British Share Market, 1829-1929," CEPR Discussion Papers 13717, C.E.P.R. Discussion Papers.

Articles

  1. 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.
    See citations under working paper version above.
  2. 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.
    See citations under working paper version above.
  3. Ito, Mikio & Sugiyama, Shunsuke, 2009. "Measuring the degree of time varying market inefficiency," Economics Letters, Elsevier, vol. 103(1), pages 62-64, April.

    Cited by:

    1. Graham Smith & Aneta Dyakova, 2014. "African Stock Markets: Efficiency and Relative Predictability," South African Journal of Economics, Economic Society of South Africa, vol. 82(2), pages 258-275, June.
    2. Bariviera, Aurelio F., 2017. "The inefficiency of Bitcoin revisited: A dynamic approach," Economics Letters, Elsevier, vol. 161(C), pages 1-4.
    3. 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.
    4. Mobarek, Asma & Fiorante, Angelo, 2014. "The prospects of BRIC countries: Testing weak-form market efficiency," Research in International Business and Finance, Elsevier, vol. 30(C), pages 217-232.
    5. Hiremath, Gourishankar S & Kumari, Jyoti, 2014. "Stock returns predictability and the adaptive market hypothesis in emerging markets: evidence from India," MPRA Paper 58378, University Library of Munich, Germany.
    6. 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.
    7. Bariviera, A.F. & Guercio, M. Belén & Martinez, Lisana B., 2012. "A comparative analysis of the informational efficiency of the fixed income market in seven European countries," Economics Letters, Elsevier, vol. 116(3), pages 426-428.
    8. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2012. "The Evolution of Stock Market Efficiency in the US: A Non-Bayesian Time-Varying Model Approach," Papers 1202.0100, arXiv.org, revised Aug 2015.
    9. Hiremath, Gourishankar S & Kumari, Jyoti, 2013. "Stock Returns Predictability and the Adaptive Market Hypothesis: Evidence from India," MPRA Paper 52581, University Library of Munich, Germany.
    10. Pawan Jain & Wen-Jun Xue, 2017. "Global Investigation of Return Autocorrelation and its Determinants," Working Papers 1704, Florida International University, Department of Economics.
    11. Alda, Mercedes, 2017. "The relationship between pension funds and the stock market: Does the aging population of Europe affect it?," International Review of Financial Analysis, Elsevier, vol. 49(C), pages 83-97.
    12. Urquhart, Andrew & McGroarty, Frank, 2014. "Calendar effects, market conditions and the Adaptive Market Hypothesis: Evidence from long-run U.S. data," International Review of Financial Analysis, Elsevier, vol. 35(C), pages 154-166.
    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. Urquhart, Andrew & Hudson, Robert, 2013. "Efficient or adaptive markets? Evidence from major stock markets using very long run historic data," International Review of Financial Analysis, Elsevier, vol. 28(C), pages 130-142.
    15. Aneta Dyakova & Graham Smith, 2013. "The evolution of stock market predictability in Bulgaria," Applied Financial Economics, Taylor & Francis Journals, vol. 23(9), pages 805-816, May.
    16. Dzung Phan Tran Trung & Hung Pham Quang, 2019. "Adaptive Market Hypothesis: Evidence from the Vietnamese Stock Market," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 12(2), pages 1-16, May.
    17. Semei Coronado-Ram'irez & Pedro Celso-Arellano & Omar Rojas, 2014. "Adaptive Market Efficiency of Agricultural Commodity Futures Contracts," Papers 1412.8017, arXiv.org, revised Mar 2015.
    18. Alvarez-Ramirez, Jose & Rodriguez, Eduardo & Alvarez, Jesus, 2012. "A multiscale entropy approach for market efficiency," International Review of Financial Analysis, Elsevier, vol. 21(C), pages 64-69.
    19. 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.
    20. Al-Khazali, Osamah & Mirzaei, Ali, 2017. "Stock market anomalies, market efficiency and the adaptive market hypothesis: Evidence from Islamic stock indices," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 51(C), pages 190-208.
    21. Wang, Zi-Mei & Chiao, Chaoshin & Chang, Ya-Ting, 2012. "Technical analyses and order submission behaviors: Evidence from an emerging market," International Review of Economics & Finance, Elsevier, vol. 24(C), pages 109-128.
    22. Jiang, Jiaqi & Gu, Rongbao, 2016. "Using Rényi parameter to improve the predictive power of singular value decomposition entropy on stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 254-264.
    23. Urquhart, Andrew & Gebka, Bartosz & Hudson, Robert, 2015. "How exactly do markets adapt? Evidence from the moving average rule in three developed markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 38(C), pages 127-147.
    24. Huai-Long Shi & Zhi-Qiang Jiang & Wei-Xing Zhou, 2016. "Time-varying return predictability in the Chinese stock market," Papers 1611.04090, arXiv.org.
    25. Kuang-Ting Chen, 2015. "Modeling Market Inefficiencies within a Single Instrument," Papers 1511.02046, arXiv.org.
    26. Shahzad, Syed Jawad Hussain & Hernandez, Jose Areola & Hanif, Waqas & Kayani, Ghulam Mujtaba, 2018. "Intraday return inefficiency and long memory in the volatilities of forex markets and the role of trading volume," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 433-450.
    27. Kinga Niemczak & Graham Smith, 2013. "Middle Eastern stock markets: absolute, evolving and relative efficiency," Applied Financial Economics, Taylor & Francis Journals, vol. 23(3), pages 181-198, February.
    28. Jain, Pawan & Xue, Wenjun, 2017. "Global investigation of return autocorrelation and its determinants," Pacific-Basin Finance Journal, Elsevier, vol. 43(C), pages 200-217.
    29. Graham Smith & Aneta Dyakova, 2016. "The Relative Predictability of Stock Markets in the Americas," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 21(2), pages 131-142, April.
    30. 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.
    31. Siokis, Fotios M., 2018. "Credit market Jitters in the course of the financial crisis: A permutation entropy approach in measuring informational efficiency in financial assets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 266-275.
    32. Mobarek, Asma & Mollah, Sabur & Keasey, Kevin, 2014. "A cross-country analysis of herd behavior in Europe," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 32(C), pages 107-127.
    33. 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.
    34. Godfrey, Keith R.L., 2017. "Toward a model-free measure of market efficiency," Pacific-Basin Finance Journal, Elsevier, vol. 44(C), pages 97-112.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 5 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-HIS: Business, Economic & Financial History (3) 2014-04-11 2014-05-09 2016-05-08
  2. NEP-ETS: Econometric Time Series (2) 2012-02-15 2016-10-23
  3. NEP-CWA: Central & Western Asia (1) 2012-02-15
  4. NEP-GER: German Papers (1) 2014-04-11
  5. NEP-PKE: Post Keynesian Economics (1) 2016-05-08

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