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Akihiko Noda

Personal Details

First Name:Akihiko
Middle Name:
Last Name:Noda
Suffix:
RePEc Short-ID:pno127
[This author has chosen not to make the email address public]
http://at-noda.com/

Affiliation

(20%) Keio Economic Observatory
Keio University

Tokyo, Japan
http://www.sanken.keio.ac.jp/
RePEc:edi:keokejp (more details at EDIRC)

(80%) School of Commerce
Meiji University

Tokyo, Japan
http://www.meiji.ac.jp/shogaku/
RePEc:edi:scmeijp (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Koichiro Moriya & Akihiko Noda, 2023. "On the Time-Varying Structure of the Arbitrage Pricing Theory using the Japanese Sector Indices," Papers 2305.05998, arXiv.org, revised Mar 2024.
  2. Akihiko Noda, 2022. "Estimating the Time-Varying Structures of the Fama-French Multi-Factor Models," Papers 2208.01270, arXiv.org.
  3. Akihiko Noda, 2021. "Examining the Dynamic Asset Market Linkages under the COVID-19 Global Pandemic," Papers 2109.02933, arXiv.org, revised Sep 2021.
  4. Kenichi Hirayama & Akihiko Noda, 2020. "Evaluating the Financial Market Function in Prewar Japan using a Time-Varying Parameter Model," Papers 2008.00860, arXiv.org, revised Jun 2021.
  5. Akihiko Noda, 2019. "On the Evolution of Cryptocurrency Market Efficiency," Papers 1904.09403, arXiv.org, revised Jul 2020.
  6. 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.
  7. 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.
  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 & Kiyotaka Maeda & Akihiko Noda, 2016. "Market Integration in the Prewar Japanese Rice Markets," Papers 1604.00148, arXiv.org, revised Sep 2017.
  10. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2016. "Time-Varying Comovement of Foreign Exchange Markets," Papers 1610.04334, arXiv.org.
  11. 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.
  12. 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.
  13. 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.
  14. 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.
  15. Akihiko Noda, 2012. "A Test of the Adaptive Market Hypothesis using a Time-Varying AR Model in Japan," Papers 1207.1842, arXiv.org, revised Jan 2016.
  16. Kazuki Kamimura & Akihiko Noda, 2010. "Addictive Behavior of Japanese Husbands and Wives," Keio/Kyoto Joint Global COE Discussion Paper Series 2010-016, Keio/Kyoto Joint Global COE Program.
  17. 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, 2022. "An Alternative Estimation Method for Time-Varying Parameter Models," Econometrics, MDPI, vol. 10(2), pages 1-27, April.
  2. Akihiko Noda, 2021. "On the evolution of cryptocurrency market efficiency," Applied Economics Letters, Taylor & Francis Journals, vol. 28(6), pages 433-439, March.
  3. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2021. "Time-Varying Comovement of Foreign Exchange Markets: A GLS-Based Time-Varying Model Approach," Mathematics, MDPI, vol. 9(8), pages 1-13, April.
  4. 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.
  5. 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.
  6. Ito, Mikio & Maeda, Kiyotaka & Noda, Akihiko, 2016. "Market efficiency and government interventions in prewar Japanese rice futures markets," Financial History Review, Cambridge University Press, vol. 23(3), pages 325-346, December.
  7. 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.
  8. 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.
  9. Akihiko Noda, 2011. "Testing the "Catching up with the Joneses" Model with Consumption Externality in Japan," Economics Bulletin, AccessEcon, vol. 31(2), pages 1648-1658.
  10. Akihiko Noda & Shunsuke Sugiyama, 2010. "Measuring the Intertemporal Elasticity of Substitution for Consumption: Some Evidence from Japan," Economics Bulletin, AccessEcon, vol. 30(1), pages 524-533.
    RePEc:taf:apfiec:v:22:y:2012:i:5:p:365-374 is not listed on IDEAS

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. Akihiko Noda, 2019. "On the Evolution of Cryptocurrency Market Efficiency," Papers 1904.09403, arXiv.org, revised Jul 2020.

    Cited by:

    1. Assaf, Ata & Bhandari, Avishek & Charif, Husni & Demir, Ender, 2022. "Multivariate long memory structure in the cryptocurrency market: The impact of COVID-19," International Review of Financial Analysis, Elsevier, vol. 82(C).
    2. Ata Assaf & Luis Alberiko Gil-Alana & Khaled Mokni, 2022. "True or spurious long memory in the cryptocurrency markets: evidence from a multivariate test and other Whittle estimation methods," Empirical Economics, Springer, vol. 63(3), pages 1543-1570, September.
    3. Ayoub Ammy-Driss & Matthieu Garcin, 2021. "Efficiency of the financial markets during the COVID-19 crisis: time-varying parameters of fractional stable dynamics," Working Papers hal-02903655, HAL.
    4. Virginie Terraza & Aslı Boru İpek & Mohammad Mahdi Rounaghi, 2024. "The nexus between the volatility of Bitcoin, gold, and American stock markets during the COVID-19 pandemic: evidence from VAR-DCC-EGARCH and ANN models," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-34, December.
    5. Ayoub Ammy-Driss & Matthieu Garcin, 2020. "Efficiency of the financial markets during the COVID-19 crisis: time-varying parameters of fractional stable dynamics," Papers 2007.10727, arXiv.org, revised Nov 2021.
    6. Fernandes, Leonardo H.S. & Bouri, Elie & Silva, José W.L. & Bejan, Lucian & de Araujo, Fernando H.A., 2022. "The resilience of cryptocurrency market efficiency to COVID-19 shock," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    7. Shanaev, Savva & Ghimire, Binam, 2022. "A generalised seasonality test and applications for cryptocurrency and stock market seasonality," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 172-185.
    8. Carmen López-Martín & Sonia Benito Muela & Raquel Arguedas, 2021. "Efficiency in cryptocurrency markets: new evidence," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(3), pages 403-431, September.
    9. Qadan, Mahmoud & Aharon, David Y. & Eichel, Ron, 2022. "Seasonal and Calendar Effects and the Price Efficiency of Cryptocurrencies," Finance Research Letters, Elsevier, vol. 46(PA).
    10. Assaf, Ata & Mokni, Khaled & Yousaf, Imran & Bhandari, Avishek, 2023. "Long memory in the high frequency cryptocurrency markets using fractal connectivity analysis: The impact of COVID-19," Research in International Business and Finance, Elsevier, vol. 64(C).
    11. Oktay Ozkan, 2020. "Time-varying return predictability and adaptive markets hypothesis: Evidence on MIST countries from a novel wild bootstrap likelihood ratio approach," Bogazici Journal, Review of Social, Economic and Administrative Studies, Bogazici University, Department of Economics, vol. 34(2), pages 101-113.
    12. Majid Mirzaee Ghazani & Mohammad Ali Jafari, 2021. "Cryptocurrencies, gold, and WTI crude oil market efficiency: a dynamic analysis based on the adaptive market hypothesis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-26, December.
    13. Shrestha, Keshab & Naysary, Babak & Philip, Sheena Sara Suresh, 2023. "Fintech market efficiency: A multifractal detrended fluctuation analysis," Finance Research Letters, Elsevier, vol. 54(C).
    14. Ammy-Driss, Ayoub & Garcin, Matthieu, 2023. "Efficiency of the financial markets during the COVID-19 crisis: Time-varying parameters of fractional stable dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    15. Manahov, Viktor & Urquhart, Andrew, 2021. "The efficiency of Bitcoin: A strongly typed genetic programming approach to smart electronic Bitcoin markets," International Review of Financial Analysis, Elsevier, vol. 73(C).
    16. Onur Özdemir, 2022. "Cue the volatility spillover in the cryptocurrency markets during the COVID-19 pandemic: evidence from DCC-GARCH and wavelet analysis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-38, December.
    17. Florentina c{S}oiman & Guillaume Dumas & Sonia Jimenez-Garces, 2022. "The return of (I)DeFiX," Papers 2204.00251, arXiv.org.

  2. 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.

    Cited by:

    1. Kenichi Hirayama & Akihiko Noda, 2020. "Evaluating the Financial Market Function in Prewar Japan using a Time-Varying Parameter Model," Papers 2008.00860, arXiv.org, revised Jun 2021.

  3. 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.

    Cited by:

    1. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2021. "Time-Varying Comovement of Foreign Exchange Markets: A GLS-Based Time-Varying Model Approach," Mathematics, MDPI, vol. 9(8), pages 1-13, April.
    2. Philippe Goulet Coulombe, 2020. "Time-Varying Parameters as Ridge Regressions," Papers 2009.00401, arXiv.org, revised Apr 2023.

  4. Mikio Ito & Kiyotaka Maeda & Akihiko Noda, 2016. "Market Integration in the Prewar Japanese Rice Markets," Papers 1604.00148, arXiv.org, revised Sep 2017.

    Cited by:

    1. Schneider, Eric B. & Ogasawara, Kota & Cole, Tim, 2021. "Health shocks, recovery and the first thousand days: the effect of the Second World War on height growth in Japanese children," LSE Research Online Documents on Economics 111948, London School of Economics and Political Science, LSE Library.

  5. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2016. "Time-Varying Comovement of Foreign Exchange Markets," Papers 1610.04334, arXiv.org.

    Cited by:

    1. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2022. "An Alternative Estimation Method for Time-Varying Parameter Models," Econometrics, MDPI, vol. 10(2), pages 1-27, April.

  6. 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. Kenichi Hirayama & Akihiko Noda, 2020. "Evaluating the Financial Market Function in Prewar Japan using a Time-Varying Parameter Model," Papers 2008.00860, arXiv.org, revised Jun 2021.
    2. 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.
    3. 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. 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. Oscar V. De la Torre-Torres & Evaristo Galeana-Figueroa & José Álvarez-García, 2021. "A Markov-Switching VSTOXX Trading Algorithm for Enhancing EUR Stock Portfolio Performance," Mathematics, MDPI, vol. 9(9), pages 1-28, May.
    2. 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.
    3. Akihiko Noda, 2022. "Estimating the Time-Varying Structures of the Fama-French Multi-Factor Models," Papers 2208.01270, arXiv.org.
    4. Yutaka Arimoto & Yoshihiro Sakane, 2021. "Agricultural development in industrialising Japan, 1880–1940," Australian Economic History Review, Economic History Society of Australia and New Zealand, vol. 61(3), pages 290-317, November.
    5. Mikio Ito & Kiyotaka Maeda & Akihiko Noda, 2016. "Market Integration in the Prewar Japanese Rice Markets," Papers 1604.00148, arXiv.org, revised Sep 2017.

  8. 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. Mariam Camarero & Juan Sapena & Cecilio Tamarit, 2020. "Modelling Time-Varying Parameters in Panel Data State-Space Frameworks: An Application to the Feldstein–Horioka Puzzle," Computational Economics, Springer;Society for Computational Economics, vol. 56(1), pages 87-114, June.
    2. 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.
    3. Shah, Anand & Bahri, Anu, 2022. "Metanomics: Adaptive market and volatility behaviour in Metaverse," MPRA Paper 114442, University Library of Munich, Germany.
    4. Ayoub Ammy-Driss & Matthieu Garcin, 2021. "Efficiency of the financial markets during the COVID-19 crisis: time-varying parameters of fractional stable dynamics," Working Papers hal-02903655, HAL.
    5. Okoroafor, Ugochi Chibuzor & Leirvik, Thomas, 2022. "Time varying market efficiency in the Brent and WTI crude market," Finance Research Letters, Elsevier, vol. 45(C).
    6. 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.
    7. 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.
    8. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2022. "An Alternative Estimation Method for Time-Varying Parameter Models," Econometrics, MDPI, vol. 10(2), pages 1-27, April.
    9. Ayoub Ammy-Driss & Matthieu Garcin, 2020. "Efficiency of the financial markets during the COVID-19 crisis: time-varying parameters of fractional stable dynamics," Papers 2007.10727, arXiv.org, revised Nov 2021.
    10. Akihiko Noda, 2019. "On the Evolution of Cryptocurrency Market Efficiency," Papers 1904.09403, arXiv.org, revised Jul 2020.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. Achal Awasthi & Oleg Malafeyev, 2015. "Is the Indian Stock Market efficient - A comprehensive study of Bombay Stock Exchange Indices," Papers 1510.03704, arXiv.org.
    18. Tran, Vu Le & Leirvik, Thomas, 2020. "Efficiency in the markets of crypto-currencies," Finance Research Letters, Elsevier, vol. 35(C).
    19. 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.
    20. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2021. "Time-Varying Comovement of Foreign Exchange Markets: A GLS-Based Time-Varying Model Approach," Mathematics, MDPI, vol. 9(8), pages 1-13, April.
    21. 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.
    22. Jiang, Jinjin & Li, Haiqi, 2020. "A new measure for market efficiency and its application," Finance Research Letters, Elsevier, vol. 34(C).
    23. Ammy-Driss, Ayoub & Garcin, Matthieu, 2023. "Efficiency of the financial markets during the COVID-19 crisis: Time-varying parameters of fractional stable dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    24. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2016. "Time-Varying Comovement of Foreign Exchange Markets," Papers 1610.04334, arXiv.org.
    25. Tran, Vu Le & Leirvik, Thomas, 2019. "A simple but powerful measure of market efficiency," Finance Research Letters, Elsevier, vol. 29(C), pages 141-151.
    26. Abakah, Emmanuel Joel Aikins & Gil-Alana, Luis Alberiko & Madigu, Godfrey & Romero-Rojo, Fatima, 2020. "Volatility persistence in cryptocurrency markets under structural breaks," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 680-691.
    27. Philippe Goulet Coulombe, 2020. "Time-Varying Parameters as Ridge Regressions," Papers 2009.00401, arXiv.org, revised Apr 2023.
    28. Onur Özdemir, 2022. "Cue the volatility spillover in the cryptocurrency markets during the COVID-19 pandemic: evidence from DCC-GARCH and wavelet analysis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-38, December.

  9. 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. Shah, Anand & Bahri, Anu, 2022. "Metanomics: Adaptive market and volatility behaviour in Metaverse," MPRA Paper 114442, University Library of Munich, Germany.
    2. 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.
    3. Taylor, Nick, 2014. "The rise and fall of technical trading rule success," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 286-302.
    4. 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.
    5. 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.
    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. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2022. "An Alternative Estimation Method for Time-Varying Parameter Models," Econometrics, MDPI, vol. 10(2), pages 1-27, April.
    8. 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.
    9. 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.
    10. Siddique, Maryam, 2023. "Does the Adaptive Market Hypothesis Exist in Equity Market? Evidence from Pakistan Stock Exchange," OSF Preprints 9b5dx, Center for Open Science.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. Vasile Brătian & Ana-Maria Acu & Camelia Oprean-Stan & Emil Dinga & Gabriela-Mariana Ionescu, 2021. "Efficient or Fractal Market Hypothesis? A Stock Indexes Modelling Using Geometric Brownian Motion and Geometric Fractional Brownian Motion," Mathematics, MDPI, vol. 9(22), pages 1-20, November.
    17. Al-Shboul, Mohammad & Alsharari, Nizar, 2019. "The dynamic behavior of evolving efficiency: Evidence from the UAE stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 73(C), pages 119-135.
    18. Oktay Ozkan, 2020. "Time-varying return predictability and adaptive markets hypothesis: Evidence on MIST countries from a novel wild bootstrap likelihood ratio approach," Bogazici Journal, Review of Social, Economic and Administrative Studies, Bogazici University, Department of Economics, vol. 34(2), pages 101-113.
    19. 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.
    20. Tran, Vu Le & Leirvik, Thomas, 2020. "Efficiency in the markets of crypto-currencies," Finance Research Letters, Elsevier, vol. 35(C).
    21. 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, vol. 11(5), pages 1-24, March.
    22. 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.
    23. Jiang, Jinjin & Li, Haiqi, 2020. "A new measure for market efficiency and its application," Finance Research Letters, Elsevier, vol. 34(C).
    24. Ali Fayyaz Munir & Mohd Edil Abd. Sukor & Shahrin Saaid Shaharuddin, 2022. "Adaptive Market Hypothesis and Time-varying Contrarian Effect: Evidence From Emerging Stock Markets of South Asia," SAGE Open, , vol. 12(1), pages 21582440211, January.
    25. Tran, Vu Le & Leirvik, Thomas, 2019. "A simple but powerful measure of market efficiency," Finance Research Letters, Elsevier, vol. 29(C), pages 141-151.
    26. 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.
    27. Koichiro Moriya & Akihiko Noda, 2023. "On the Time-Varying Structure of the Arbitrage Pricing Theory using the Japanese Sector Indices," Papers 2305.05998, arXiv.org, revised Mar 2024.
    28. Nevi Danila, 2022. "Random Walk of Socially Responsible Investment in Emerging Market," Sustainability, MDPI, vol. 14(19), pages 1-13, September.

  10. Akihiko Noda, 2012. "A Test of the Adaptive Market Hypothesis using a Time-Varying AR Model in Japan," Papers 1207.1842, arXiv.org, revised Jan 2016.

    Cited by:

    1. Paulo Vitor Souza de Souza & C sar Augusto Tib rcio Silva, 2020. "Effects of COVID-19 Pandemic on International Capital Markets," International Journal of Economics and Financial Issues, Econjournals, vol. 10(6), pages 163-171.
    2. 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.
    3. 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.
    4. Cristi Spulbar & Ramona Birau & Lucian Florin Spulbar, 2021. "A Critical Survey on Efficient Market Hypothesis (EMH), Adaptive Market Hypothesis (AMH) and Fractal Markets Hypothesis (FMH) Considering Their Implication on Stock Markets Behavior," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(2), pages 1161-1165, December.
    5. Okoroafor, Ugochi Chibuzor & Leirvik, Thomas, 2022. "Time varying market efficiency in the Brent and WTI crude market," Finance Research Letters, Elsevier, vol. 45(C).
    6. 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.
    7. 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.
    8. Akihiko Noda, 2019. "On the Evolution of Cryptocurrency Market Efficiency," Papers 1904.09403, arXiv.org, revised Jul 2020.
    9. Siddique, Maryam, 2023. "Does the Adaptive Market Hypothesis Exist in Equity Market? Evidence from Pakistan Stock Exchange," OSF Preprints 9b5dx, Center for Open Science.
    10. 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.
    11. 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.
    12. Akihiko Noda, 2022. "Estimating the Time-Varying Structures of the Fama-French Multi-Factor Models," Papers 2208.01270, arXiv.org.
    13. Carmen López-Martín & Sonia Benito Muela & Raquel Arguedas, 2021. "Efficiency in cryptocurrency markets: new evidence," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(3), pages 403-431, September.
    14. 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.
    15. Samuel Tabot Enow, 2021. "The Impact of Covid-19 on Market Efficiency: A Comparative Market Analysis," Eurasian Journal of Economics and Finance, Eurasian Publications, vol. 9(4), pages 235-244.
    16. Puertas, Antonio M. & Clara-Rahola, Joaquim & Sánchez-Granero, Miguel A. & de las Nieves, F. Javier & Trinidad-Segovia, Juan E., 2023. "A new look at financial markets efficiency from linear response theory," Finance Research Letters, Elsevier, vol. 51(C).
    17. 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).
    18. Sehrish Kayani & Usman Ayub & Imran Abbas Jadoon, 2019. "Adaptive Market Hypothesis and Artificial Neural Networks: Evidence from Pakistan," Global Regional Review, Humanity Only, vol. 4(2), pages 190-203, June.
    19. Okoroafor, Ugochi C. & Leirvik, Thomas, 2023. "Time-varying market efficiency of safe-haven assets," Finance Research Letters, Elsevier, vol. 56(C).
    20. Oktay Ozkan, 2020. "Time-varying return predictability and adaptive markets hypothesis: Evidence on MIST countries from a novel wild bootstrap likelihood ratio approach," Bogazici Journal, Review of Social, Economic and Administrative Studies, Bogazici University, Department of Economics, vol. 34(2), pages 101-113.
    21. Tran, Vu Le & Leirvik, Thomas, 2020. "Efficiency in the markets of crypto-currencies," Finance Research Letters, Elsevier, vol. 35(C).
    22. 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).
    23. 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.
    24. 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.
    25. Mushinada, Venkata Narasimha Chary, 2020. "Are individual investors irrational or adaptive to market dynamics?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 25(C).
    26. Majid Mirzaee Ghazani & Mohammad Ali Jafari, 2021. "Cryptocurrencies, gold, and WTI crude oil market efficiency: a dynamic analysis based on the adaptive market hypothesis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-26, December.
    27. Akihiko Noda, 2022. "Examining the Dynamic Asset Market Linkages under the COVID-19 Global Pandemic," Economics Bulletin, AccessEcon, vol. 42(2), pages 653-661.
    28. Mensi, Walid & Tiwari, Aviral Kumar & Yoon, Seong-Min, 2017. "Global financial crisis and weak-form efficiency of Islamic sectoral stock markets: An MF-DFA analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 135-146.
    29. Jiang, Jinjin & Li, Haiqi, 2020. "A new measure for market efficiency and its application," Finance Research Letters, Elsevier, vol. 34(C).
    30. Paulo Vitor Souza de SOUZA & César Augusto Tibúrcio SILVA, 2021. "Economic policy uncertainty and adaptability in international capital markets," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(1(626), S), pages 85-100, Spring.
    31. Tran, Vu Le & Leirvik, Thomas, 2019. "A simple but powerful measure of market efficiency," Finance Research Letters, Elsevier, vol. 29(C), pages 141-151.
    32. Akihiko Noda, 2021. "Examining the Dynamic Asset Market Linkages under the COVID-19 Global Pandemic," Papers 2109.02933, arXiv.org, revised Sep 2021.
    33. Abakah, Emmanuel Joel Aikins & Gil-Alana, Luis Alberiko & Madigu, Godfrey & Romero-Rojo, Fatima, 2020. "Volatility persistence in cryptocurrency markets under structural breaks," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 680-691.
    34. 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.
    35. Koichiro Moriya & Akihiko Noda, 2023. "On the Time-Varying Structure of the Arbitrage Pricing Theory using the Japanese Sector Indices," Papers 2305.05998, arXiv.org, revised Mar 2024.

Articles

  1. Akihiko Noda, 2021. "On the evolution of cryptocurrency market efficiency," Applied Economics Letters, Taylor & Francis Journals, vol. 28(6), pages 433-439, March.
    See citations under working paper version above.
  2. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2021. "Time-Varying Comovement of Foreign Exchange Markets: A GLS-Based Time-Varying Model Approach," Mathematics, MDPI, vol. 9(8), pages 1-13, April.

    Cited by:

    1. Mikio Ito, 2022. "Detecting Structural Breaks in Foreign Exchange Markets by using the group LASSO technique," Papers 2202.02988, arXiv.org.

  3. 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.
    See citations under working paper version above.
  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.
    See citations under working paper version above.
  5. Ito, Mikio & Maeda, Kiyotaka & Noda, Akihiko, 2016. "Market efficiency and government interventions in prewar Japanese rice futures markets," Financial History Review, Cambridge University Press, vol. 23(3), pages 325-346, December.
    See citations under working paper version above.
  6. 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.
  7. 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.
  8. Akihiko Noda & Shunsuke Sugiyama, 2010. "Measuring the Intertemporal Elasticity of Substitution for Consumption: Some Evidence from Japan," Economics Bulletin, AccessEcon, vol. 30(1), pages 524-533.

    Cited by:

    1. Steven Lugauer & Nelson Mark & Horag Choi, 2013. "The Size of the Precautionary Component of Household Saving: China and the U.S," 2013 Meeting Papers 1046, Society for Economic Dynamics.
    2. Horag Choi & Steven Lugauer & Nelson C. Mark, 2014. "Precautionary Saving of Chinese and U.S. Households," NBER Working Papers 20527, National Bureau of Economic Research, Inc.
    3. Jalali-Naini , Ahmad R. & Naderian , Mohammad A., 2012. "Central Bank Lending, Inflation and Output Dynamics in a Limited Participation Model," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 7(1), pages 41-66, October.
    4. Julian Thimme, 2017. "Intertemporal Substitution In Consumption: A Literature Review," Journal of Economic Surveys, Wiley Blackwell, vol. 31(1), pages 226-257, February.

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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 10 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 and Financial History (4) 2014-04-11 2014-05-09 2016-05-08 2017-04-09
  2. NEP-ETS: Econometric Time Series (3) 2012-02-15 2016-10-23 2017-07-30
  3. NEP-FMK: Financial Markets (3) 2019-04-29 2020-08-17 2021-09-20
  4. NEP-CWA: Central and Western Asia (1) 2012-02-15
  5. NEP-ECM: Econometrics (1) 2017-07-30
  6. NEP-GER: German Papers (1) 2014-04-11
  7. NEP-ISF: Islamic Finance (1) 2021-09-20
  8. NEP-MON: Monetary Economics (1) 2019-04-29
  9. NEP-PAY: Payment Systems and Financial Technology (1) 2019-04-29
  10. NEP-PKE: Post Keynesian Economics (1) 2016-05-08

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