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Ryuichi Yamamoto

Personal Details

First Name:Ryuichi
Middle Name:
Last Name:Yamamoto
Suffix:
RePEc Short-ID:pya313
http://www.f.waseda.jp/ryuichi/

Affiliation

(50%) School of Political Science and Economics
Faculty of Political Science and Economics
Waseda University

Tokyo, Japan
http://www.waseda.jp/fpse/pse/
RePEc:edi:spwasjp (more details at EDIRC)

(50%) Graduate School of Economics
Faculty of Political Science and Economics
Waseda University

Tokyo, Japan
http://www.waseda.jp/seikei/gse/
RePEc:edi:gewasjp (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Ryuichi Yamamoto, 2015. "Dynamic predictor selection and order splitting in a limit order market," Working Papers 1514, Waseda University, Faculty of Political Science and Economics.
  2. Ryuichi Yamamoto & Hideaki Hirata, "undated". "Belief Changes and Expectation Heterogeneity in Buy- and Sell-Side Professionals in the Japanese Stock Market," Working Paper 164461, Harvard University OpenScholar.
  3. Ryuichi Yamamoto & Hideaki Hirata, "undated". "Strategy Switching in the Japanese Stock Market," Working Paper 164466, Harvard University OpenScholar.

Articles

  1. 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.
  2. Yamamoto, Ryuichi, 2020. "Limit order submission risks, order choice, and tick size," Pacific-Basin Finance Journal, Elsevier, vol. 59(C).
  3. Xiao, Xijuan & Yamamoto, Ryuichi, 2020. "Price discovery, order submission, and tick size during preopen period," Pacific-Basin Finance Journal, Elsevier, vol. 63(C).
  4. Yamamoto, Ryuichi, 2019. "Dynamic Predictor Selection And Order Splitting In A Limit Order Market," Macroeconomic Dynamics, Cambridge University Press, vol. 23(5), pages 1757-1792, July.
  5. Ryuichi Yamamoto, 2016. "Trading profitability from learning and adaptation on the Tokyo Stock Exchange," Quantitative Finance, Taylor & Francis Journals, vol. 16(6), pages 969-996, June.
  6. Yamamoto, Ryuichi, 2014. "An empirical analysis of non-execution and picking-off risks on the Tokyo Stock Exchange," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 369-383.
  7. Yamamoto, Ryuichi & Hirata, Hideaki, 2013. "Strategy switching in the Japanese stock market," Journal of Economic Dynamics and Control, Elsevier, vol. 37(10), pages 2010-2022.
  8. Yamamoto, Ryuichi, 2012. "Intraday technical analysis of individual stocks on the Tokyo Stock Exchange," Journal of Banking & Finance, Elsevier, vol. 36(11), pages 3033-3047.
  9. Ryuichi Yamamoto, 2011. "Volatility clustering and herding agents: does it matter what they observe?," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 6(1), pages 41-59, May.
  10. Yamamoto, Ryuichi, 2011. "Order aggressiveness, pre-trade transparency, and long memory in an order-driven market," Journal of Economic Dynamics and Control, Elsevier, vol. 35(11), pages 1938-1963.
  11. R. Yamamoto & B. LeBaron, 2010. "Order-splitting and long-memory in an order-driven market," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 73(1), pages 51-57, January.
  12. Yamamoto, Ryuichi, 2010. "Asymmetric volatility, volatility clustering, and herding agents with a borrowing constraint," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(6), pages 1208-1214.
  13. Blake LeBaron & Ryuichi Yamamoto, 2008. "The Impact of Imitation on Long Memory in an Order-Driven Market," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 34(4), pages 504-517.
  14. LeBaron, Blake & Yamamoto, Ryuichi, 2007. "Long-memory in an order-driven market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 383(1), pages 85-89.
  15. Ryuichi Yamamoto, 2006. "What Causes Persistence Of Stock Return Volatility? One Possible Explanation With An Artificial Stock Market," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 2(03), pages 261-270.

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. Ryuichi Yamamoto & Hideaki Hirata, "undated". "Belief Changes and Expectation Heterogeneity in Buy- and Sell-Side Professionals in the Japanese Stock Market," Working Paper 164461, Harvard University OpenScholar.

    Cited by:

    1. Ryuichi Yamamoto & Hideaki Hirata, "undated". "Strategy Switching in the Japanese Stock Market," Working Paper 164466, Harvard University OpenScholar.

  2. Ryuichi Yamamoto & Hideaki Hirata, "undated". "Strategy Switching in the Japanese Stock Market," Working Paper 164466, Harvard University OpenScholar.

    Cited by:

    1. Songtao Wu & Jianmin He & Chao Wang, 2017. "Effects of Common Factors on Dynamics of Stocks Traded by Investors with Limited Information Capacity," Discrete Dynamics in Nature and Society, Hindawi, vol. 2017, pages 1-15, September.
    2. Takanobu Mizuta & Shintaro Kosugi & Takuya Kusumoto & Wataru Matsumoto & Kiyoshi Izumi & Isao Yagi & Shinobu Yoshimura, 2016. "Effects of Price Regulations and Dark Pools on Financial Market Stability: An Investigation by Multiagent Simulations," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 23(1-2), pages 97-120, January.
    3. Wai-Mun Chia & Mengling Li & Huanhuan Zheng, 2017. "Behavioral heterogeneity in the Australian housing market," Applied Economics, Taylor & Francis Journals, vol. 49(9), pages 872-885, February.
    4. 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.
    5. Yosra Mefteh Rekik & Younes Boujelbene, 2015. "Price Dynamics and Market Volatility: Behavioral Heterogeneity under Switching Trading Strategies on Artificial Financial Market," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 6(2), pages 33-43, April.

Articles

  1. 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.

    Cited by:

    1. Jujie Wang & Yinan Liao & Zhenzhen Zhuang & Dongming Gao, 2021. "An Optimal Weighted Combined Model Coupled with Feature Reconstruction and Deep Learning for Multivariate Stock Index Forecasting," Mathematics, MDPI, vol. 9(21), pages 1-20, October.

  2. Yamamoto, Ryuichi, 2020. "Limit order submission risks, order choice, and tick size," Pacific-Basin Finance Journal, Elsevier, vol. 59(C).

    Cited by:

    1. Maruyama, Hiroyuki & Tabata, Tomoaki, 2022. "Timing of tick size reduction: Threshold and smooth transition model analysis," Finance Research Letters, Elsevier, vol. 45(C).
    2. Zhu, Hongyu & Yamamoto, Ryuichi, 2022. "Order submission, information asymmetry, and tick size," Pacific-Basin Finance Journal, Elsevier, vol. 74(C).

  3. Xiao, Xijuan & Yamamoto, Ryuichi, 2020. "Price discovery, order submission, and tick size during preopen period," Pacific-Basin Finance Journal, Elsevier, vol. 63(C).

    Cited by:

    1. Maruyama, Hiroyuki & Tabata, Tomoaki, 2022. "Timing of tick size reduction: Threshold and smooth transition model analysis," Finance Research Letters, Elsevier, vol. 45(C).

  4. Ryuichi Yamamoto, 2016. "Trading profitability from learning and adaptation on the Tokyo Stock Exchange," Quantitative Finance, Taylor & Francis Journals, vol. 16(6), pages 969-996, June.

    Cited by:

    1. Bley, Jorg & Saad, Mohsen, 2020. "An analysis of technical trading rules: The case of MENA markets," Finance Research Letters, Elsevier, vol. 33(C).
    2. Day, Min-Yuh & Ni, Yensen, 2023. "Be greedy when others are fearful: Evidence from a two-decade assessment of the NDX 100 and S&P 500 indexes," International Review of Financial Analysis, Elsevier, vol. 90(C).

  5. Yamamoto, Ryuichi, 2014. "An empirical analysis of non-execution and picking-off risks on the Tokyo Stock Exchange," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 369-383.

    Cited by:

    1. Chiu, Junmao & Chen, Chin-Ho, 2023. "Limit order revisions across investor sophistication," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 74-90.
    2. Xiao, Xijuan & Yamamoto, Ryuichi, 2020. "Price discovery, order submission, and tick size during preopen period," Pacific-Basin Finance Journal, Elsevier, vol. 63(C).
    3. Federico Gonzalez & Mark Schervish, 2017. "Instantaneous order impact and high-frequency strategy optimization in limit order books," Papers 1707.01167, arXiv.org, revised Oct 2017.
    4. Yamamoto, Ryuichi, 2020. "Limit order submission risks, order choice, and tick size," Pacific-Basin Finance Journal, Elsevier, vol. 59(C).
    5. Wan, Xiaoyuan, 2020. "The impact of short-selling and margin-buying on liquidity: Evidence from the Chinese stock market," Journal of Empirical Finance, Elsevier, vol. 55(C), pages 104-118.

  6. Yamamoto, Ryuichi & Hirata, Hideaki, 2013. "Strategy switching in the Japanese stock market," Journal of Economic Dynamics and Control, Elsevier, vol. 37(10), pages 2010-2022.
    See citations under working paper version above.
  7. Yamamoto, Ryuichi, 2012. "Intraday technical analysis of individual stocks on the Tokyo Stock Exchange," Journal of Banking & Finance, Elsevier, vol. 36(11), pages 3033-3047.

    Cited by:

    1. Chang, C-L. & Ilomäki, J. & Laurila, H. & McAleer, M.J., 2018. "Long Run Returns Predictability and Volatility with Moving Averages," Econometric Institute Research Papers EI2018-39, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Gao, Ya & Han, Xing & Li, Youwei & Xiong, Xiong, 2019. "Overnight Momentum, Informational Shocks, and Late-Informed Trading in China," MPRA Paper 96784, University Library of Munich, Germany.
    3. Lundström, Christian, 2020. "On the Profitability of Momentum Strategies and Optimal Leverage Rules," Umeå Economic Studies 974, Umeå University, Department of Economics.
    4. Yang, Ann Shawing, 2016. "Calendar trading of Taiwan stock market: A study of holidays on trading detachment and interruptions," Emerging Markets Review, Elsevier, vol. 28(C), pages 140-154.
    5. Popov, Maxim & Madlener, Reinhard, 2014. "Backtesting and Evaluation of Different Trading Schemes for the Portfolio Management of Natural Gas," FCN Working Papers 5/2014, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    6. Chang, C-L. & Ilomäki, J. & Laurila, H. & McAleer, M.J., 2018. "Market Timing with Moving Averages for Fossil Fuel and Renewable Energy Stocks," Econometric Institute Research Papers EI2018-44, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    7. Xiaoye Jin, 2022. "Evaluating the predictive power of intraday technical trading in China's crude oil market," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1416-1432, November.
    8. Sensoy, Ahmet & Omole, John, 2022. "Information content of order imbalance in the index options market," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 418-432.
    9. Jin, Xiaoye, 2022. "Performance of intraday technical trading in China’s gold market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 76(C).
    10. Farias Nazário, Rodolfo Toríbio & e Silva, Jéssica Lima & Sobreiro, Vinicius Amorim & Kimura, Herbert, 2017. "A literature review of technical analysis on stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 66(C), pages 115-126.
    11. Hu, Chunhua & Feng, Huarong, 2024. "Kinetic model for asset allocation with strategy switching," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 636(C).
    12. Andrés Felipe Galeano Zurbaran, 2018. "Distribuciones no normales para la selección de activos en el mercado Colombiano," Documentos de Trabajo 17208, Quantil.
    13. Ting Zhang & George J. Jiang & Wei‐Xing Zhou, 2021. "Order imbalance and stock returns: New evidence from the Chinese stock market," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(2), pages 2809-2836, June.
    14. Akyildirim, Erdinc & Sensoy, Ahmet & Gulay, Guzhan & Corbet, Shaen & Salari, Hajar Novin, 2021. "Big data analytics, order imbalance and the predictability of stock returns," Journal of Multinational Financial Management, Elsevier, vol. 62(C).
    15. Robert Hudson & Andrew Urquhart, 2021. "Technical trading and cryptocurrencies," Annals of Operations Research, Springer, vol. 297(1), pages 191-220, February.
    16. Batten, Jonathan A. & Lucey, Brian M. & McGroarty, Frank & Peat, Maurice & Urquhart, Andrew, 2018. "Does intraday technical trading have predictive power in precious metal markets?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 52(C), pages 102-113.
    17. Mehmet Bayramoglu & Coskun Hamzacebi, 2016. "Stock Selection Based on Fundamental Analysis Approach by Grey Relational Analysis: A Case of Turkey," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 8(7), pages 178-178, July.

  8. Ryuichi Yamamoto, 2011. "Volatility clustering and herding agents: does it matter what they observe?," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 6(1), pages 41-59, May.

    Cited by:

    1. Sunyoung Lee & Keun Lee, 2021. "3% rules the market: herding behavior of a group of investors, asset market volatility, and return to the group in an agent-based model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(2), pages 359-380, April.
    2. Lu, Jingen & Chen, Xiaohong & Liu, Xiaoxing, 2018. "Stock market information flow: Explanations from market status and information-related behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 837-848.
    3. Pengfei Wang & Wei Zhang & Xiao Li & Dehua Shen, 2019. "Trading volume and return volatility of Bitcoin market: evidence for the sequential information arrival hypothesis," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(2), pages 377-418, June.

  9. Yamamoto, Ryuichi, 2011. "Order aggressiveness, pre-trade transparency, and long memory in an order-driven market," Journal of Economic Dynamics and Control, Elsevier, vol. 35(11), pages 1938-1963.

    Cited by:

    1. Hautsch, Nikolaus & Huang, Ruihong, 2009. "The market impact of a limit order," CFS Working Paper Series 2009/23, Center for Financial Studies (CFS).
    2. Vivien Lespagnol & Juliette Rouchier, 2014. "Trading Volume and Market Efficiency: An Agent Based Model with Heterogenous Knowledge about Fundamentals," Working Papers halshs-00997573, HAL.
    3. Vivien Lespagnol & Juliette Rouchier, 2015. "What Is the Impact of Heterogeneous Knowledge About Fundamentals on Market Liquidity and Efficiency: An ABM Approach," Lecture Notes in Economics and Mathematical Systems, in: Frédéric Amblard & Francisco J. Miguel & Adrien Blanchet & Benoit Gaudou (ed.), Advances in Artificial Economics, edition 127, pages 105-117, Springer.
    4. Kovaleva, Polina & Iori, Giulia, 2015. "The impact of reduced pre-trade transparency regimes on market quality," Journal of Economic Dynamics and Control, Elsevier, vol. 57(C), pages 145-162.
    5. Ryuichi Yamamoto, 2015. "Dynamic predictor selection and order splitting in a limit order market," Working Papers 1514, Waseda University, Faculty of Political Science and Economics.
    6. Yuki Sato & Kiyoshi Kanazawa, 2023. "Exact solution to a generalised Lillo-Mike-Farmer model with heterogeneous order-splitting strategies," Papers 2306.13378, arXiv.org, revised Nov 2023.
    7. Paulo M.M. Rodrigues & Marina Balboa, 2021. "Multivariate Fractional Integration Tests allowing for Conditional Heteroskedasticity with an Application to Return Volatility and Trading Volume," Working Papers w202102, Banco de Portugal, Economics and Research Department.
    8. Erdinc Akyildirim & Shaen Corbet & Guzhan Gulay & Duc Khuong Nguyen & Ahmet Sensoy, 2019. "Order Flow Persistence in Equity Spot and Futures Markets: Evidence from a Dynamic Emerging Market," Working Papers 2019-011, Department of Research, Ipag Business School.
    9. Vivien Lespagnol & Juliette Rouchier, 2018. "Trading Volume and Price Distortion: An Agent-Based Model with Heterogenous Knowledge of Fundamentals," Computational Economics, Springer;Society for Computational Economics, vol. 51(4), pages 991-1020, April.
    10. Bellia, Mario & Pelizzon, Loriana & Subrahmanyam, Marti G. & Uno, Jun & Yuferova, Darya, 2017. "Low-latency trading and price discovery: Evidence from the Tokyo Stock Exchange in the pre-opening and opening periods," SAFE Working Paper Series 144, Leibniz Institute for Financial Research SAFE, revised 2017.
    11. Iris Lucas & Michel Cotsaftis & Cyrille Bertelle, 2018. "Self-Organization, Resilience and Robustness of Complex Systems Through an Application to Financial Market from an Agent-Based Approach," Post-Print hal-02114928, HAL.
    12. Roberto Mota Navarro & Hernán Larralde, 2017. "A detailed heterogeneous agent model for a single asset financial market with trading via an order book," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-27, February.
    13. Vivien Lespagnol & Juliette Rouchier, 2015. "Fair Price And Trading Price: An Abm Approach With Order-Placement Strategy And Misunderstanding Of Fundamental Value," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 18(05n06), pages 1-14, August.
    14. Kyubin Yim & Gabjin Oh & Seunghwan Kim, 2016. "Understanding Financial Market States Using an Artificial Double Auction Market," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-15, March.
    15. Yamamoto, Ryuichi, 2012. "Intraday technical analysis of individual stocks on the Tokyo Stock Exchange," Journal of Banking & Finance, Elsevier, vol. 36(11), pages 3033-3047.
    16. 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.
    17. Xiao, Xijuan & Yamamoto, Ryuichi, 2020. "Price discovery, order submission, and tick size during preopen period," Pacific-Basin Finance Journal, Elsevier, vol. 63(C).
    18. Pham, Thu Phuong & Westerholm, P. Joakim, 2013. "A survey of research into broker identity and limit order book," Working Papers 17212, University of Tasmania, Tasmanian School of Business and Economics, revised 16 Oct 2013.
    19. Iris Lucas & Michel Cotsaftis & Cyrille Bertelle, 2017. "Heterogeneity and Self-Organization of Complex Systems Through an Application to Financial Market with Multiagent Systems," Post-Print hal-02114933, HAL.
    20. Mathieu, Philippe & Morvan, Rémi, 2019. "A deterministic behaviour for realistic price dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 33-49.
    21. Lien, Donald & Hung, Pi-Hsia & Chen, Hung-Ju, 2021. "Who knows more and makes more? A perspective of order submission decisions across investor types," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 381-398.
    22. Ming-Chang Wang & Yu-Jia Ding & Pei-Han Hsin, 2018. "Order Aggressiveness and the Heating and Cooling-off Effects of Price Limits: Evidence from Taiwan Stock Exchange," Journal of Economics and Management, College of Business, Feng Chia University, Taiwan, vol. 14(2), pages 191-216, August.
    23. Tóth, Bence & Palit, Imon & Lillo, Fabrizio & Farmer, J. Doyne, 2015. "Why is equity order flow so persistent?," Journal of Economic Dynamics and Control, Elsevier, vol. 51(C), pages 218-239.
    24. Vivien Lespagnol & Juliette Rouchier, 2018. "Trading Volume and Price Distortion: An Agent-Based Model with Heterogenous Knowledge of Fundamentals," Post-Print hal-02084910, HAL.
    25. Tseng, Yi-Heng & Chen, Shu-Heng, 2015. "Limit order book transparency and order aggressiveness at the closing call: Lessons from the TWSE 2012 new information disclosure mechanism," Pacific-Basin Finance Journal, Elsevier, vol. 35(PA), pages 241-272.

  10. R. Yamamoto & B. LeBaron, 2010. "Order-splitting and long-memory in an order-driven market," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 73(1), pages 51-57, January.

    Cited by:

    1. Alessio Emanuele Biondo, 2020. "Information versus imitation in a real-time agent-based model of financial markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(3), pages 613-631, July.
    2. Michiel Leur & Mikhail Anufriev, 2018. "Timing under individual evolutionary learning in a continuous double auction," Journal of Evolutionary Economics, Springer, vol. 28(3), pages 609-631, August.
    3. Rocco Caferra & Gabriele Tedeschi & Andrea Morone, 2023. "Agents interaction and price dynamics: evidence from the laboratory," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 18(2), pages 251-274, April.
    4. Ryuichi Yamamoto, 2015. "Dynamic predictor selection and order splitting in a limit order market," Working Papers 1514, Waseda University, Faculty of Political Science and Economics.
    5. Erdinc Akyildirim & Shaen Corbet & Guzhan Gulay & Duc Khuong Nguyen & Ahmet Sensoy, 2019. "Order Flow Persistence in Equity Spot and Futures Markets: Evidence from a Dynamic Emerging Market," Working Papers 2019-011, Department of Research, Ipag Business School.
    6. Jiahua Wang & Hongliang Zhu & Dongxin Li, 2018. "Price Dynamics in an Order-Driven Market with Bayesian Learning," Complexity, Hindawi, vol. 2018, pages 1-15, November.
    7. Vivien Lespagnol & Juliette Rouchier, 2018. "Trading Volume and Price Distortion: An Agent-Based Model with Heterogenous Knowledge of Fundamentals," Computational Economics, Springer;Society for Computational Economics, vol. 51(4), pages 991-1020, April.
    8. Bence Toth & Imon Palit & Fabrizio Lillo & J. Doyne Farmer, 2011. "Why is order flow so persistent?," Papers 1108.1632, arXiv.org, revised Nov 2014.
    9. Kyubin Yim & Gabjin Oh & Seunghwan Kim, 2016. "Understanding Financial Market States Using an Artificial Double Auction Market," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-15, March.
    10. Yamamoto, Ryuichi, 2011. "Order aggressiveness, pre-trade transparency, and long memory in an order-driven market," Journal of Economic Dynamics and Control, Elsevier, vol. 35(11), pages 1938-1963.
    11. Ryuichi Yamamoto, 2011. "Volatility clustering and herding agents: does it matter what they observe?," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 6(1), pages 41-59, May.
    12. Vivien Lespagnol & Juliette Rouchier, 2018. "Trading Volume and Price Distortion: An Agent-Based Model with Heterogenous Knowledge of Fundamentals," Post-Print hal-02084910, HAL.

  11. Yamamoto, Ryuichi, 2010. "Asymmetric volatility, volatility clustering, and herding agents with a borrowing constraint," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(6), pages 1208-1214.

    Cited by:

    1. Yue Chen & Juan Lin & Ximing Wu, 2022. "Revisiting the return‐volatility relationship of exchange rates: New evidence from offshore RMB," Pacific Economic Review, Wiley Blackwell, vol. 27(3), pages 277-294, August.
    2. Krause, Sebastian M. & Bornholdt, Stefan, 2013. "Spin models as microfoundation of macroscopic market models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(18), pages 4048-4054.
    3. Miikka Kaurijoki & Jussi Nikkinen & Janne Äijö, 2015. "Return‐Implied Volatility Dynamics of High and Low Yielding Currencies," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 35(11), pages 1026-1041, November.

  12. Blake LeBaron & Ryuichi Yamamoto, 2008. "The Impact of Imitation on Long Memory in an Order-Driven Market," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 34(4), pages 504-517.

    Cited by:

    1. Danilo Liuzzi & Paolo Pellizzari & Marco Tolotti, 2019. "Fast traders and slow price adjustments: an artificial market with strategic interaction and transaction costs," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(3), pages 643-662, September.
    2. Kunal Saha & Vinodh Madhavan & Chandrashekhar G. R. & David McMillan, 2020. "Pitfalls in long memory research," Cogent Economics & Finance, Taylor & Francis Journals, vol. 8(1), pages 1733280-173, January.
    3. Recchioni, Maria Cristina & Tedeschi, Gabriele & Gallegati, Mauro, 2014. "A calibration procedure for analyzing stock price dynamics in an agent-based framework," FinMaP-Working Papers 26, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    4. Stefan, F.M. & Atman, A.P.F., 2015. "Is there any connection between the network morphology and the fluctuations of the stock market index?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 630-641.
    5. Gabriele Tedeschi & Stefania Vitali & Mauro Gallegati, 2014. "The dynamic of innovation networks: a switching model on technological change," Journal of Evolutionary Economics, Springer, vol. 24(4), pages 817-834, September.
    6. Yuki Sato & Kiyoshi Kanazawa, 2023. "Exact solution to a generalised Lillo-Mike-Farmer model with heterogeneous order-splitting strategies," Papers 2306.13378, arXiv.org, revised Nov 2023.
    7. Paulo M.M. Rodrigues & Marina Balboa, 2021. "Multivariate Fractional Integration Tests allowing for Conditional Heteroskedasticity with an Application to Return Volatility and Trading Volume," Working Papers w202102, Banco de Portugal, Economics and Research Department.
    8. Erdinc Akyildirim & Shaen Corbet & Guzhan Gulay & Duc Khuong Nguyen & Ahmet Sensoy, 2019. "Order Flow Persistence in Equity Spot and Futures Markets: Evidence from a Dynamic Emerging Market," Working Papers 2019-011, Department of Research, Ipag Business School.
    9. Tedeschi, Gabriele & Iori, Giulia & Gallegati, Mauro, 2012. "Herding effects in order driven markets: The rise and fall of gurus," Journal of Economic Behavior & Organization, Elsevier, vol. 81(1), pages 82-96.
    10. Tedeschi, Gabriele & Recchioni, Maria Cristina & Berardi, Simone, 2019. "An approach to identifying micro behavior: How banks’ strategies influence financial cycles," Journal of Economic Behavior & Organization, Elsevier, vol. 162(C), pages 329-346.
    11. Bence Toth & Imon Palit & Fabrizio Lillo & J. Doyne Farmer, 2011. "Why is order flow so persistent?," Papers 1108.1632, arXiv.org, revised Nov 2014.
    12. Luis Goncalves de Faria, 2022. "An Agent-Based Model With Realistic Financial Time Series: A Method for Agent-Based Models Validation," Papers 2206.09772, arXiv.org.
    13. Marko Petrovic & Bulent Ozel & Andrea Teglio & Marco Raberto & Silvano Cincotti, 2017. "Eurace Open: An agent-based multi-country model," Working Papers 2017/09, Economics Department, Universitat Jaume I, Castellón (Spain).
    14. Yamamoto, Ryuichi, 2011. "Order aggressiveness, pre-trade transparency, and long memory in an order-driven market," Journal of Economic Dynamics and Control, Elsevier, vol. 35(11), pages 1938-1963.
    15. Chiarella, Carl & He, Xue-Zhong & Wei, Lijian, 2015. "Learning, information processing and order submission in limit order markets," Journal of Economic Dynamics and Control, Elsevier, vol. 61(C), pages 245-268.
    16. Gabriel Bobeica & Elena Bojesteanu, 2008. "Long Memory in Volatility. An Investigation on the Central and Eastern European Exchange Rates," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 7-18.
    17. Roberto Dieci & Xue-Zhong He, 2018. "Heterogeneous Agent Models in Finance," Research Paper Series 389, Quantitative Finance Research Centre, University of Technology, Sydney.
    18. Simone Berardi & Gabriele Tedeschi, 2016. "How banks’ strategies influence financial cycles: An approach to identifying micro behavior," Working Papers 2016/24, Economics Department, Universitat Jaume I, Castellón (Spain).
    19. Ryuichi Yamamoto, 2011. "Volatility clustering and herding agents: does it matter what they observe?," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 6(1), pages 41-59, May.
    20. Ke Xu & Yu‐Lun Chen & Bo Liu & Jian Chen, 2024. "Price discovery and long‐memory property: Simulation and empirical evidence from the bitcoin market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(4), pages 605-618, April.
    21. Stefan, F.M. & Atman, A.P.F., 2023. "Asymmetric rate of returns and wealth distribution influenced by the introduction of technical analysis into a behavioral agent-based model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    22. Recchioni, Maria Cristina & Tedeschi, Gabriele & Berardi, Simone, 2014. "Bank's strategies during the financial crisis," FinMaP-Working Papers 25, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    23. Berardi, Simone & Tedeschi, Gabriele, 2017. "From banks' strategies to financial (in)stability," International Review of Economics & Finance, Elsevier, vol. 47(C), pages 255-272.
    24. Blaurock, Ivonne & Schmitt, Noemi & Westerhoff, Frank, 2018. "Market entry waves and volatility outbursts in stock markets," Journal of Economic Behavior & Organization, Elsevier, vol. 153(C), pages 19-37.
    25. Tóth, Bence & Palit, Imon & Lillo, Fabrizio & Farmer, J. Doyne, 2015. "Why is equity order flow so persistent?," Journal of Economic Dynamics and Control, Elsevier, vol. 51(C), pages 218-239.
    26. Hazem Krichene & Mhamed-Ali El-Aroui, 2018. "Artificial stock markets with different maturity levels: simulation of information asymmetry and herd behavior using agent-based and network models," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(3), pages 511-535, October.

  13. LeBaron, Blake & Yamamoto, Ryuichi, 2007. "Long-memory in an order-driven market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 383(1), pages 85-89.

    Cited by:

    1. Andrea Coletta & Aymeric Moulin & Svitlana Vyetrenko & Tucker Balch, 2022. "Learning to simulate realistic limit order book markets from data as a World Agent," Papers 2210.09897, arXiv.org.
    2. Fabrizio Pomponio & Frédéric Abergel, 2013. "Multiple-limit trades : empirical facts and application to lead-lag measures," Post-Print hal-00745317, HAL.
    3. Luis Miguel Doncel & Pilar Grau-Carles & Jorge Sainz, 2009. "On the long-term behavior of mutual fund returns," Quantitative Finance, Taylor & Francis Journals, vol. 9(6), pages 653-660.
    4. Kunal Saha & Vinodh Madhavan & Chandrashekhar G. R. & David McMillan, 2020. "Pitfalls in long memory research," Cogent Economics & Finance, Taylor & Francis Journals, vol. 8(1), pages 1733280-173, January.
    5. Ross M. Miller, 2003. "Don't Let Your Robots Grow Up To Be Traders: Artificial Intelligence, Human Intelligence, and Asset-Market Bubbles," Experimental 0306001, University Library of Munich, Germany.
    6. Recchioni, Maria Cristina & Tedeschi, Gabriele & Gallegati, Mauro, 2014. "A calibration procedure for analyzing stock price dynamics in an agent-based framework," FinMaP-Working Papers 26, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    7. Yuki Sato & Kiyoshi Kanazawa, 2023. "Exact solution to a generalised Lillo-Mike-Farmer model with heterogeneous order-splitting strategies," Papers 2306.13378, arXiv.org, revised Nov 2023.
    8. Erdinc Akyildirim & Shaen Corbet & Guzhan Gulay & Duc Khuong Nguyen & Ahmet Sensoy, 2019. "Order Flow Persistence in Equity Spot and Futures Markets: Evidence from a Dynamic Emerging Market," Working Papers 2019-011, Department of Research, Ipag Business School.
    9. Angelo Carollo & Gabriella Vaglica & Fabrizio Lillo & Rosario N. Mantegna, 2012. "Trading activity and price impact in parallel markets: SETS vs. off-book market at the London Stock Exchange," Quantitative Finance, Taylor & Francis Journals, vol. 12(4), pages 517-530, November.
    10. Tedeschi, Gabriele & Iori, Giulia & Gallegati, Mauro, 2012. "Herding effects in order driven markets: The rise and fall of gurus," Journal of Economic Behavior & Organization, Elsevier, vol. 81(1), pages 82-96.
    11. Jiahua Wang & Hongliang Zhu & Dongxin Li, 2018. "Price Dynamics in an Order-Driven Market with Bayesian Learning," Complexity, Hindawi, vol. 2018, pages 1-15, November.
    12. Bàrbara Llacay & Gilbert Peffer, 2018. "Using realistic trading strategies in an agent-based stock market model," Computational and Mathematical Organization Theory, Springer, vol. 24(3), pages 308-350, September.
    13. Svitlana Vyetrenko & David Byrd & Nick Petosa & Mahmoud Mahfouz & Danial Dervovic & Manuela Veloso & Tucker Hybinette Balch, 2019. "Get Real: Realism Metrics for Robust Limit Order Book Market Simulations," Papers 1912.04941, arXiv.org.
    14. Bence Toth & Imon Palit & Fabrizio Lillo & J. Doyne Farmer, 2011. "Why is order flow so persistent?," Papers 1108.1632, arXiv.org, revised Nov 2014.
    15. Luis Goncalves de Faria, 2022. "An Agent-Based Model With Realistic Financial Time Series: A Method for Agent-Based Models Validation," Papers 2206.09772, arXiv.org.
    16. Bai, Ye & Chow, Darien Yan Pang, 2017. "Shanghai-Hong Kong Stock Connect: An analysis of Chinese partial stock market liberalization impact on the local and foreign markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 50(C), pages 182-203.
    17. Onsurang Norrbin & Aaron D. Smallwood, 2011. "Mean Reversion in the Real Interest Rate and the Effects of Calculating Expected Inflation," Southern Economic Journal, John Wiley & Sons, vol. 78(1), pages 107-130, July.
    18. Joshin Murai, 2016. "A model of transaction signs with order splitting and public information," Evolutionary and Institutional Economics Review, Springer, vol. 13(2), pages 469-480, December.
    19. Georges, Christophre & Wallace, John C., 2009. "Learning Dynamics And Nonlinear Misspecification In An Artificial Financial Market," Macroeconomic Dynamics, Cambridge University Press, vol. 13(5), pages 625-655, November.
    20. Steve Phelps & Wing Lon Ng, 2014. "A Simulation Analysis Of Herding And Unifractal Scaling Behaviour," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 21(1), pages 39-58, January.
    21. Anufriev, M. & Panchenko, V., 2007. "Asset Prices, Traders' Behavior, and Market Design," CeNDEF Working Papers 07-14, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    22. Yamamoto, Ryuichi, 2011. "Order aggressiveness, pre-trade transparency, and long memory in an order-driven market," Journal of Economic Dynamics and Control, Elsevier, vol. 35(11), pages 1938-1963.
    23. Zaitsev, Sergey & Zaitsev, Alexander & Leonidov, Andrei & Trainin, Vladimir, 2009. "Market mill dependence pattern in the stock market: Multiscale conditional dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(21), pages 4624-4634.
    24. Ryuichi Yamamoto, 2011. "Volatility clustering and herding agents: does it matter what they observe?," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 6(1), pages 41-59, May.
    25. Paolo Barucca & Fabrizio Lillo, 2017. "Behind the price: on the role of agent's reflexivity in financial market microstructure," Papers 1708.07047, arXiv.org.
    26. Jean-Philippe Bouchaud & J. Doyne Farmer & Fabrizio Lillo, 2008. "How markets slowly digest changes in supply and demand," Papers 0809.0822, arXiv.org.
    27. Recchioni, Maria Cristina & Tedeschi, Gabriele & Berardi, Simone, 2014. "Bank's strategies during the financial crisis," FinMaP-Working Papers 25, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    28. Pirino, Davide, 2009. "Jump detection and long range dependence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(7), pages 1150-1156.
    29. Tóth, Bence & Palit, Imon & Lillo, Fabrizio & Farmer, J. Doyne, 2015. "Why is equity order flow so persistent?," Journal of Economic Dynamics and Control, Elsevier, vol. 51(C), pages 218-239.
    30. Blake LeBaron & Ryuichi Yamamoto, 2008. "The Impact of Imitation on Long Memory in an Order-Driven Market," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 34(4), pages 504-517.
    31. Martin D. Gould & Mason A. Porter & Sam D. Howison, 2015. "The Long Memory of Order Flow in the Foreign Exchange Spot Market," Papers 1504.04354, arXiv.org, revised Oct 2015.

  14. Ryuichi Yamamoto, 2006. "What Causes Persistence Of Stock Return Volatility? One Possible Explanation With An Artificial Stock Market," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 2(03), pages 261-270.

    Cited by:

    1. Ho, Kin-Yip & Zheng, Lin & Zhang, Zhaoyong, 2012. "Volume, volatility and information linkages in the stock and option markets," Review of Financial Economics, Elsevier, vol. 21(4), pages 168-174.
    2. Kin‐Yip Ho & Zhaoyong Zhang, 2012. "Dynamic Linkages among Financial Markets in the Greater China Region: A Multivariate Asymmetric Approach," The World Economy, Wiley Blackwell, vol. 35(4), pages 500-523, April.

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