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Taisei Kaizoji

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. Cheoljun Eom & Taisei Kaizoji & Enrico Scalas, 2019. "Fat Tails in Financial Return Distributions Revisited: Evidence from the Korean Stock Market," Papers 1904.02567, arXiv.org.

    Cited by:

    1. Eom, Cheoljun & Park, Jong Won, 2023. "Price behavior of small-cap stocks and momentum: A study using principal component momentum," Research in International Business and Finance, Elsevier, vol. 65(C).
    2. Giulia Di Nunno & Kęstutis Kubilius & Yuliya Mishura & Anton Yurchenko-Tytarenko, 2023. "From Constant to Rough: A Survey of Continuous Volatility Modeling," Mathematics, MDPI, vol. 11(19), pages 1-35, October.
    3. EOM, Cheoljun & EOM, Yunsung & PARK, Jong Won, 2024. "Intermediate cross-sectional prospect theory value in stock markets: A novel method," International Review of Financial Analysis, Elsevier, vol. 93(C).
    4. Changtai Li & Weihong Huang & Wei-Siang Wang & Wai-Mun Chia, 2023. "Price Change and Trading Volume: Behavioral Heterogeneity in Stock Market," Computational Economics, Springer;Society for Computational Economics, vol. 61(2), pages 677-713, February.
    5. Till Massing & Arturo Ramos, 2023. "Student't mixture models for stock indices. A comparative study," Papers 2308.10023, arXiv.org.
    6. Eom, Cheoljun & Kaizoji, Taisei & Livan, Giacomo & Scalas, Enrico, 2021. "Limitations of portfolio diversification through fat tails of the return Distributions: Some empirical evidence," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    7. Echaust, Krzysztof & Just, Małgorzata, 2022. "Is gold still a safe haven for stock markets? New insights through the tail thickness of portfolio return distributions," Research in International Business and Finance, Elsevier, vol. 63(C).
    8. Leovardo Mata Mata & José Antonio Núñez Mora & Ramona Serrano Bautista, 2021. "Multivariate Distribution in the Stock Markets of Brazil, Russia, India, and China," SAGE Open, , vol. 11(2), pages 21582440211, April.
    9. Giulia Di Nunno & Kk{e}stutis Kubilius & Yuliya Mishura & Anton Yurchenko-Tytarenko, 2023. "From constant to rough: A survey of continuous volatility modeling," Papers 2309.01033, arXiv.org, revised Sep 2023.
    10. Marcin Wk{a}torek & Jaros{l}aw Kwapie'n & Stanis{l}aw Dro.zd.z, 2021. "Financial Return Distributions: Past, Present, and COVID-19," Papers 2107.06659, arXiv.org.
    11. Eom, Cheoljun & Park, Jong Won, 2020. "Effects of the fat-tail distribution on the relationship between prospect theory value and expected return," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    12. Eom, Cheoljun & Eom, Yunsung & Park, Jong Won, 2023. "Left-tail momentum and tail properties of return distributions: A case of Korea," International Review of Financial Analysis, Elsevier, vol. 87(C).
    13. Burns, Christopher B. & Kane, Stephen, 2022. "Arbitrage breakdown in WTI crude oil futures: An analysis of the events on April 20, 2020," Resources Policy, Elsevier, vol. 76(C).

  2. Taisei Kaizoji & Michiko Miyano, 2017. "Zipf's law for share price and company fundamentals," Papers 1702.00144, arXiv.org.

    Cited by:

    1. Da Silva, Sergio & Matsushita, Raul & Giglio, Ricardo & Massena, Gunther, 2018. "Granularity of the top 1,000 Brazilian companies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 68-73.

  3. Taisei Kaizoji & Michiko Miyano, 2016. "Stock Market Market Crash of 2008: an empirical study of the deviation of share prices from company fundamentals," Papers 1607.03205, arXiv.org.

    Cited by:

    1. Taisei Kaizoji & Michiko Miyano, 2017. "Zipf's law for share price and company fundamentals," Papers 1702.00144, arXiv.org.

  4. Taisei KAIZOJI & Matthias LEISS & Alexander I. SAICHEV & Didier SORNETTE, 2015. "Super-Exponential Endogenous Bubbles in an Equilibrium Model of Fundamentalist and Chartist Traders," Swiss Finance Institute Research Paper Series 15-07, Swiss Finance Institute.

    Cited by:

    1. Li Lin & Didier Sornette, 2023. "The inverse Cox-Ingersoll-Ross process for parsimonious financial price modeling," Papers 2302.11423, arXiv.org, revised Jun 2023.
    2. Antoine Kopp & Rebecca Westphal & Didier Sornette, 2022. "Agent-based model generating stylized facts of fixed income markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 17(4), pages 947-992, October.
    3. Rebecca Westphal & Didier Sornette, 2019. "Market Impact and Performance of Arbitrageurs of Financial Bubbles in An Agent-Based Model," Swiss Finance Institute Research Paper Series 19-29, Swiss Finance Institute.
    4. Rebecca Westphal & Didier Sornette, 2020. "How market intervention can prevent bubbles and crashes," Swiss Finance Institute Research Paper Series 20-74, Swiss Finance Institute.
    5. Li, Zhuolei & Diao, Xundi & Wu, Chongfeng, 2022. "The influence of mobile trading on return dispersion and herding behavior," Pacific-Basin Finance Journal, Elsevier, vol. 73(C).
    6. Li Lin & Didier Sornette, 2015. ""Speculative Influence Network" during financial bubbles: application to Chinese Stock Markets," Papers 1510.08162, arXiv.org.
    7. T. T. Chen & B. Zheng & Y. Li & X. F. Jiang, 2017. "New approaches in agent-based modeling of complex financial systems," Papers 1703.06840, arXiv.org.
    8. Ardila-Alvarez, Diego & Forro, Zalan & Sornette, Didier, 2021. "The acceleration effect and Gamma factor in asset pricing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 569(C).
    9. Aleksejus Kononovicius & Vygintas Gontis, 2019. "Approximation of the first passage time distribution for the birth-death processes," Papers 1902.00924, arXiv.org.
    10. Rebecca Westphal & Didier Sornette, 2024. "How Market Intervention can Prevent Bubbles and Crashes: An Agent Based Modelling Approach," Computational Economics, Springer;Society for Computational Economics, vol. 64(3), pages 1315-1356, September.
    11. Cafferata, Alessia & Tramontana, Fabio, 2022. "Disposition Effect and its outcome on endogenous price fluctuations," MPRA Paper 113904, University Library of Munich, Germany.
    12. Andreas Hefti & Steve Heinke & Frédéric Schneider, 2016. "Mental capabilities, trading styles, and asset market bubbles: theory and experiment," ECON - Working Papers 234, Department of Economics - University of Zurich.
    13. Kononovicius, Aleksejus & Ruseckas, Julius, 2019. "Order book model with herd behavior exhibiting long-range memory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 171-191.
    14. Rytis Kazakeviv{c}ius & Aleksejus Kononovicius, 2023. "Anomalous diffusion and long-range memory in the scaled voter model," Papers 2301.08088, arXiv.org, revised Feb 2023.
    15. Westphal, Rebecca & Sornette, Didier, 2020. "Market impact and performance of arbitrageurs of financial bubbles in an agent-based model," Journal of Economic Behavior & Organization, Elsevier, vol. 171(C), pages 1-23.
    16. Chen, Ting-Ting & Zheng, Bo & Li, Yan & Jiang, Xiong-Fei, 2018. "Information driving force and its application in agent-based modeling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 593-601.

  5. T. Kaizoji & M. Leiss & A. Saichev & D. Sornette, 2011. "Super-exponential endogenous bubbles in an equilibrium model of rational and noise traders," Papers 1109.4726, arXiv.org, revised Mar 2014.

    Cited by:

    1. Li Lin & Didier Sornette, 2018. "“Speculative Influence Network” during financial bubbles: application to Chinese stock markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(2), pages 385-431, July.

  6. Mauro Politi & Taisei Kaizoji & Enrico Scalas, 2011. "Full characterization of the fractional Poisson process," Papers 1104.4234, arXiv.org.

    Cited by:

    1. De Martino, Giuseppe & Spina, Serena, 2015. "Exploiting the time-dynamics of news diffusion on the Internet through a generalized Susceptible–Infected model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 634-644.
    2. Chicheportiche, Rémy & Chakraborti, Anirban, 2017. "A model-free characterization of recurrences in stationary time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 474(C), pages 312-318.
    3. Leonenko, Nikolai & Scalas, Enrico & Trinh, Mailan, 2017. "The fractional non-homogeneous Poisson process," Statistics & Probability Letters, Elsevier, vol. 120(C), pages 147-156.
    4. Beghin, Luisa & Macci, Claudio, 2017. "Asymptotic results for a multivariate version of the alternative fractional Poisson process," Statistics & Probability Letters, Elsevier, vol. 129(C), pages 260-268.
    5. Beghin, Luisa & Macci, Claudio, 2013. "Large deviations for fractional Poisson processes," Statistics & Probability Letters, Elsevier, vol. 83(4), pages 1193-1202.
    6. Alessandro Gregorio & Francesco Iafrate, 2024. "Path Dynamics of Time-Changed Lévy Processes: A Martingale Approach," Journal of Theoretical Probability, Springer, vol. 37(4), pages 3246-3280, November.
    7. Orsingher, Enzo & Polito, Federico, 2012. "The space-fractional Poisson process," Statistics & Probability Letters, Elsevier, vol. 82(4), pages 852-858.
    8. Davide Cocco & Massimiliano Giona, 2021. "Generalized Counting Processes in a Stochastic Environment," Mathematics, MDPI, vol. 9(20), pages 1-19, October.
    9. Orsingher, Enzo & Polito, Federico, 2013. "On the integral of fractional Poisson processes," Statistics & Probability Letters, Elsevier, vol. 83(4), pages 1006-1017.

  7. Kaizoji, Taisei, 2010. "Multiple equilibria and chaos in a discrete tâtonnement process," MPRA Paper 24002, University Library of Munich, Germany.

    Cited by:

    1. Cavalli, Fausto & Naimzada, Ahmad, 2015. "A tâtonnement process with fading memory, stabilization and optimal speed of convergence," Chaos, Solitons & Fractals, Elsevier, vol. 79(C), pages 116-129.

  8. Kaizoji, Taisei (kaizoji@icu.ac.jp), 2010. "A Behavioral Model of Bubbles and Crashes," MPRA Paper 20352, University Library of Munich, Germany.

    Cited by:

    1. Andreas D. Huesler & Didier Sornette & C. H. Hommes, 2012. "Super-Exponential Bubbles in Lab Experiments: Evidence for Anchoring Over-Optimistic Expectations on Price," Swiss Finance Institute Research Paper Series 12-20, Swiss Finance Institute.
    2. Kaizoji, Taisei & Leiss, Matthias & Saichev, Alexander & Sornette, Didier, 2015. "Super-exponential endogenous bubbles in an equilibrium model of fundamentalist and chartist traders," Journal of Economic Behavior & Organization, Elsevier, vol. 112(C), pages 289-310.
    3. Kaizoji, Taisei, 2010. "Carry Trade, Forward Premium Puzzle and Currency Crisis," MPRA Paper 21432, University Library of Munich, Germany.
    4. T. Kaizoji & M. Leiss & A. Saichev & D. Sornette, 2011. "Super-exponential endogenous bubbles in an equilibrium model of rational and noise traders," Papers 1109.4726, arXiv.org, revised Mar 2014.

  9. Kaizoji, Taisei, 2010. "Carry Trade, Forward Premium Puzzle and Currency Crisis," MPRA Paper 21432, University Library of Munich, Germany.

    Cited by:

    1. Zhang, Ziyun & Chen, Su & Li, Bo, 2022. "Does previous carry trade position affect following investors' decision-making and carry returns?," International Review of Financial Analysis, Elsevier, vol. 80(C).

  10. T. Kaizoji & D. Sornette, 2008. "Market bubbles and crashes," Papers 0812.2449, arXiv.org.

    Cited by:

    1. Zhi-Qiang Jiang & Wei-Xing Zhou & Didier Sornette & Ryan Woodard & Ken Bastiaensen & Peter Cauwels, 2009. "Bubble Diagnosis and Prediction of the 2005-2007 and 2008-2009 Chinese stock market bubbles," Papers 0909.1007, arXiv.org, revised Oct 2009.
    2. Helmut Herwartz & Konstantin A. Kholodilin, 2011. "In-Sample and Out-of-Sample Prediction of Stock Market Bubbles: Cross-Sectional Evidence," Discussion Papers of DIW Berlin 1173, DIW Berlin, German Institute for Economic Research.
    3. Celia Anteneodo & Silvio M. Duarte Queiros, 2009. "Statistical mixing and aggregation in Feller diffusion," Papers 0910.1394, arXiv.org.
    4. Leiss, Matthias & Nax, Heinrich H. & Sornette, Didier, 2015. "Super-exponential growth expectations and the global financial crisis," LSE Research Online Documents on Economics 65434, London School of Economics and Political Science, LSE Library.
    5. Li Lin & Didier Sornette, 2009. "Diagnostics of Rational Expectation Financial Bubbles with Stochastic Mean-Reverting Termination Times," Papers 0911.1921, arXiv.org.
    6. Vladimir Filimonov & Guilherme Demos & Didier Sornette, 2016. "Modified Profile Likelihood Inference and Interval Forecast of the Burst of Financial Bubbles," Swiss Finance Institute Research Paper Series 16-12, Swiss Finance Institute.
    7. D. Sornette & R. Woodard, "undated". "Financial Bubbles, Real Estate bubbles, Derivative Bubbles, and the Financial and Economic Crisis," Working Papers CCSS-09-003, ETH Zurich, Chair of Systems Design.
    8. Damian Smug & Peter Ashwin & Didier Sornette, 2018. "Predicting financial market crashes using ghost singularities," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-20, March.
    9. Markus Vogl, 2022. "Quantitative modelling frontiers: a literature review on the evolution in financial and risk modelling after the financial crisis (2008–2019)," SN Business & Economics, Springer, vol. 2(12), pages 1-69, December.
    10. Riza Demirer & Guilherme Demos & Rangan Gupta & Didier Sornette, 2017. "On the Predictability of Stock Market Bubbles: Evidence from LPPLS ConfidenceTM Multi-scale Indicators," Working Papers 201752, University of Pretoria, Department of Economics.
    11. Didier Sornette & Ryan Woodard, 2009. "Financial Bubbles, Real Estate bubbles, Derivative Bubbles, and the Financial and Economic Crisis," Papers 0905.0220, arXiv.org.

  11. Cheoljun Eom & Woo-Sung Jung & Taisei Kaizoji & Seunghwan Kim, 2008. "Effect of changing data size on eigenvalues in the Korean and Japanese stock markets," Papers 0811.4021, arXiv.org, revised Jun 2009.

    Cited by:

    1. Eom, Cheoljun & Park, Jong Won, 2018. "A new method for better portfolio investment: A case of the Korean stock market," Pacific-Basin Finance Journal, Elsevier, vol. 49(C), pages 213-231.
    2. Eom, Cheoljun & Kaizoji, Taisei & Livan, Giacomo & Scalas, Enrico, 2021. "Limitations of portfolio diversification through fat tails of the return Distributions: Some empirical evidence," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    3. Eom, Cheoljun, 2017. "Two-faced property of a market factor in asset pricing and diversification effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 190-199.
    4. Bommarito, Michael J. & Duran, Ahmet, 2018. "Spectral analysis of time-dependent market-adjusted return correlation matrix," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 273-282.
    5. Eom, Cheoljun & Park, Jong Won, 2021. "Investor attention, firm-specific characteristic, and momentum: A case of the Korean stock market," Research in International Business and Finance, Elsevier, vol. 57(C).
    6. Uechi, Lisa & Akutsu, Tatsuya & Stanley, H. Eugene & Marcus, Alan J. & Kenett, Dror Y., 2015. "Sector dominance ratio analysis of financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 488-509.
    7. Eom, Cheoljun & Kwon, Okyu & Jung, Woo-Sung & Kim, Seunghwan, 2010. "The effect of a market factor on information flow between stocks using the minimal spanning tree," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(8), pages 1643-1652.

  12. Woo-Sung Jung & Okyu Kwon & Fengzhong Wang & Taisei Kaizoji & Hie-Tae Moon & H. Eugene Stanley, 2007. "Group dynamics of the Japanese market," Papers 0708.0562, arXiv.org.

    Cited by:

    1. Tabak, Benjamin M. & Serra, Thiago R. & Cajueiro, Daniel O., 2009. "The expectation hypothesis of interest rates and network theory: The case of Brazil," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(7), pages 1137-1149.
    2. Teh, Boon Kin & Goo, Yik Wen & Lian, Tong Wei & Ong, Wei Guang & Choi, Wen Ting & Damodaran, Mridula & Cheong, Siew Ann, 2015. "The Chinese Correction of February 2007: How financial hierarchies change in a market crash," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 225-241.
    3. Gautier Marti & Frank Nielsen & Miko{l}aj Bi'nkowski & Philippe Donnat, 2017. "A review of two decades of correlations, hierarchies, networks and clustering in financial markets," Papers 1703.00485, arXiv.org, revised Nov 2020.
    4. Kantar, Ersin & Aslan, Alper & Deviren, Bayram & Keskin, Mustafa, 2016. "Hierarchical structure of the countries based on electricity consumption and economic growth," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 454(C), pages 1-10.
    5. Miśkiewicz, Janusz & Ausloos, Marcel, 2010. "Has the world economy reached its globalization limit?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(4), pages 797-806.
    6. Yonatan Berman & Yoash Shapira & Eshel Ben-Jacob, 2014. "Unraveling Hidden Order in the Dynamics of Developed and Emerging Markets," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-10, November.
    7. Tsai, Kuo-Ting & Lih, Jiann-Shing & Ko, Jing-Yuan, 2012. "The overnight effect on the Taiwan stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(24), pages 6497-6505.
    8. Lee, Junghoon & Youn, Janghyuk & Chang, Woojin, 2012. "Intraday volatility and network topological properties in the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1354-1360.
    9. Cheong, Siew Ann & Fornia, Robert Paulo & Lee, Gladys Hui Ting & Kok, Jun Liang & Yim, Woei Shyr & Xu, Danny Yuan & Zhang, Yiting, 2012. "The Japanese economy in crises: A time series segmentation study," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 6, pages 1-81.
    10. Tristan Millington & Mahesan Niranjan, 2020. "Construction of Minimum Spanning Trees from Financial Returns using Rank Correlation," Papers 2005.03963, arXiv.org, revised Nov 2020.
    11. Tabak, Benjamin M. & Serra, Thiago R. & Cajueiro, Daniel O., 2010. "Topological properties of stock market networks: The case of Brazil," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(16), pages 3240-3249.
    12. Millington, Tristan & Niranjan, Mahesan, 2021. "Construction of minimum spanning trees from financial returns using rank correlation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    13. Zhang, Yiting & Lee, Gladys Hui Ting & Wong, Jian Cheng & Kok, Jun Liang & Prusty, Manamohan & Cheong, Siew Ann, 2011. "Will the US economy recover in 2010? A minimal spanning tree study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(11), pages 2020-2050.

  13. Woo-Sung Jung & Fengzhong Wang & Shlomo Havlin & Taisei Kaizoji & Hie-Tae Moon & H. Eugene Stanley, 2007. "Volatility return intervals analysis of the Japanese market," Papers 0709.1725, arXiv.org.

    Cited by:

    1. Fei Ren & Gao-Feng Gu & Wei-Xing Zhou, 2009. "Scaling and memory in the return intervals of realized volatility," Papers 0904.1107, arXiv.org, revised Aug 2009.
    2. Ren, Fei & Guo, Liang & Zhou, Wei-Xing, 2009. "Statistical properties of volatility return intervals of Chinese stocks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(6), pages 881-890.
    3. Wen-Jie Xie & Zhi-Qiang Jiang & Wei-Xing Zhou, 2012. "Extreme value statistics and recurrence intervals of NYMEX energy futures volatility," Papers 1211.5502, arXiv.org.
    4. Jin-Hu Liu & Zi-Ke Zhang & Lingjiao Chen & Chuang Liu & Chengcheng Yang & Xueqi Wang, 2014. "Gravity Effects on Information Filtering and Network Evolving," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-7, March.
    5. Mahata, Ajit & Bal, Debi Prasad & Nurujjaman, Md, 2020. "Identification of short-term and long-term time scales in stock markets and effect of structural break," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    6. Wang, Guochao & Zheng, Shenzhou & Wang, Jun, 2020. "Fluctuation and volatility dynamics of stochastic interacting energy futures price model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    7. Zhi-Qiang Jiang & Askery A. Canabarro & Boris Podobnik & H. Eugene Stanley & Wei-Xing Zhou, 2015. "Early warning of large volatilities based on recurrence interval analysis in Chinese stock markets," Papers 1508.07505, arXiv.org.
    8. Xiao-Hui Ni & Zhi-Qiang Jiang & Gao-Feng Gu & Fei Ren & Wei Chen & Wei-Xing Zhou, 2009. "Scaling and memory in the non-poisson process of limit order cancelation," Papers 0911.0057, arXiv.org.

  14. Lux, Thomas & Kaizoji, Taisei, 2006. "Forecasting volatility and volume in the Tokyo stock market: Long memory, fractality and regime switching," Economics Working Papers 2006-13, Christian-Albrechts-University of Kiel, Department of Economics.

    Cited by:

    1. Aßmuth, Pascal, 2015. "Stock price related financial fragility and growth patterns," Center for Mathematical Economics Working Papers 539, Center for Mathematical Economics, Bielefeld University.
    2. Lux, Thomas & Segnon, Mawuli & Gupta, Rangan, 2016. "Forecasting crude oil price volatility and value-at-risk: Evidence from historical and recent data," Energy Economics, Elsevier, vol. 56(C), pages 117-133.
    3. Chang, C-L. & McAleer, M.J. & Tansuchat, R., 2012. "Modelling Long Memory Volatility in Agricultural Commodity Futures Returns," Econometric Institute Research Papers EI 2012-15, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Xin-Lan Fu & Xing-Lu Gao & Zheng Shan & Zhi-Qiang Jiang & Wei-Xing Zhou, 2018. "Multifractal characteristics and return predictability in the Chinese stock markets," Papers 1806.07604, arXiv.org.
    5. Elliott, Robert J. & Siu, Tak Kuen & Badescu, Alexandru, 2011. "On pricing and hedging options in regime-switching models with feedback effect," Journal of Economic Dynamics and Control, Elsevier, vol. 35(5), pages 694-713, May.
    6. González-Pla, Francisco & Lovreta, Lidija, 2019. "Persistence in firm’s asset and equity volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    7. Caraiani, Petre & Haven, Emmanuel, 2015. "Evidence of multifractality from CEE exchange rates against Euro," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 395-407.
    8. Thomas Lux & Jaba Ghonghadze, 2011. "Modeling the Dynamics of EU Economic Sentiment Indicators: An Interaction-Based Approach," Post-Print hal-00711445, HAL.
    9. Aßmuth, Pascal, 2017. "Stock price related financial fragility and growth patterns," Economics Discussion Papers 2017-108, Kiel Institute for the World Economy (IfW Kiel).
    10. Mehmet Sahiner, 2022. "Forecasting volatility in Asian financial markets: evidence from recursive and rolling window methods," SN Business & Economics, Springer, vol. 2(10), pages 1-74, October.
    11. Schmitt, Noemi & Westerhoff, Frank, 2014. "Speculative behavior and the dynamics of interacting stock markets," Journal of Economic Dynamics and Control, Elsevier, vol. 45(C), pages 262-288.
    12. Cai, Guixin & Zhang, Hao & Chen, Ziyue, 2019. "Comovement between commodity sectors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1247-1258.
    13. Idier, J., 2008. "Long term vs. short term comovements in stock markets: the use of Markov-switching multifractal models," Working papers 218, Banque de France.
    14. Cevik, Emrah Ismail, 2012. "İstanbul Menkul Kıymetler Borsası’nda etkin piyasa hipotezinin uzun hafıza modelleri ile analizi: sektörel bazda bir inceleme [The testing of efficient market hypothesis in the Istanbul Stock Excha," MPRA Paper 71484, University Library of Munich, Germany, revised 2012.
    15. Lux, Thomas & Segnon, Mawuli & Gupta, Rangan, 2015. "Modeling and forecasting crude oil price volatility: Evidence from historical and recent data," FinMaP-Working Papers 31, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    16. Nasr, Adnen Ben & Lux, Thomas & Ajm, Ahdi Noomen & Gupta, Rangan, 2014. "Forecasting the volatility of the dow jones islamic stock market index: Long memory vs. regime switching," Economics Working Papers 2014-07, Christian-Albrechts-University of Kiel, Department of Economics.
    17. Groß-Klußmann, Axel & Hautsch, Nikolaus, 2011. "Predicting bid-ask spreads using long memory autoregressive conditional poisson models," SFB 649 Discussion Papers 2011-044, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    18. Argyroudis, G. & Siokis, F., 2018. "The complexity of the HANG SENG Index and its constituencies during the 2007–2008 Great Recession," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 495(C), pages 463-474.
    19. Lux, Thomas & Morales-Arias, Leonardo, 2009. "Forecasting volatility under fractality, regime-switching, long memory and student-t innovations," Kiel Working Papers 1532, Kiel Institute for the World Economy (IfW Kiel).
    20. Lux, Thomas & Morales-Arias, Leonardo & Sattarhoff, Cristina, 2011. "A Markov-switching multifractal approach to forecasting realized volatility," Kiel Working Papers 1737, Kiel Institute for the World Economy (IfW Kiel).
    21. Malinda & Maya & Jo-Hui & Chen, 2022. "Testing for the Long Memory and Multiple Structural Breaks in Consumer ETFs," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 12(6), pages 1-6.
    22. Leandro Maciel, 2012. "A Hybrid Fuzzy GJR-GARCH Modeling Approach for Stock Market Volatility Forecasting," Brazilian Review of Finance, Brazilian Society of Finance, vol. 10(3), pages 337-367.
    23. Ivan Letteri & Giuseppe Della Penna & Giovanni De Gasperis & Abeer Dyoub, 2022. "DNN-ForwardTesting: A New Trading Strategy Validation using Statistical Timeseries Analysis and Deep Neural Networks," Papers 2210.11532, arXiv.org.
    24. Aßmuth, Pascal, 2020. "Stock price related financial fragility and growth patterns," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 14, pages 1-34.
    25. Lang, Korbinian & Auer, Benjamin R., 2020. "The economic and financial properties of crude oil: A review," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    26. Lux, Thomas & Morales-Arias, Leonardo, 2010. "Forecasting volatility under fractality, regime-switching, long memory and student-t innovations," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2676-2692, November.
    27. Lux, Thomas & Morales-Arias, Leonardo, 2010. "Relative forecasting performance of volatility models: Monte Carlo evidence," Kiel Working Papers 1582, Kiel Institute for the World Economy (IfW Kiel).
    28. 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.
    29. Kang, Sang Hoon & Yoon, Seong-Min, 2008. "Long memory features in the high frequency data of the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(21), pages 5189-5196.
    30. Segnon, Mawuli & Lux, Thomas, 2013. "Multifractal models in finance: Their origin, properties, and applications," Kiel Working Papers 1860, Kiel Institute for the World Economy (IfW Kiel).
    31. Wang, Yudong & Wu, Chongfeng & Yang, Li, 2016. "Forecasting crude oil market volatility: A Markov switching multifractal volatility approach," International Journal of Forecasting, Elsevier, vol. 32(1), pages 1-9.
    32. Kukacka, Jiri & Kristoufek, Ladislav, 2021. "Does parameterization affect the complexity of agent-based models?," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 324-356.
    33. Kukacka, Jiri & Kristoufek, Ladislav, 2020. "Do ‘complex’ financial models really lead to complex dynamics? Agent-based models and multifractality," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    34. Korkmaz, Turhan & Cevik, Emrah Ismail & Özataç, Nesrin, 2009. "Testing for long memory in ISE using Arfima-Figarch model and structural break test," MPRA Paper 71302, University Library of Munich, Germany.
    35. Liu, Yufang & Zhang, Weiguo & Fu, Junhui, 2016. "Binomial Markov-Switching Multifractal model with Skewed t innovations and applications to Chinese SSEC Index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 56-66.
    36. Cheng, Fangzheng & Fan, Tijun & Fan, Dandan & Li, Shanling, 2018. "The prediction of oil price turning points with log-periodic power law and multi-population genetic algorithm," Energy Economics, Elsevier, vol. 72(C), pages 341-355.
    37. Siokis, Fotios M., 2014. "European economies in crisis: A multifractal analysis of disruptive economic events and the effects of financial assistance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 283-292.
    38. Liu, Ruipeng & Lux, Thomas, 2010. "Flexible and robust modelling of volatility comovements: a comparison of two multifractal models," Kiel Working Papers 1594, Kiel Institute for the World Economy (IfW Kiel).
    39. Siokis, Fotios M., 2013. "Multifractal analysis of stock exchange crashes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(5), pages 1164-1171.
    40. Ma, Feng & Wang, Jiqian & Wahab, M.I.M. & Ma, Yuanhui, 2023. "Stock market volatility predictability in a data-rich world: A new insight," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1804-1819.
    41. Söderberg, Jonas, 2008. "Do Macroeconomic Variables Forecast Changes in Liquidity? An Out-of-sample Study on the Order-driven Stock Markets in Scandinavia," CAFO Working Papers 2009:10, Linnaeus University, Centre for Labour Market Policy Research (CAFO), School of Business and Economics.
    42. Augustyniak, Maciej & Dufays, Arnaud, 2018. "Modeling macroeconomic series with regime-switching models characterized by a high-dimensional state space," Economics Letters, Elsevier, vol. 170(C), pages 122-126.
    43. Lux, Thomas, 2013. "Exact solutions for the transient densities of continuous-time Markov switching models: With an application to the poisson multifractal model," Kiel Working Papers 1871, Kiel Institute for the World Economy (IfW Kiel).
    44. Yonghong Jiang & Jinqi Mu & He Nie & Lanxin Wu, 2022. "Time‐frequency analysis of risk spillovers from oil to BRICS stock markets: A long‐memory Copula‐CoVaR‐MODWT method," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3386-3404, July.
    45. Calvet, Laurent E. & Fearnley, Marcus & Fisher, Adlai J. & Leippold, Markus, 2015. "What is beneath the surface? Option pricing with multifrequency latent states," Journal of Econometrics, Elsevier, vol. 187(2), pages 498-511.
    46. Kurt Dopfer, 2011. "Economics in a Cultural Key: Complexity and Evolution Revisited," Chapters, in: John B. Davis & D. Wade Hands (ed.), The Elgar Companion to Recent Economic Methodology, chapter 14, Edward Elgar Publishing.
    47. Wamg, Jianxin, 2011. "Forecasting Volatility in Asian Stock Markets: Contributions of Local, Regional, and Global Factors," Asian Development Review, Asian Development Bank, vol. 28(2), pages 32-57.

  15. Taisei Kaizoji, 2006. "An interacting-agent model of financial markets from the viewpoint of nonextensive statistical mechanics," Papers physics/0601106, arXiv.org, revised Apr 2006.

    Cited by:

    1. Quanbo Zha & Gang Kou & Hengjie Zhang & Haiming Liang & Xia Chen & Cong-Cong Li & Yucheng Dong, 2020. "Opinion dynamics in finance and business: a literature review and research opportunities," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-22, December.
    2. Martins, Francisco Leonardo Bezerra & do Nascimento, José Cláudio, 2022. "Power law dynamics in genealogical graphs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    3. Ryo Murakami & Tomomichi Nakamura & Shin Kimura & Masashi Manabe & Toshihiro Tanizawa, 2014. "On possible origins of trends in financial market price changes," Papers 1406.5276, arXiv.org, revised Nov 2014.
    4. Zhao, Pan & Pan, Jian & Yue, Qin & Zhang, Jinbo, 2021. "Pricing of financial derivatives based on the Tsallis statistical theory," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    5. Răzvan-Cornel Sfetcu & Vasile Preda, 2024. "Order Properties Concerning Tsallis Residual Entropy," Mathematics, MDPI, vol. 12(3), pages 1-16, January.
    6. Răzvan-Cornel Sfetcu & Vasile Preda, 2023. "Fractal Divergences of Generalized Jacobi Polynomials," Mathematics, MDPI, vol. 11(16), pages 1-12, August.
    7. Murakami, Ryo & Nakamura, Tomomichi & Kimura, Shin & Manabe, Masashi & Tanizawa, Toshihiro, 2015. "On possible origins of trends in financial market price changes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 420(C), pages 179-189.

  16. Taisei Kaizoji, 2006. "Power laws and market crashes," Papers physics/0603138, arXiv.org.

    Cited by:

    1. Takayuki Mizuno & Takaaki Ohnishi & Tsutomu Watanabe, 2016. "Power laws in market capitalization during the dot-com and Shanghai bubble periods," Evolutionary and Institutional Economics Review, Springer, vol. 13(2), pages 445-454, December.
    2. Takayuki Mizuno & Takaaki Ohnishi & Tsutomu Watanabe, 2016. "Power laws in market capitalization during the Dot-com and Shanghai bubble periods," CARF F-Series CARF-F-392, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    3. Blackwell, Calvin, 2018. "Power Laws in Real Estate Prices? Some Evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 90-98.
    4. Tabak, B.M. & Takami, M.Y. & Cajueiro, D.O. & Petitinga, A., 2009. "Quantifying price fluctuations in the Brazilian stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(1), pages 59-62.
    5. Lisa Borland & Yoan Hassid, 2010. "Market panic on different time-scales," Papers 1010.4917, arXiv.org.
    6. Borland, Lisa, 2016. "Exploring the dynamics of financial markets: from stock prices to strategy returns," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 59-74.
    7. T. Kaizoji, 2006. "A precursor of market crashes: Empirical laws of Japan's internet bubble," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 50(1), pages 123-127, March.
    8. Takayuki Mizuno & Takaaki Ohnishi & Tsutomu Watanabe, 2019. "Detecting stock market bubbles based on the cross-sectional dispersion of stock prices," CARF F-Series CARF-F-463, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    9. Takayuki Mizuno & Takaaki Ohnishi & Tsutomu Watanabe, 2016. "Power laws in market capitalization during the Dot-com and Shanghai bubble periods," UTokyo Price Project Working Paper Series 070, University of Tokyo, Graduate School of Economics.
    10. Mizuno, Takayuki & Ohnishi, Takaaki & Watanabe, Tsutomu, 2017. "Stock market bubble detection based on the price dispersion among similar listed Firms," HIT-REFINED Working Paper Series 67, Institute of Economic Research, Hitotsubashi University.
    11. Takayuki Mizuno & Takaaki Ohnishi & Tsutomu Watanabe, 2019. "Detecting stock market bubbles based on the cross-sectional dispersion of stock prices," Working Papers on Central Bank Communication 010, University of Tokyo, Graduate School of Economics.
    12. Mizuno, Takayuki & Ohnishi, Takaaki & Watanabe, Tsutomu, 2016. "Power law in market capitalization during Dot-com and Shanghai bubble periods," HIT-REFINED Working Paper Series 60, Institute of Economic Research, Hitotsubashi University.

  17. Enrico Scalas & Taisei Kaizoji & Michael Kirchler & Juergen Huber & Alessandra Tedeschi, 2006. "Waiting times between orders and trades in double-auction markets," Papers physics/0608273, arXiv.org.

    Cited by:

    1. Cappellini, Alessandro & Ferraris, Gianluigi, 2007. "Waiting Times in Simulated Stock Markets," MPRA Paper 7324, University Library of Munich, Germany.
    2. Huber, Jürgen & Kleinlercher, Daniel & Kirchler, Michael, 2012. "The impact of a financial transaction tax on stylized facts of price returns—Evidence from the lab," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1248-1266.
    3. Politi, Mauro & Scalas, Enrico, 2007. "Activity spectrum from waiting-time distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 383(1), pages 43-48.
    4. Fei Ren & Gao-Feng Gu & Wei-Xing Zhou, 2009. "Scaling and memory in the return intervals of realized volatility," Papers 0904.1107, arXiv.org, revised Aug 2009.
    5. Scalas, Enrico, 2007. "Mixtures of compound Poisson processes as models of tick-by-tick financial data," Chaos, Solitons & Fractals, Elsevier, vol. 34(1), pages 33-40.
    6. Kazuto Sasai & Yukio-Pegio Gunji & Tetsuo Kinoshita, 2017. "Intermittent Behavior Induced By Asynchronous Interactions In A Continuous Double Auction Model," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 20(02n03), pages 1-21, March.
    7. Jiang, Zhi-Qiang & Chen, Wei & Zhou, Wei-Xing, 2008. "Scaling in the distribution of intertrade durations of Chinese stocks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(23), pages 5818-5825.
    8. Schinckus, C., 2013. "Between complexity of modelling and modelling of complexity: An essay on econophysics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3654-3665.
    9. Kreer, Markus & Kizilersu, Ayse & Thomas, Anthony W., 2022. "Censored expectation maximization algorithm for mixtures: Application to intertrade waiting times," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 587(C).
    10. Bertram, William K., 2008. "Measuring time dependent volatility and cross-sectional correlation in Australian equity returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(13), pages 3183-3191.
    11. Zhang, Zhikun & Dai, Min & Wang, Xiangjun, 2023. "Statistical inference for mixed jump processes by Markov switching model with application to identify seismicity levels," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 632(P1).
    12. Schütz, Gunter M. & de Almeida Prado, Fernando Pigeard & Harris, Rosemary J. & Belitsky, Vladimir, 2009. "Short-time behaviour of demand and price viewed through an exactly solvable model for heterogeneous interacting market agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(19), pages 4126-4144.
    13. Zhou, Bin & Xie, Jia-Rong & Yan, Xiao-Yong & Wang, Nianxin & Wang, Bing-Hong, 2017. "A model of task-deletion mechanism based on the priority queueing system of Barabási," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 415-421.
    14. V. Filimonov & D. Sornette, 2015. "Apparent criticality and calibration issues in the Hawkes self-excited point process model: application to high-frequency financial data," Quantitative Finance, Taylor & Francis Journals, vol. 15(8), pages 1293-1314, August.
    15. Kirchler, Michael & Huber, Jürgen, 2009. "An exploration of commonly observed stylized facts with data from experimental asset markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(8), pages 1631-1658.
    16. Scalas, Enrico & Rapallo, Fabio & Radivojević, Tijana, 2017. "Low-traffic limit and first-passage times for a simple model of the continuous double auction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 485(C), pages 61-72.
    17. Hayashi, Katsuhiko & Kaizoji, Taisei & Pichl, Lukáš, 2007. "Correlation patterns of NIKKEI index constituents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 383(1), pages 16-21.
    18. Zhi-Qiang Jiang & Wei Chen & Wei-Xing Zhou, 2008. "Detrended fluctuation analysis of intertrade durations," Papers 0806.2444, arXiv.org.
    19. Bence Toth & Enrico Scalas, 2007. "The value of information in financial markets: An agent-based simulation," Papers 0712.2687, arXiv.org.
    20. Yong-Ping Ruan & Wei-Xing Zhou, 2010. "Long-term correlations and multifractal nature in the intertrade durations of a liquid Chinese stock and its warrant," Papers 1008.0160, arXiv.org.
    21. Gunter M. Schutz & Fernando Pigeard de Almeida Prado & Rosemary J. Harris & Vladimir Belitsky, 2007. "Short-time behaviour of demand and price viewed through an exactly solvable model for heterogeneous interacting market agents," Papers 0801.0003, arXiv.org, revised Jun 2009.
    22. Vladimir Filimonov & Didier Sornette, 2013. "Apparent criticality and calibration issues in the Hawkes self-excited point process model: application to high-frequency financial data," Papers 1308.6756, arXiv.org, revised Jul 2014.
    23. Bertram, William K., 2009. "Optimal trading strategies for Itô diffusion processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(14), pages 2865-2873.

  18. Taisei Kaizoji, 2006. "Statistical properties of absolute log-returns and a stochastic model of stock markets with heterogeneous agents," Papers physics/0603139, arXiv.org.

    Cited by:

    1. Taisei Kaizoji, 2010. "Stock volatility in the periods of booms and stagnations," EERI Research Paper Series EERI_RP_2010_07, Economics and Econometrics Research Institute (EERI), Brussels.
    2. Kerim Eser AFÞAR & Zakayo S. KISAVA, 2018. "The analysis of bubbles and crashes on financial markets for emerging economies: Evidenced From BRICS," Turkish Economic Review, KSP Journals, vol. 5(1), pages 1-11, March.

  19. Taisei Kaizoji & Hiroshi Iyetomi & Yuichi Ikeda, 2005. "Re-examination of the size distribution of firms," Papers physics/0512124, arXiv.org, revised Mar 2006.

    Cited by:

    1. Segarra, Agustí & Teruel, Mercedes, 2012. "An appraisal of firm size distribution: Does sample size matter?," Journal of Economic Behavior & Organization, Elsevier, vol. 82(1), pages 314-328.
    2. Lina M Cortés & Juan M Lozada & Javier Perote, 2021. "Firm size and economic concentration: An analysis from a lognormal expansion," PLOS ONE, Public Library of Science, vol. 16(7), pages 1-21, July.
    3. Stankov, Petar & Vasilev, Aleksandar, 2015. "What Explains the Diversity of Regulatory Reform Outcomes?," EconStor Research Reports 141915, ZBW - Leibniz Information Centre for Economics.
    4. Stankov, Petar & Vasilev, Aleksandar, 2019. "Business reform outcomes: Why so different?," Journal of Policy Modeling, Elsevier, vol. 41(6), pages 1109-1127.
    5. Ivan O. Kitov, 2009. "What is the best firm size to invest?," Papers 0903.0286, arXiv.org.
    6. Chen Ge & Shu-Guang Zhang & Bin Wang, 2020. "Modeling the joint distribution of firm size and firm age based on grouped data," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-19, July.
    7. Lina Cortés & Juan M. Lozada & Javier Perote, 2019. "Firm size and concentration inequality: A flexible extension of Gibrat’s law," Documentos de Trabajo de Valor Público 17205, Universidad EAFIT.
    8. Lina Cortés & Andrés Mora-Valencia & Javier Perote, 2017. "Measuring firm size distribution with semi-nonparametric densities," Documentos de Trabajo de Valor Público 15300, Universidad EAFIT.
    9. Kang, Sang Hoon & Jiang, Zhuhua & Cheong, Chongcheul & Yoon, Seong-Min, 2011. "Changes of firm size distribution: The case of Korea," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(2), pages 319-327.
    10. Lublóy, Ágnes & Szenes, Márk, 2007. "Az ügyfélelvándorlás kereskedelmi banki modellezése [Modelling the migration of commercial bank clients]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(10), pages 915-934.
    11. Gao, Baojun & Chan, Wai Kin (Victor) & Li, Hongyi, 2015. "On the increasing inequality in size distribution of China's listed companies," China Economic Review, Elsevier, vol. 36(C), pages 25-41.

  20. Taisei Kaizoji, 2005. "A Precursor of Market Crashes," Papers physics/0510055, arXiv.org, revised Mar 2006.

    Cited by:

    1. Li Lin & Didier Sornette, 2023. "The inverse Cox-Ingersoll-Ross process for parsimonious financial price modeling," Papers 2302.11423, arXiv.org, revised Jun 2023.
    2. Bikramaditya Ghosh & Spyros Papathanasiou & Georgios Pergeris, 2022. "Did cryptocurrencies exhibit log‐periodic power law signature during the second wave of COVID‐19?," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 51(3), November.
    3. Vidal-Tomás, David & Alfarano, Simone, 2018. "An agent based early warning indicator for financial market instability," MPRA Paper 89693, University Library of Munich, Germany.
    4. John Rutledge, 2015. "Economics as energy framework: Complexity, turbulence, financial crises, and protectionism," Review of Financial Economics, John Wiley & Sons, vol. 25(1), pages 10-18, April.
    5. Guevara Hidalgo, Esteban, 2017. "Bin size independence in intra-day seasonalities for relative prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 722-732.
    6. Kerim Eser AFÞAR & Zakayo S. KISAVA, 2018. "The analysis of bubbles and crashes on financial markets for emerging economies: Evidenced From BRICS," Turkish Economic Review, KSP Journals, vol. 5(1), pages 1-11, March.
    7. Cajueiro, Daniel O. & Tabak, Benjamin M. & Werneck, Filipe K., 2009. "Can we predict crashes? The case of the Brazilian stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(8), pages 1603-1609.
    8. Graham Bird & Wenti Du & Thomas Willett, 2017. "Behavioral Finance and Efficient Markets: What does the Euro Crisis Tell us?," Open Economies Review, Springer, vol. 28(2), pages 273-295, April.
    9. Todorova, Lora & Vogt, Bodo, 2011. "Power law distribution in high frequency financial data? An econometric analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4433-4444.
    10. Brée, David S. & Joseph, Nathan Lael, 2013. "Testing for financial crashes using the Log Periodic Power Law model," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 287-297.
    11. Frederic Abergel & Nicolas Huth & Ioane Muni Toke, 2009. "Financial bubbles analysis with a cross-sectional estimator," Papers 0909.2885, arXiv.org.
    12. Xavier Gabaix, 2008. "Power Laws in Economics and Finance," NBER Working Papers 14299, National Bureau of Economic Research, Inc.
    13. Rutledge, John, 2015. "Economics as energy framework: Complexity, turbulence, financial crises, and protectionism," Review of Financial Economics, Elsevier, vol. 25(C), pages 10-18.
    14. Blackwell, Calvin, 2018. "Power Laws in Real Estate Prices? Some Evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 90-98.
    15. Esteban Guevara Hidalgo, 2015. "Bin Size Independence in Intra-day Seasonalities for Relative Prices," Papers 1501.05176, arXiv.org, revised Dec 2016.
    16. Kaizoji, Taisei & Miyano, Michiko, 2016. "Why does the power law for stock price hold?," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 19-23.

  21. Lux, Thomas & Kaizoji, Taisei, 2004. "Forecasting volatility and volume in the Tokyo stock market: The advantage of long memory models," Economics Working Papers 2004-05, Christian-Albrechts-University of Kiel, Department of Economics.

    Cited by:

    1. Chortareas, Georgios & Jiang, Ying & Nankervis, John. C., 2011. "Forecasting exchange rate volatility using high-frequency data: Is the euro different?," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1089-1107, October.
    2. Georgios Chortareas & John Nankervis & Ying Jiang, 2007. "Forecasting Exchange Rate Volatility with High Frequency Data: Is the Euro Different?," Money Macro and Finance (MMF) Research Group Conference 2006 79, Money Macro and Finance Research Group.
    3. Rachna Mahalwala, 2016. "A Study of Expiration-day Effects of Index Derivatives Trading in India," Metamorphosis: A Journal of Management Research, , vol. 15(1), pages 10-19, June.

  22. Taisei Kaizoji & Thomas Lux, 2004. "Forecasting Volume and Volatility in the Tokyo Stock Market: The Advantage of Long Memory Models," Computing in Economics and Finance 2004 158, Society for Computational Economics.

    Cited by:

    1. Chortareas, Georgios & Jiang, Ying & Nankervis, John. C., 2011. "Forecasting exchange rate volatility using high-frequency data: Is the euro different?," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1089-1107, October.
    2. Georgios Chortareas & John Nankervis & Ying Jiang, 2007. "Forecasting Exchange Rate Volatility with High Frequency Data: Is the Euro Different?," Money Macro and Finance (MMF) Research Group Conference 2006 79, Money Macro and Finance Research Group.
    3. Rachna Mahalwala, 2016. "A Study of Expiration-day Effects of Index Derivatives Trading in India," Metamorphosis: A Journal of Management Research, , vol. 15(1), pages 10-19, June.

  23. Taisei Kaizoji & Michiyo Kaizoji, 2003. "A mechanism leading bubbles to crashes: the case of Japan's land markets," Papers cond-mat/0312404, arXiv.org, revised Mar 2006.

    Cited by:

    1. Kaizoji, Taisei & Kaizoji, Michiyo, 2004. "Power law for ensembles of stock prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 240-243.

  24. Taisei Kaizoji, 2003. "Intermittent chaos in a model of financial markets with heterogeneous agents," Papers nlin/0312065, arXiv.org.

    Cited by:

    1. Doris Neuberger & Roger Rissi, 2014. "Macroprudential Banking Regulation: Does One Size Fit All?," Journal of Banking and Financial Economics, University of Warsaw, Faculty of Management, vol. 1(1), pages 5-28, May.

  25. Taisei Kaizoji & Michiyo Kaizoji, 2003. "Power law for ensembles of stock prices," Papers cond-mat/0312406, arXiv.org, revised Mar 2006.

    Cited by:

    1. Fei Ren & Gao-Feng Gu & Wei-Xing Zhou, 2009. "Scaling and memory in the return intervals of realized volatility," Papers 0904.1107, arXiv.org, revised Aug 2009.
    2. Brée, David S. & Joseph, Nathan Lael, 2013. "Testing for financial crashes using the Log Periodic Power Law model," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 287-297.
    3. Frederic Abergel & Nicolas Huth & Ioane Muni Toke, 2009. "Financial bubbles analysis with a cross-sectional estimator," Papers 0909.2885, arXiv.org.
    4. Tabak, B.M. & Takami, M.Y. & Cajueiro, D.O. & Petitinga, A., 2009. "Quantifying price fluctuations in the Brazilian stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(1), pages 59-62.
    5. Kaizoji, Taisei & Miyano, Michiko, 2016. "Why does the power law for stock price hold?," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 19-23.
    6. Kaizoji, Taisei, 2004. "Inflation and deflation in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 343(C), pages 662-668.

  26. Taisei Kaizoji & Michiyo Kaizoji, 2003. "Power law for the calm-time interval of price changes," Papers cond-mat/0312560, arXiv.org, revised Mar 2006.

    Cited by:

    1. Shapoval, A., 2010. "Prediction problem for target events based on the inter-event waiting time," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(22), pages 5145-5154.
    2. Enrico Scalas & Taisei Kaizoji & Michael Kirchler & Juergen Huber & Alessandra Tedeschi, 2006. "Waiting times between orders and trades in double-auction markets," Papers physics/0608273, arXiv.org.
    3. Wen-Jie Xie & Zhi-Qiang Jiang & Wei-Xing Zhou, 2012. "Extreme value statistics and recurrence intervals of NYMEX energy futures volatility," Papers 1211.5502, arXiv.org.
    4. Enrico Scalas & Rudolf Gorenflo & Hugh Luckock & Francesco Mainardi & Maurizio Mantelli & Marco Raberto, 2005. "Anomalous waiting times in high-frequency financial data," Papers physics/0505210, arXiv.org.
    5. Scalas, Enrico, 2006. "The application of continuous-time random walks in finance and economics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 362(2), pages 225-239.
    6. Jovanovic, Franck & Schinckus, Christophe, 2017. "Econophysics and Financial Economics: An Emerging Dialogue," OUP Catalogue, Oxford University Press, number 9780190205034.
    7. Chi Zhang & Zhengning Pu & Qin Zhou, 2018. "Sustainable Energy Consumption in Northeast Asia: A Case from China’s Fuel Oil Futures Market," Sustainability, MDPI, vol. 10(1), pages 1-14, January.
    8. Enrico Scalas, 2006. "Five Years of Continuous-time Random Walks in Econophysics," Lecture Notes in Economics and Mathematical Systems, in: Akira Namatame & Taisei Kaizouji & Yuuji Aruka (ed.), The Complex Networks of Economic Interactions, pages 3-16, Springer.
    9. Tabak, B.M. & Takami, M.Y. & Cajueiro, D.O. & Petitinga, A., 2009. "Quantifying price fluctuations in the Brazilian stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(1), pages 59-62.
    10. Zhi-Qiang Jiang & Askery A. Canabarro & Boris Podobnik & H. Eugene Stanley & Wei-Xing Zhou, 2015. "Early warning of large volatilities based on recurrence interval analysis in Chinese stock markets," Papers 1508.07505, arXiv.org.
    11. Xiao-Hui Ni & Zhi-Qiang Jiang & Gao-Feng Gu & Fei Ren & Wei Chen & Wei-Xing Zhou, 2009. "Scaling and memory in the non-poisson process of limit order cancelation," Papers 0911.0057, arXiv.org.
    12. Suo, Yuan-Yuan & Wang, Dong-Hua & Li, Sai-Ping, 2015. "Risk estimation of CSI 300 index spot and futures in China from a new perspective," Economic Modelling, Elsevier, vol. 49(C), pages 344-353.
    13. Kaizoji, Taisei, 2004. "Inflation and deflation in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 343(C), pages 662-668.

  27. Taisei Kaizoji, 2003. "Scaling behavior in land markets," Papers cond-mat/0302470, arXiv.org, revised Mar 2006.

    Cited by:

    1. Igor Fedotenkov, 2020. "A Review of More than One Hundred Pareto-Tail Index Estimators," Statistica, Department of Statistics, University of Bologna, vol. 80(3), pages 245-299.
    2. Blackwell, Calvin, 2018. "Power Laws in Real Estate Prices? Some Evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 90-98.
    3. Morales, Raffaello & Di Matteo, T. & Gramatica, Ruggero & Aste, Tomaso, 2012. "Dynamical generalized Hurst exponent as a tool to monitor unstable periods in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(11), pages 3180-3189.
    4. Raffaello Morales & T. Di Matteo & Ruggero Gramatica & Tomaso Aste, 2011. "Dynamical Hurst exponent as a tool to monitor unstable periods in financial time series," Papers 1109.0465, arXiv.org.
    5. Andersson, Claes & Hellervik, Alexander & Lindgren, Kristian, 2005. "A spatial network explanation for a hierarchy of urban power laws," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 345(1), pages 227-244.
    6. Ioannis P. Antoniades & Giuseppe Brandi & L. G. Magafas & T. Di Matteo, 2020. "The use of scaling properties to detect relevant changes in financial time series: a new visual warning tool," Papers 2010.08890, arXiv.org, revised Dec 2020.
    7. Claes Andersson & Koen Frenken & Alexander Hellervik, 2006. "A Complex Network Approach to Urban Growth," Environment and Planning A, , vol. 38(10), pages 1941-1964, October.
    8. D'Acci, Luca S., 2023. "Is housing price distribution across cities, scale invariant? Fractal distribution of settlements' house prices as signature of self-organized complexity," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    9. Antoniades, I.P. & Brandi, Giuseppe & Magafas, L. & Di Matteo, T., 2021. "The use of scaling properties to detect relevant changes in financial time series: A new visual warning tool," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).

  28. Taisei Kaizoji & Masahide Nuki, 2003. "Scaling Law for the Distribution of Fluctuations of Share Volume," Papers cond-mat/0302468, arXiv.org, revised Mar 2006.

    Cited by:

    1. Taisei Kaizoji, 2013. "Modeling of Stock Returns and Trading Volume," Papers 1309.2416, arXiv.org.

  29. Taisei Kaizoji, 2003. "Speculative bubbles and fat tail phenomena in a heterogeneous agent model," Papers nlin/0312040, arXiv.org.

    Cited by:

    1. Ahmad Naimzada & Giorgio Ricchiuti, 2007. "Dynamic Effects of Increasing Heterogeneity in Financial Markets," Working Papers 111, University of Milano-Bicocca, Department of Economics, revised 2007.
    2. Ahmad Naimzada & Giorgio Ricchiuti, 2006. "Heterogeneous Fundamentalists and Imitative Processes," Working Papers 104, University of Milano-Bicocca, Department of Economics, revised Nov 2006.
    3. Doris Neuberger & Roger Rissi, 2014. "Macroprudential Banking Regulation: Does One Size Fit All?," Journal of Banking and Financial Economics, University of Warsaw, Faculty of Management, vol. 1(1), pages 5-28, May.

  30. Yoshi Fujiwara & Wataru Souma & Hideaki Aoyama & Taisei Kaizoji & Masanao Aoki, 2002. "Growth and Fluctuations of Personal Income," Papers cond-mat/0208398, arXiv.org.

    Cited by:

    1. Carmen Comaniciu, 2015. "Some coordinates concerning taxation in the EU candidate countries," Annals of the University of Petrosani, Economics, University of Petrosani, Romania, vol. 15(1), pages 91-100.
    2. Thomas Lux, 2009. "Applications of Statistical Physics in Finance and Economics," Chapters, in: J. Barkley Rosser Jr. (ed.), Handbook of Research on Complexity, chapter 9, Edward Elgar Publishing.
    3. Costas Efthimiou & Adam Wearne, 2016. "Household Income Distribution in the USA," Papers 1602.06234, arXiv.org.
    4. Anirban Chakraborti & Ioane Muni Toke & Marco Patriarca & Frédéric Abergel, 2011. "Econophysics review: II. Agent-based models," Post-Print hal-00621059, HAL.
    5. Edgardo Bucciarelli & Marcello Silvestri, 2013. "Hyman P. Minsky's unorthodox approach: recent advances in simulation techniques to develop his theoretical assumptions," Journal of Post Keynesian Economics, Taylor & Francis Journals, vol. 36(2), pages 299-324.
    6. Darrell Jiajie Tay & Chung-I Chou & Sai-Ping Li & Shang You Tee & Siew Ann Cheong, 2016. "Bubbles Are Departures from Equilibrium Housing Markets: Evidence from Singapore and Taiwan," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-13, November.
    7. Alberto Russo, 2014. "A Stochastic Model of Wealth Accumulation with Class Division," Metroeconomica, Wiley Blackwell, vol. 65(1), pages 1-35, February.
    8. Kerim Eser Afc{s}ar & Mehmet Ozyi~git & Yusuf Yuksel & Umit Ak{i}nc{i}, 2021. "Testing the Goodwin Growth Cycles with Econophysics Approach in 2002-2019 Period in Turkey," Papers 2106.02546, arXiv.org.
    9. Néda, Zoltán & Gere, István & Biró, Tamás S. & Tóth, Géza & Derzsy, Noemi, 2020. "Scaling in income inequalities and its dynamical origin," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    10. Atushi Ishikawa & Shouji Fujimoto & Takayuki Mizuno, 2019. "Statistical law observed in inactive rate of firms," Evolutionary and Institutional Economics Review, Springer, vol. 16(1), pages 201-212, June.
    11. Muhammad Hilmi Abdul Majid & Kamarulzaman Ibrahim & Nurulkamal Masseran, 2023. "Three-Part Composite Pareto Modelling for Income Distribution in Malaysia," Mathematics, MDPI, vol. 11(13), pages 1-15, June.
    12. Atushi Ishikawa & Shouji Fujimoto & Takayuki Mizuno, 2021. "Why does production function take the Cobb–Douglas form?," Evolutionary and Institutional Economics Review, Springer, vol. 18(1), pages 79-102, April.
    13. Atushi Ishikawa & Shouji Fujimoto & Takayuki Mizuno & Tsutomu Watanabe, 2016. "Long-term firm growth properties derived from short-term laws of sales and number of employees in Japan and France," Evolutionary and Institutional Economics Review, Springer, vol. 13(2), pages 409-422, December.
    14. Atushi Ishikawa & Takayuki Mizuno & Shouji Fujimoto, 2022. "Employee Number Dependence in Labor Productivity Distribution," The Review of Socionetwork Strategies, Springer, vol. 16(2), pages 465-477, October.
    15. Shouji Fujimoto & Atushi Ishikawa & Takayuki Mizuno, 2022. "Copula-Based Synthetic Data Generation in Firm-Size Variables," The Review of Socionetwork Strategies, Springer, vol. 16(2), pages 479-492, October.
    16. Tomson Ogwang, 2011. "Power laws in top wealth distributions: evidence from Canada," Empirical Economics, Springer, vol. 41(2), pages 473-486, October.
    17. Ogwang, Tomson, 2013. "Is the wealth of the world’s billionaires Paretian?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 757-762.
    18. Cui, Jian & Pan, Qiuhui & Qian, Qian & He, Mingfeng & Sun, Qilin, 2013. "A multi-agent dynamic model based on different kinds of bequests," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1393-1397.
    19. Victor M. Yakovenko, 2012. "Applications of statistical mechanics to economics: Entropic origin of the probability distributions of money, income, and energy consumption," Papers 1204.6483, arXiv.org.
    20. Giulio Bottazzi, 2007. "On the Irreconcilability of Pareto and Gibrat Laws," LEM Papers Series 2007/10, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    21. Atushi Ishikawa & Shouji Fujimoto & Takayuki Mizuno & Tsutomu Watanabe, 2017. "Dependence of the decay rate of firm activities on firm age," Evolutionary and Institutional Economics Review, Springer, vol. 14(2), pages 351-362, December.
    22. Marco Patriarca & Anirban Chakraborti & Guido Germano, 2005. "Influence of saving propensity on the power law tail of wealth distribution," Papers physics/0506028, arXiv.org.
    23. Boris M. Dolgonosov, 2018. "A Conceptual Model of the Relationship Among World Economy and Climate Indicators," Biophysical Economics and Resource Quality, Springer, vol. 3(1), pages 1-15, March.
    24. Xu, Yan & Wang, Yougui & Tao, Xiaobo & Ližbetinová, Lenka, 2017. "Evidence of Chinese income dynamics and its effects on income scaling law," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 487(C), pages 143-152.
    25. Troy Tassier, 2013. "Handbook of Research on Complexity, by J. Barkley Rosser, Jr. and Edward Elgar," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 39(1), pages 132-133.
    26. Chakrabarti, Anindya S. & Chakrabarti, Bikas K., 2010. "Statistical theories of income and wealth distribution," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 4, pages 1-31.
    27. Ma, Tao & Holden, John G. & Serota, R.A., 2013. "Distribution of wealth in a network model of the economy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(10), pages 2434-2441.
    28. Aoyama, Hideaki & Fujiwara, Yoshi & Souma, Wataru, 2004. "Kinematics and dynamics of Pareto–Zipf's law and Gibrat's law," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 117-121.
    29. Shuhei Aoki & Makoto Nirei, 2016. "Pareto Distribution of Income in Neoclassical Growth Models," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 20, pages 25-42, April.
    30. Hosseiny, Ali, 2017. "A geometrical imaging of the real gap between economies of China and the United States," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 151-161.
    31. Soriano-Hernández, P. & del Castillo-Mussot, M. & Campirán-Chávez, I. & Montemayor-Aldrete, J.A., 2017. "Wealth of the world’s richest publicly traded companies per industry and per employee: Gamma, Log-normal and Pareto power-law as universal distributions?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 733-749.
    32. Lux, Thomas, 2008. "Applications of statistical physics in finance and economics," Kiel Working Papers 1425, Kiel Institute for the World Economy (IfW Kiel).
    33. Atushi Ishikawa & Shouji Fujimoto & Takayuki Mizuno, 2024. "Statistical laws observed in earthquakes using mesh statistics: an econophysical point of view," Evolutionary and Institutional Economics Review, Springer, vol. 21(2), pages 203-216, September.
    34. Victor M. Yakovenko & J. Barkley Rosser, 2009. "Colloquium: Statistical mechanics of money, wealth, and income," Papers 0905.1518, arXiv.org, revised Dec 2009.
    35. Anand Banerjee & Victor M. Yakovenko, 2009. "Universal patterns of inequality," Papers 0912.4898, arXiv.org, revised Apr 2010.
    36. Safari, Muhammad Aslam Mohd & Masseran, Nurulkamal & Ibrahim, Kamarulzaman & Hussain, Saiful Izzuan, 2021. "Measuring income inequality: A robust semi-parametric approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 562(C).
    37. Zoltan Neda & Istvan Gere & Tamas S. Biro & Geza Toth & Noemi Derzsy, 2019. "Scaling in Income Inequalities and its Dynamical Origin," Papers 1911.02449, arXiv.org, revised Mar 2020.
    38. Sitabhra Sinha, 2005. "The Rich Are Different!: Pareto Law from asymmetric interactions in asset exchange models," Papers physics/0504197, arXiv.org.
    39. Guo, Qiang & Gao, Li, 2012. "Distribution of individual incomes in China between 1992 and 2009," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(21), pages 5139-5145.
    40. Antonio Doria, Francisco, 2011. "J.B. Rosser Jr. , Handbook of Research on Complexity, Edward Elgar, Cheltenham, UK--Northampton, MA, USA (2009) 436 + viii pp., index, ISBN 978 1 84542 089 5 (cased)," Journal of Economic Behavior & Organization, Elsevier, vol. 78(1-2), pages 196-204, April.

  31. Taisei Kaizoji & Stefan Bornholdt & Yoshi Fujiwara, 2002. "Dynamics of price and trading volume in a spin model of stock markets with heterogeneous agents," Papers cond-mat/0207253, arXiv.org.

    Cited by:

    1. Kristoufek, Ladislav & Vošvrda, Miloslav S., 2016. "Herding, minority game, market clearing and efficient markets in a simple spin model framework," FinMaP-Working Papers 68, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    2. Quanbo Zha & Gang Kou & Hengjie Zhang & Haiming Liang & Xia Chen & Cong-Cong Li & Yucheng Dong, 2020. "Opinion dynamics in finance and business: a literature review and research opportunities," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-22, December.
    3. Simon Cramer & Torsten Trimborn, 2019. "Stylized Facts and Agent-Based Modeling," Papers 1912.02684, arXiv.org.
    4. Cross, Rod & Grinfeld, Michael & Lamba, Harbir & Seaman, Tim, 2005. "A threshold model of investor psychology," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 354(C), pages 463-478.
    5. Shi, Leilei, 2006. "Does security transaction volume–price behavior resemble a probability wave?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 366(C), pages 419-436.
    6. Wagner, D.C. & Schmitt, T.A. & Schäfer, R. & Guhr, T. & Wolf, D.E., 2014. "Analysis of a decision model in the context of equilibrium pricing and order book pricing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 347-353.
    7. Daniel C. Wagner & Thilo A. Schmitt & Rudi Schafer & Thomas Guhr & Dietrich E. Wolf, 2014. "Analysis of a decision model in the context of equilibrium pricing and order book pricing," Papers 1404.7356, arXiv.org.
    8. Jørgen Vitting Andersen & Ioannis Vrontos & Petros Dellaportas & Serge Galam, 2014. "Communication impacting financial markets," Documents de travail du Centre d'Economie de la Sorbonne 14029, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    9. IKEDA Yuichi & YOSHIKAWA Hiroshi, 2018. "Macroprudential Modeling Based on Spin Dynamics in a Supply Chain Network," Discussion papers 18045, Research Institute of Economy, Trade and Industry (RIETI).
    10. Stefan Bornholdt, 2021. "A q-spin Potts model of markets: Gain-loss asymmetry in stock indices as an emergent phenomenon," Papers 2112.06290, arXiv.org.
    11. Yue Chen & Xiaojian Niu & Yan Zhang, 2019. "Exploring Contrarian Degree in the Trading Behavior of China's Stock Market," Complexity, Hindawi, vol. 2019, pages 1-12, April.
    12. Kei Katahira & Yu Chen & Gaku Hashimoto & Hiroshi Okuda, 2019. "Development of an agent-based speculation game for higher reproducibility of financial stylized facts," Papers 1902.02040, arXiv.org.
    13. Yuichi Ikeda, 2020. "An Interacting Agent Model of Economic Crisis," Papers 2001.11843, arXiv.org.
    14. Katahira, Kei & Chen, Yu & Hashimoto, Gaku & Okuda, Hiroshi, 2019. "Development of an agent-based speculation game for higher reproducibility of financial stylized facts," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 503-518.
    15. Theodosopoulos, Ted & Yuen, Ming, 2007. "Properties of the wealth process in a market microstructure model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 378(2), pages 443-452.
    16. Tetsuya Takaishi, 2014. "Analysis of Spin Financial Market by GARCH Model," Papers 1409.0118, arXiv.org.
    17. Marco Airoldi & Vito Antonelli & Bruno Bassetti & Andrea Martinelli & Marco Picariello, 2004. "Long Range Interaction Generating Fat-Tails in Finance," GE, Growth, Math methods 0404006, University Library of Munich, Germany, revised 27 Apr 2004.
    18. Didier Sornette & Wei-Xing Zhou, 2005. "Importance of Positive Feedbacks and Over-confidence in a Self-Fulfilling Ising Model of Financial Markets," Papers cond-mat/0503607, arXiv.org, revised Mar 2005.
    19. Veglio, A. & Marsili, M., 2007. "Stochastic analysis of an agent-based model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 385(2), pages 631-636.
    20. Taisei Kaizoji, 2013. "Modeling of Stock Returns and Trading Volume," Papers 1309.2416, arXiv.org.
    21. Didier SORNETTE, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based Models," Swiss Finance Institute Research Paper Series 14-25, Swiss Finance Institute.
    22. Maximilian Beikirch & Simon Cramer & Martin Frank & Philipp Otte & Emma Pabich & Torsten Trimborn, 2020. "Robust Mathematical Formulation And Probabilistic Description Of Agent-Based Computational Economic Market Models," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 23(06), pages 1-41, September.
    23. 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).
    24. Torsten Trimborn & Philipp Otte & Simon Cramer & Maximilian Beikirch & Emma Pabich & Martin Frank, 2020. "SABCEMM: A Simulator for Agent-Based Computational Economic Market Models," Computational Economics, Springer;Society for Computational Economics, vol. 55(2), pages 707-744, February.
    25. Maximilian Beikirch & Simon Cramer & Martin Frank & Philipp Otte & Emma Pabich & Torsten Trimborn, 2019. "Robust Mathematical Formulation and Probabilistic Description of Agent-Based Computational Economic Market Models," Papers 1904.04951, arXiv.org, revised Mar 2021.
    26. Kukacka, Jiri & Barunik, Jozef, 2013. "Behavioural breaks in the heterogeneous agent model: The impact of herding, overconfidence, and market sentiment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 5920-5938.
    27. Tetsuya Takaishi, 2008. "Financial Time Series Analysis of SV Model by Hybrid Monte Carlo," Papers 0807.4394, arXiv.org.
    28. Ted Theodosopoulos & Ming Yuen, 2005. "Properties of the wealth process in a market microstructure model," Papers math/0502105, arXiv.org, revised Feb 2005.
    29. Torsten Trimborn & Philipp Otte & Simon Cramer & Max Beikirch & Emma Pabich & Martin Frank, 2018. "SABCEMM-A Simulator for Agent-Based Computational Economic Market Models," Papers 1801.01811, arXiv.org, revised Oct 2018.
    30. Ted Theodosopoulos & Ming Yuen, 2006. "Imbalance attractors for a strategic model of market microstructure," Papers math/0605421, arXiv.org.
    31. Tetsuya Takaishi, 2016. "Dynamical cross-correlation of multiple time series Ising model," Evolutionary and Institutional Economics Review, Springer, vol. 13(2), pages 455-468, December.
    32. Ted Theodosopoulos, 2004. "Uncertainty relations in models of market microstructure," Papers math/0409076, arXiv.org, revised Feb 2005.
    33. D. Sornette, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based models," Papers 1404.0243, arXiv.org.
    34. Kyrylo Shmatov & Mikhail Smirnov, 2005. "On Some Processes and Distributions in a Collective Model of Investors' Behavior," Papers nlin/0506015, arXiv.org.
    35. Taisei Kaizoji, 2013. "Modelling of Stock Returns and Trading Volume," IIM Kozhikode Society & Management Review, , vol. 2(2), pages 147-155, July.
    36. 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.
    37. Marcin Wk{a}torek & Jaros{l}aw Kwapie'n & Stanis{l}aw Dro.zd.z, 2021. "Financial Return Distributions: Past, Present, and COVID-19," Papers 2107.06659, arXiv.org.
    38. Horvath, Philip A. & Roos, Kelly R. & Sinha, Amit, 2016. "An Ising spin state explanation for financial asset allocation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 445(C), pages 112-116.
    39. Samar K. Guharay & Gaurav S. Thakur & Fred J. Goodman & Scott L. Rosen & Daniel Houser, 2016. "Integrated data-driven analytics to identify instability signatures in nonstationary financial time series," Applied Economics, Taylor & Francis Journals, vol. 48(18), pages 1678-1694, April.
    40. Theodosopoulos, Ted, 2005. "Uncertainty relations in models of market microstructure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(1), pages 209-216.
    41. 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.
    42. Lux, Thomas & Alfarano, Simone, 2016. "Financial power laws: Empirical evidence, models, and mechanisms," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 3-18.
    43. Kei Katahira & Yu Chen, 2019. "Heterogeneous wealth distribution, round-trip trading and the emergence of volatility clustering in Speculation Game," Papers 1909.03185, arXiv.org.
    44. Bornholdt, Stefan, 2022. "A q-spin Potts model of markets: Gain–loss asymmetry in stock indices as an emergent phenomenon," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).
    45. Meudt, Frederik & Schmitt, Thilo A. & Schäfer, Rudi & Guhr, Thomas, 2016. "Equilibrium pricing in an order book environment: Case study for a spin model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 453(C), pages 228-235.
    46. Bargigli, Leonardo & Tedeschi, Gabriele, 2014. "Interaction in agent-based economics: A survey on the network approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 399(C), pages 1-15.
    47. 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.
    48. Zubillaga, Bernardo J. & Vilela, André L.M. & Wang, Chao & Nelson, Kenric P. & Stanley, H. Eugene, 2022. "A three-state opinion formation model for financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).
    49. Tetsuya Takaishi, 2009. "An Adaptive Markov Chain Monte Carlo Method for GARCH Model," Papers 0901.0992, arXiv.org.
    50. Lan, Yun & Fang, Wen, 2024. "Mechanisms of investors’ bounded rationality and market herding effect by the stochastic Ising financial model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 648(C).
    51. Frederik Meudt & Thilo A. Schmitt & Rudi Schafer & Thomas Guhr, 2015. "Equilibrium Pricing in an Order Book Environment: Case Study for a Spin Model," Papers 1502.01125, arXiv.org.
    52. Theodosopoulos, Ted & Boyer, Robert, 2007. "Periodic attractors of random truncator maps," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 302-310.

  32. Taisei Kaizoji, 2000. "Speculative bubbles and crashes in stock market: an interacting-agent model of speculative activity," Papers cond-mat/0010263, arXiv.org.

    Cited by:

    1. Maria Boguta & Eric Jarpe, 2010. "A new space-time model for volatility clustering in the financial market," Papers 1002.0609, arXiv.org.
    2. Kristoufek, Ladislav & Vošvrda, Miloslav S., 2016. "Herding, minority game, market clearing and efficient markets in a simple spin model framework," FinMaP-Working Papers 68, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    3. Quanbo Zha & Gang Kou & Hengjie Zhang & Haiming Liang & Xia Chen & Cong-Cong Li & Yucheng Dong, 2020. "Opinion dynamics in finance and business: a literature review and research opportunities," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-22, December.
    4. Cross, Rod & Grinfeld, Michael & Lamba, Harbir & Seaman, Tim, 2005. "A threshold model of investor psychology," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 354(C), pages 463-478.
    5. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2001. "Microscopic Models of Financial Markets," Papers cond-mat/0110354, arXiv.org.
    6. Sato, Aki-Hiro, 2007. "Frequency analysis of tick quotes on the foreign exchange market and agent-based modeling: A spectral distance approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 258-270.
    7. Gao-Feng Gu & Wei Chen & Wei-Xing Zhou, 2007. "Empirical regularities of order placement in the Chinese stock market," Papers 0712.0912, arXiv.org.
    8. IKEDA Yuichi & YOSHIKAWA Hiroshi, 2018. "Macroprudential Modeling Based on Spin Dynamics in a Supply Chain Network," Discussion papers 18045, Research Institute of Economy, Trade and Industry (RIETI).
    9. Yuichi Ikeda, 2020. "An Interacting Agent Model of Economic Crisis," Papers 2001.11843, arXiv.org.
    10. Wang, Guochao & Zheng, Shenzhou & Wang, Jun, 2019. "Complex and composite entropy fluctuation behaviors of statistical physics interacting financial model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 97-113.
    11. Kaizoji, Taisei & Leiss, Matthias & Saichev, Alexander & Sornette, Didier, 2015. "Super-exponential endogenous bubbles in an equilibrium model of fundamentalist and chartist traders," Journal of Economic Behavior & Organization, Elsevier, vol. 112(C), pages 289-310.
    12. Ditian Zhang & Yangyang Zhuang & Pan Tang & Hongjuan Peng & Qingying Han, 2023. "Financial price dynamics and phase transitions in the stock markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 96(3), pages 1-21, March.
    13. Christopher D. Clack & Elias Court & Dmitrijs Zaparanuks, 2020. "Dynamic Coupling and Market Instability," Papers 2005.13621, arXiv.org.
    14. Ilaria Foroni & Anna Agliari, 2008. "Complex Price Dynamics in a Financial Market with Imitation," Computational Economics, Springer;Society for Computational Economics, vol. 32(1), pages 21-36, September.
    15. Kaizoji, Taisei (kaizoji@icu.ac.jp), 2010. "A behavioral model of bubbles and crashes," MPRA Paper 35655, University Library of Munich, Germany.
    16. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2007. "Agent-based Models of Financial Markets," Papers physics/0701140, arXiv.org.
    17. Taisei Kaizoji, 2013. "Modeling of Stock Returns and Trading Volume," Papers 1309.2416, arXiv.org.
    18. Didier SORNETTE, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based Models," Swiss Finance Institute Research Paper Series 14-25, Swiss Finance Institute.
    19. Stefan-Cosmin DANILA & Ioan-Bogdan ROBU, 2019. "The Influence of Cryptocurrency Bitcoin over the Romanian Capital Market," The Audit Financiar journal, Chamber of Financial Auditors of Romania, vol. 17(155), pages 507-507.
    20. Agnieszka Kuś & Agnieszka Kuś, 2023. "Photovoltaic Companies on the Warsaw Stock Exchange—Another Speculative Bubble or a Sign of the Times?," Energies, MDPI, vol. 16(2), pages 1-21, January.
    21. Torsten Trimborn & Philipp Otte & Simon Cramer & Maximilian Beikirch & Emma Pabich & Martin Frank, 2020. "SABCEMM: A Simulator for Agent-Based Computational Economic Market Models," Computational Economics, Springer;Society for Computational Economics, vol. 55(2), pages 707-744, February.
    22. Gallegati, Mauro & Palestrini, Antonio & Rosser, J. Barkley, 2011. "The Period Of Financial Distress In Speculative Markets: Interacting Heterogeneous Agents And Financial Constraints," Macroeconomic Dynamics, Cambridge University Press, vol. 15(1), pages 60-79, February.
    23. Schütz, Gunter M. & de Almeida Prado, Fernando Pigeard & Harris, Rosemary J. & Belitsky, Vladimir, 2009. "Short-time behaviour of demand and price viewed through an exactly solvable model for heterogeneous interacting market agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(19), pages 4126-4144.
    24. Christoph J. Borner & Ingo Hoffmann & John H. Stiebel, 2023. "On the Connection between Temperature and Volatility in Ideal Agent Systems," Papers 2303.15164, arXiv.org.
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Articles

  1. Eom, Cheoljun & Kaizoji, Taisei & Kang, Sang Hoon & Pichl, Lukas, 2019. "Bitcoin and investor sentiment: Statistical characteristics and predictability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 511-521.

    Cited by:

    1. Haffar, Adlane & Le Fur, Éric, 2022. "Time-varying dependence of Bitcoin," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 211-220.
    2. ?ikolaos A. Kyriazis, 2021. "Impacts of Stock Indices, Oil, and Twitter Sentiment on Major Cryptocurrencies during the COVID-19 First Wave," Bulletin of Applied Economics, Risk Market Journals, vol. 8(2), pages 133-146.
    3. Martina Halouskov'a & Daniel Stav{s}ek & Mat'uv{s} Horv'ath, 2022. "The role of investor attention in global asset price variation during the invasion of Ukraine," Papers 2205.05985, arXiv.org, revised Aug 2022.
    4. Apostolakis, George N., 2024. "Bitcoin price volatility transmission between spot and futures markets," International Review of Financial Analysis, Elsevier, vol. 94(C).
    5. Chi-Ming Ho, 2023. "Research on interaction of innovation spillovers in the AI, Fin-Tech, and IoT industries: considering structural changes accelerated by COVID-19," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-29, December.
    6. Giacomo di Tollo & Joseph Andria & Gianni Filograsso, 2023. "The Predictive Power of Social Media Sentiment: Evidence from Cryptocurrencies and Stock Markets Using NLP and Stochastic ANNs," Mathematics, MDPI, vol. 11(16), pages 1-18, August.
    7. Figà-Talamanca, Gianna & Focardi, Sergio & Patacca, Marco, 2021. "Regime switches and commonalities of the cryptocurrencies asset class," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    8. Yongqiang Meng & Dehua Shen & Xiong Xiong & Jorgen Vitting Andersen, 2020. "A Socio-Finance Model: The Case of Bitcoin," Documents de travail du Centre d'Economie de la Sorbonne 20031, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    9. Bourghelle, David & Jawadi, Fredj & Rozin, Philippe, 2022. "Do collective emotions drive bitcoin volatility? A triple regime-switching vector approach," Journal of Economic Behavior & Organization, Elsevier, vol. 196(C), pages 294-306.
    10. Xun Zhang & Fengbin Lu & Rui Tao & Shouyang Wang, 2021. "The time-varying causal relationship between the Bitcoin market and internet attention," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-19, December.
    11. Dunbar, Kwamie & Owusu-Amoako, Johnson, 2022. "Cryptocurrency returns under empirical asset pricing," International Review of Financial Analysis, Elsevier, vol. 82(C).
    12. Michael Demmler & Amilcar Orlian Fernández Domínguez, 2021. "Bitcoin and the South Sea Company: A comparative analysis," Revista Finanzas y Politica Economica, Universidad Católica de Colombia, vol. 13(1), pages 197-224, March.
    13. Zhao, Ruwei, 2020. "Quantifying the cross sectional relation of daily happiness sentiment and stock return: Evidence from US," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 538(C).
    14. Duy Duong & Toan Luu Duc Huynh, 2020. "Tail dependence in emerging ASEAN-6 equity markets: empirical evidence from quantitative approaches," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-26, December.
    15. Ahmed, Walid M.A. & Al Mafrachi, Mustafa, 2021. "Do higher-order realized moments matter for cryptocurrency returns?," International Review of Economics & Finance, Elsevier, vol. 72(C), pages 483-499.
    16. Hajek, Petr & Hikkerova, Lubica & Sahut, Jean-Michel, 2023. "How well do investor sentiment and ensemble learning predict Bitcoin prices?," Research in International Business and Finance, Elsevier, vol. 64(C).
    17. Adel Benhamed & Ahlem Selma Messai & Ghassen El Montasser, 2023. "On the Determinants of Bitcoin Returns and Volatility: What We Get from Gets?," Sustainability, MDPI, vol. 15(3), pages 1-21, January.
    18. Mokni, Khaled, 2021. "When, where, and how economic policy uncertainty predicts Bitcoin returns and volatility? A quantiles-based analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 65-73.
    19. A. V. Biju & Aparna Merin Mathew & P. P. Nithi Krishna & M. P. Akhil, 2022. "Is the future of bitcoin safe? A triangulation approach in the reality of BTC market through a sentiments analysis," Digital Finance, Springer, vol. 4(4), pages 275-290, December.
    20. Ahmed, Walid M.A., 2022. "Robust drivers of Bitcoin price movements: An extreme bounds analysis," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    21. Alessandra Cretarola & Gianna Figà-Talamanca, 2021. "Detecting bubbles in Bitcoin price dynamics via market exuberance," Annals of Operations Research, Springer, vol. 299(1), pages 459-479, April.
    22. Osman, Myriam Ben & Urom, Christian & Guesmi, Khaled & Benkraiem, Ramzi, 2024. "Economic sentiment and the cryptocurrency market in the post-COVID-19 era," International Review of Financial Analysis, Elsevier, vol. 91(C).
    23. Garcia-Jorcano, Laura & Benito, Sonia, 2020. "Studying the properties of the Bitcoin as a diversifying and hedging asset through a copula analysis: Constant and time-varying," Research in International Business and Finance, Elsevier, vol. 54(C).
    24. Fasanya, Ismail O. & Oyewole, Oluwatomisin J. & Oliyide, Johnson A., 2022. "Investors' sentiments and the dynamic connectedness between cryptocurrency and precious metals markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 347-364.
    25. Alessandra Cretarola & Gianna Figà-Talamanca & Cyril Grunspan, 2021. "Blockchain and cryptocurrencies: economic and financial research," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 781-787, December.
    26. Halousková, Martina & Stašek, Daniel & Horváth, Matúš, 2022. "The role of investor attention in global asset price variation during the invasion of Ukraine," Finance Research Letters, Elsevier, vol. 50(C).
    27. Gianna Figá-Talamanca & Sergio Focardi & Marco Patacca, 2021. "Common dynamic factors for cryptocurrencies and multiple pair-trading statistical arbitrages," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 863-882, December.
    28. Mokni, Khaled & Bouteska, Ahmed & Nakhli, Mohamed Sahbi, 2022. "Investor sentiment and Bitcoin relationship: A quantile-based analysis," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    29. Zeng, Sheng & Liu, Xinchun & Li, Xiafei & Wei, Qi & Shang, Yue, 2019. "Information dominance among hedging assets: Evidence from return and volatility directional spillovers in time and frequency domains," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    30. Shen, Na & Chen, Jiayi, 2023. "Asymmetric multifractal spectrum distribution based on detrending moving average cross-correlation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    31. Hashem A. AlNemer & Besma Hkiri & Muhammed Asif Khan, 2021. "Time-Varying Nexus between Investor Sentiment and Cryptocurrency Market: New Insights from a Wavelet Coherence Framework," JRFM, MDPI, vol. 14(6), pages 1-19, June.
    32. David L. John & Sebastian Binnewies & Bela Stantic, 2024. "Cryptocurrency Price Prediction Algorithms: A Survey and Future Directions," Forecasting, MDPI, vol. 6(3), pages 1-35, August.
    33. Piccoli, Pedro & de Castro, Jessica, 2021. "Attention-return relation in the gold market and market states," Resources Policy, Elsevier, vol. 74(C).
    34. Naeem, Muhammad Abubakr & Mbarki, Imen & Shahzad, Syed Jawad Hussain, 2021. "Predictive role of online investor sentiment for cryptocurrency market: Evidence from happiness and fears," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 496-514.
    35. López-Martín, Carmen & Arguedas-Sanz, Raquel & Muela, Sonia Benito, 2022. "A cryptocurrency empirical study focused on evaluating their distribution functions," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 387-407.
    36. Park, Sangjin & Jang, Kwahngsoo & Yang, Jae-Suk, 2021. "Information flow between bitcoin and other financial assets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    37. Duc Huynh, Toan Luu & Burggraf, Tobias & Wang, Mei, 2020. "Gold, platinum, and expected Bitcoin returns," Journal of Multinational Financial Management, Elsevier, vol. 56(C).
    38. Gaies, Brahim & Nakhli, Mohamed Sahbi & Sahut, Jean Michel & Guesmi, Khaled, 2021. "Is Bitcoin rooted in confidence? – Unraveling the determinants of globalized digital currencies," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    39. Ştefan Cristian Gherghina & Liliana Nicoleta Simionescu, 2023. "Exploring the asymmetric effect of COVID-19 pandemic news on the cryptocurrency market: evidence from nonlinear autoregressive distributed lag approach and frequency domain causality," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-58, December.

  2. Taisei Kaizoji & Michiko Miyano, 2019. "Stock market crash of 2008: an empirical study of the deviation of share prices from company fundamentals," Applied Economics Letters, Taylor & Francis Journals, vol. 26(5), pages 362-369, March.

    Cited by:

    1. Wu, Xu & Wang, Pei-Yu & Wang, Kun, 2023. "The effect of stabilization fund to rescue stock market based on expected return-capita circulation equation," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).

  3. Nan, Zheng & Kaizoji, Taisei, 2019. "Market efficiency of the bitcoin exchange rate: Weak and semi-strong form tests with the spot, futures and forward foreign exchange rates," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 273-281.

    Cited by:

    1. Naeem, Muhammad Abubakr & Bouri, Elie & Peng, Zhe & Shahzad, Syed Jawad Hussain & Vo, Xuan Vinh, 2021. "Asymmetric efficiency of cryptocurrencies during COVID19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    2. Huang, Guan-Ying & Gau, Yin-Feng & Wu, Zhen-Xing, 2022. "Price discovery in fiat currency and cryptocurrency markets," Finance Research Letters, Elsevier, vol. 47(PA).
    3. Qiao, Xingzhi & Zhu, Huiming & Hau, Liya, 2020. "Time-frequency co-movement of cryptocurrency return and volatility: Evidence from wavelet coherence analysis," International Review of Financial Analysis, Elsevier, vol. 71(C).
    4. Li, Zhenghui & Mo, Bin & Nie, He, 2023. "Time and frequency dynamic connectedness between cryptocurrencies and financial assets in China," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 46-57.
    5. Vasilios Plakandaras & Elie Bouri & Rangan Gupta, 2019. "Forecasting Bitcoin Returns: Is there a Role for the U.S. – China Trade War?," Working Papers 201980, University of Pretoria, Department of Economics.
    6. Tran, Vu Le & Leirvik, Thomas, 2020. "Efficiency in the markets of crypto-currencies," Finance Research Letters, Elsevier, vol. 35(C).
    7. F. N. M. de Sousa Filho & J. N. Silva & M. A. Bertella & E. Brigatti, 2020. "The leverage effect and other stylized facts displayed by Bitcoin returns," Papers 2004.05870, arXiv.org, revised Jan 2021.
    8. Felföldi-Szűcs, Nóra & Králik, Balázs & Váradi, Kata, 2024. "Put–call parity in a crypto option market — Evidence from Binance," Finance Research Letters, Elsevier, vol. 61(C).
    9. Mehmet Balcilar & Huseyin Ozdemir, 2023. "On the Risk Spillover from Bitcoin to Altcoins: The Fear of Missing Out and Pump-and-Dump Scheme Effects," JRFM, MDPI, vol. 16(1), pages 1-15, January.
    10. Aslam, Faheem & Memon, Bilal Ahmed & Hunjra, Ahmed Imran & Bouri, Elie, 2023. "The dynamics of market efficiency of major cryptocurrencies," Global Finance Journal, Elsevier, vol. 58(C).
    11. Ángeles Cebrián-Hernández & Enrique Jiménez-Rodríguez, 2021. "Modeling of the Bitcoin Volatility through Key Financial Environment Variables: An Application of Conditional Correlation MGARCH Models," Mathematics, MDPI, vol. 9(3), pages 1-16, January.
    12. Cheng, Jiameng & Dai, Yanke, 2020. "Is bitcoin a channel of capital inflow? Evidence from carry trade activity," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 261-278.
    13. Takeshi Yoshihara & Taisei Kaizoji, 2022. "Mechanism of information transmission from a spot rate market to crypto-asset markets," Papers 2211.16176, arXiv.org.

  4. Yuki Hirano & Lukáš Pichl & Cheoljun Eom & Taisei Kaizoji, 2018. "Analysis Of Bitcoin Market Efficiency By Using Machine Learning," CBU International Conference Proceedings, ISE Research Institute, vol. 6(0), pages 175-180, September.

    Cited by:

    1. Saggese, Pietro & Belmonte, Alessandro & Dimitri, Nicola & Facchini, Angelo & Böhme, Rainer, 2023. "Arbitrageurs in the Bitcoin ecosystem: Evidence from user-level trading patterns in the Mt. Gox exchange platform," Journal of Economic Behavior & Organization, Elsevier, vol. 213(C), pages 251-270.
    2. Park, Sangjin & Jang, Kwahngsoo & Yang, Jae-Suk, 2021. "Information flow between bitcoin and other financial assets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).

  5. Osamu Kodama & Lukáš Pichl & Taisei Kaizoji, 2017. "Regime Change And Trend Prediction For Bitcoin Time Series Data," CBU International Conference Proceedings, ISE Research Institute, vol. 5(0), pages 384-388, September.

    Cited by:

    1. Dag, Ali & Dag, Asli Z. & Asilkalkan, Abdullah & Simsek, Serhat & Delen, Dursun, 2023. "A Tree Augmented Naïve Bayes-based methodology for classifying cryptocurrency trends," Journal of Business Research, Elsevier, vol. 156(C).

  6. Kaizoji, Taisei & Leiss, Matthias & Saichev, Alexander & Sornette, Didier, 2015. "Super-exponential endogenous bubbles in an equilibrium model of fundamentalist and chartist traders," Journal of Economic Behavior & Organization, Elsevier, vol. 112(C), pages 289-310.
    See citations under working paper version above.
  7. Yang, Jae-Suk & Kaizoji, Taisei & Kwak, Wooseop, 2011. "Temporal evolution into a more efficient stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(11), pages 2002-2008.

    Cited by:

    1. Kantar, Ersin & Keskin, Mustafa, 2013. "The relationships between electricity consumption and GDP in Asian countries, using hierarchical structure methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(22), pages 5678-5684.
    2. Oh, Gabjin & Kim, Ho-yong & Ahn, Seok-Won & Kwak, Wooseop, 2015. "Analyzing the financial crisis using the entropy density function," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 464-469.

  8. Kaizoji, Taisei, 2010. "Multiple equilibria and chaos in a discrete tâtonnement process," Journal of Economic Behavior & Organization, Elsevier, vol. 76(3), pages 597-599, December.
    See citations under working paper version above.
  9. Eom, Cheoljun & Jung, Woo-Sung & Kaizoji, Taisei & Kim, Seunghwan, 2009. "Effect of changing data size on eigenvalues in the Korean and Japanese stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(22), pages 4780-4786.
    See citations under working paper version above.
  10. Jung, Woo-Sung & Kwon, Okyu & Wang, Fengzhong & Kaizoji, Taisei & Moon, Hie-Tae & Stanley, H. Eugene, 2008. "Group dynamics of the Japanese market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(2), pages 537-542.
    See citations under working paper version above.
  11. W.-S. Jung & F. Z. Wang & S. Havlin & T. Kaizoji & H.-T. Moon & H. E. Stanley, 2008. "Volatility return intervals analysis of the Japanese market," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 62(1), pages 113-119, March.
    See citations under working paper version above.
  12. Yamano, Takuya & Sato, Kodai & Kaizoji, Taisei & Rost, Jan-Michael & Pichl, Lukás, 2008. "Symbolic analysis of indicator time series by quantitative sequence alignment," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 486-495, December.

    Cited by:

    1. Laih, Yih-Wenn, 2014. "Measuring rank correlation coefficients between financial time series: A GARCH-copula based sequence alignment algorithm," European Journal of Operational Research, Elsevier, vol. 232(2), pages 375-382.

  13. Jae-Suk Yang & Wooseop Kwak & Taisei Kaizoji & In-mook Kim, 2008. "Increasing market efficiency in the stock markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 61(3), pages 389-389, February.

    Cited by:

    1. Campos Dias de Sousa, Ricardo Emanuel & Howden, David, 2015. "The Efficient Market Conjecture," MPRA Paper 79792, University Library of Munich, Germany.
    2. Xu, Meng & Shang, Pengjian, 2018. "Analysis of financial time series using multiscale entropy based on skewness and kurtosis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1543-1550.
    3. Taisei Kaizoji, 2010. "Stock volatility in the periods of booms and stagnations," EERI Research Paper Series EERI_RP_2010_07, Economics and Econometrics Research Institute (EERI), Brussels.
    4. Kantar, Ersin & Keskin, Mustafa, 2013. "The relationships between electricity consumption and GDP in Asian countries, using hierarchical structure methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(22), pages 5678-5684.
    5. Oh, Gabjin & Kim, Ho-yong & Ahn, Seok-Won & Kwak, Wooseop, 2015. "Analyzing the financial crisis using the entropy density function," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 464-469.
    6. Minsung Kim & Minki Kim, 2014. "Group-Wise Herding Behavior in Financial Markets: An Agent-Based Modeling Approach," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-7, April.
    7. Park, Sangjin & Jang, Kwahngsoo & Yang, Jae-Suk, 2021. "Information flow between bitcoin and other financial assets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    8. Preuss, Björn, 2019. "Equity fund managements promise and action: A comparative study of Nordic and US fund’s," Journal of Behavioral and Experimental Finance, Elsevier, vol. 23(C), pages 84-89.

  14. Hayashi, Katsuhiko & Kaizoji, Taisei & Pichl, Lukáš, 2007. "Correlation patterns of NIKKEI index constituents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 383(1), pages 16-21.

    Cited by:

    1. Laih, Yih-Wenn, 2014. "Measuring rank correlation coefficients between financial time series: A GARCH-copula based sequence alignment algorithm," European Journal of Operational Research, Elsevier, vol. 232(2), pages 375-382.

  15. Lux, Thomas & Kaizoji, Taisei, 2007. "Forecasting volatility and volume in the Tokyo Stock Market: Long memory, fractality and regime switching," Journal of Economic Dynamics and Control, Elsevier, vol. 31(6), pages 1808-1843, June.
    See citations under working paper version above.
  16. Onozaki, Tamotsu & Yanagita, Tatsuo & Kaizoji, Taisei & Toyabe, Kazutaka, 2007. "Regional business cycle synchronization through expectations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 383(1), pages 102-107.

    Cited by:

    1. Tamotsu Onozaki, 2018. "Nonlinearity, Bounded Rationality, and Heterogeneity," Springer Books, Springer, number 978-4-431-54971-0, June.
    2. Esashi, Kunihiko & Onozaki, Tamotsu & Saiki, Yoshitaka & Sato, Yuzuru, 2018. "Intermittent transition between synchronization and desynchronization in multi-regional business cycles," Structural Change and Economic Dynamics, Elsevier, vol. 44(C), pages 68-76.

  17. Ikeda, Yuichi & Souma, Wataru & Aoyama, Hideaki & Iyetomi, Hiroshi & Fujiwara, Yoshi & Kaizoji, Taisei, 2007. "Quantitative agent-based firm dynamics simulation with parameters estimated by financial and transaction data analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 375(2), pages 651-667.

    Cited by:

    1. Yuichi Ikeda & Hideaki Aoyama & Hiroshi Iyetomi & Yoshi Fujiwara & Wataru Souma, 2008. "Correlated performance of firms in a transaction network," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 3(1), pages 73-80, June.
    2. Ikeda, Yuichi & Aoyama, Hideaki & Iyetomi, Hiroshi & Fujiwara, Yoshi & Souma, Wataru & Kaizoji, Taisei, 2007. "Response of firm agent network to exogenous shock," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 138-148.

  18. Souma, Wataru & Aoyama, Hideaki & Fujiwara, Yoshi & Ikeda, Yuichi & Iyetomi, Hiroshi & Kaizoji, Taisei, 2006. "Correlation in business networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 370(1), pages 151-155.

    Cited by:

    1. Yuichi Ikeda & Hideaki Aoyama & Hiroshi Iyetomi & Yoshi Fujiwara & Wataru Souma, 2008. "Correlated performance of firms in a transaction network," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 3(1), pages 73-80, June.
    2. Brida, Juan Gabriel & Matesanz, David & Seijas, Maria Nela, 2016. "Network analysis of returns and volume trading in stock markets: The Euro Stoxx case," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 751-764.
    3. Mary Han & Bill McKelvey, 2016. "How to Grow Successful Social Entrepreneurship Firms? Key Ideas from Complexity Theory," Journal of Enterprising Culture (JEC), World Scientific Publishing Co. Pte. Ltd., vol. 24(03), pages 243-280, September.
    4. Pierpaolo Andriani & Bill McKelvey, 2009. "Perspective ---From Gaussian to Paretian Thinking: Causes and Implications of Power Laws in Organizations," Organization Science, INFORMS, vol. 20(6), pages 1053-1071, December.
    5. Sankowska, Anna & Siudak, Dariusz, 2016. "The small world phenomenon and assortative mixing in Polish corporate board and director networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 309-315.
    6. Giulia Rotundo & Anna D’Arcangelis, 2014. "Network of companies: an analysis of market concentration in the Italian stock market," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(4), pages 1893-1910, July.
    7. Ikeda, Yuichi & Souma, Wataru & Aoyama, Hideaki & Iyetomi, Hiroshi & Fujiwara, Yoshi & Kaizoji, Taisei, 2007. "Quantitative agent-based firm dynamics simulation with parameters estimated by financial and transaction data analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 375(2), pages 651-667.
    8. Juan Brida & Wiston Risso, 2010. "Dynamics and Structure of the 30 Largest North American Companies," Computational Economics, Springer;Society for Computational Economics, vol. 35(1), pages 85-99, January.

  19. Scalas, Enrico & Kaizoji, Taisei & Kirchler, Michael & Huber, Jürgen & Tedeschi, Alessandra, 2006. "Waiting times between orders and trades in double-auction markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 366(C), pages 463-471.
    See citations under working paper version above.
  20. T. Kaizoji, 2006. "A precursor of market crashes: Empirical laws of Japan's internet bubble," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 50(1), pages 123-127, March.

    Cited by:

    1. Levan Efremidze & John Rutledge & Thomas D. Willett, 2016. "Capital Flow Surges As Bubbles: Behavioral Finance And Mckinnon’S Over-Borrowing Syndrome Extended," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 61(02), pages 1-27, June.
    2. Bikramaditya Ghosh & Spyros Papathanasiou & Georgios Pergeris, 2022. "Did cryptocurrencies exhibit log‐periodic power law signature during the second wave of COVID‐19?," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 51(3), November.
    3. Vidal-Tomás, David & Alfarano, Simone, 2018. "An agent based early warning indicator for financial market instability," MPRA Paper 89693, University Library of Munich, Germany.
    4. John Rutledge, 2015. "Economics as energy framework: Complexity, turbulence, financial crises, and protectionism," Review of Financial Economics, John Wiley & Sons, vol. 25(1), pages 10-18, April.
    5. Guevara Hidalgo, Esteban, 2017. "Bin size independence in intra-day seasonalities for relative prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 722-732.
    6. Kerim Eser AFÞAR & Zakayo S. KISAVA, 2018. "The analysis of bubbles and crashes on financial markets for emerging economies: Evidenced From BRICS," Turkish Economic Review, KSP Journals, vol. 5(1), pages 1-11, March.
    7. Cajueiro, Daniel O. & Tabak, Benjamin M. & Werneck, Filipe K., 2009. "Can we predict crashes? The case of the Brazilian stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(8), pages 1603-1609.
    8. Graham Bird & Wenti Du & Thomas Willett, 2017. "Behavioral Finance and Efficient Markets: What does the Euro Crisis Tell us?," Open Economies Review, Springer, vol. 28(2), pages 273-295, April.
    9. Todorova, Lora & Vogt, Bodo, 2011. "Power law distribution in high frequency financial data? An econometric analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4433-4444.
    10. Takayuki Mizuno & Takaaki Ohnishi & Tsutomu Watanabe, 2016. "Power laws in market capitalization during the Dot-com and Shanghai bubble periods," CARF F-Series CARF-F-392, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    11. Brée, David S. & Joseph, Nathan Lael, 2013. "Testing for financial crashes using the Log Periodic Power Law model," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 287-297.
    12. Frederic Abergel & Nicolas Huth & Ioane Muni Toke, 2009. "Financial bubbles analysis with a cross-sectional estimator," Papers 0909.2885, arXiv.org.
    13. Rutledge, John, 2015. "Economics as energy framework: Complexity, turbulence, financial crises, and protectionism," Review of Financial Economics, Elsevier, vol. 25(C), pages 10-18.
    14. Blackwell, Calvin, 2018. "Power Laws in Real Estate Prices? Some Evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 90-98.
    15. Esteban Guevara Hidalgo, 2015. "Bin Size Independence in Intra-day Seasonalities for Relative Prices," Papers 1501.05176, arXiv.org, revised Dec 2016.
    16. Kaizoji, Taisei & Miyano, Michiko, 2016. "Why does the power law for stock price hold?," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 19-23.
    17. Takayuki Mizuno & Takaaki Ohnishi & Tsutomu Watanabe, 2019. "Detecting stock market bubbles based on the cross-sectional dispersion of stock prices," CARF F-Series CARF-F-463, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    18. Takayuki Mizuno & Takaaki Ohnishi & Tsutomu Watanabe, 2016. "Power laws in market capitalization during the Dot-com and Shanghai bubble periods," UTokyo Price Project Working Paper Series 070, University of Tokyo, Graduate School of Economics.
    19. Mizuno, Takayuki & Ohnishi, Takaaki & Watanabe, Tsutomu, 2017. "Stock market bubble detection based on the price dispersion among similar listed Firms," HIT-REFINED Working Paper Series 67, Institute of Economic Research, Hitotsubashi University.
    20. Mizuno, Takayuki & Ohnishi, Takaaki & Watanabe, Tsutomu, 2016. "Power law in market capitalization during Dot-com and Shanghai bubble periods," HIT-REFINED Working Paper Series 60, Institute of Economic Research, Hitotsubashi University.

  21. Kaizoji, Taisei, 2006. "An interacting-agent model of financial markets from the viewpoint of nonextensive statistical mechanics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 370(1), pages 109-113.
    See citations under working paper version above.
  22. Kaizoji, Taisei & Kaizoji, Michiyo, 2004. "Power law for the calm-time interval of price changes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 336(3), pages 563-570.
    See citations under working paper version above.
  23. Kaizoji, Taisei & Kaizoji, Michiyo, 2004. "Power law for ensembles of stock prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 240-243.
    See citations under working paper version above.
  24. Kaizoji, Taisei & Kaizoji, Michiyo, 2004. "A mechanism leading from bubbles to crashes: the case of Japan's land market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 138-141.

    Cited by:

    1. Marcin Wk{a}torek & Stanis{l}aw Dro.zd.z & Jaros{l}aw Kwapie'n & Ludovico Minati & Pawe{l} O'swik{e}cimka & Marek Stanuszek, 2020. "Multiscale characteristics of the emerging global cryptocurrency market," Papers 2010.15403, arXiv.org, revised Mar 2021.
    2. Blackwell, Calvin, 2018. "Power Laws in Real Estate Prices? Some Evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 90-98.
    3. Zheng, Zhiyong & Lu, Yunfan & Zhang, Junhuan, 2022. "Multiscale complexity fluctuation behaviours of stochastic interacting cryptocurrency price model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    4. D'Acci, Luca S., 2023. "Is housing price distribution across cities, scale invariant? Fractal distribution of settlements' house prices as signature of self-organized complexity," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    5. Kaizoji, Taisei, 2004. "Inflation and deflation in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 343(C), pages 662-668.

  25. Kaizoji, Taisei, 2004. "Inflation and deflation in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 343(C), pages 662-668.

    Cited by:

    1. Taisei Kaizoji, 2005. "Comparison of volatility distributions in the periods of booms and stagnations: an empirical study on stock price indices," Papers physics/0506114, arXiv.org.
    2. Martins, Francisco Leonardo Bezerra & do Nascimento, José Cláudio, 2022. "Power law dynamics in genealogical graphs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    3. Taisei Kaizoji & Michiyo Kaizoji, 2003. "Empirical Laws Of A Stock Price Index And A Stochastic Model," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 6(03), pages 303-312.

  26. Fujiwara, Yoshi & Souma, Wataru & Aoyama, Hideaki & Kaizoji, Taisei & Aoki, Masanao, 2003. "Growth and fluctuations of personal income," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 321(3), pages 598-604.
    See citations under working paper version above.
  27. Taisei Kaizoji & Michiyo Kaizoji, 2003. "Empirical Laws Of A Stock Price Index And A Stochastic Model," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 6(03), pages 303-312.

    Cited by:

    1. Bikramaditya Ghosh & Spyros Papathanasiou & Georgios Pergeris, 2022. "Did cryptocurrencies exhibit log‐periodic power law signature during the second wave of COVID‐19?," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 51(3), November.
    2. Taisei Kaizoji, 2005. "Comparison of volatility distributions in the periods of booms and stagnations: an empirical study on stock price indices," Papers physics/0506114, arXiv.org.
    3. Taisei Kaizoji, 2010. "Stock volatility in the periods of booms and stagnations," EERI Research Paper Series EERI_RP_2010_07, Economics and Econometrics Research Institute (EERI), Brussels.
    4. Taisei Kaizoji, 2013. "Modeling of Stock Returns and Trading Volume," Papers 1309.2416, arXiv.org.
    5. Taisei Kaizoji, 2013. "Modelling of Stock Returns and Trading Volume," IIM Kozhikode Society & Management Review, , vol. 2(2), pages 147-155, July.
    6. Ramos, Antônio M.T. & Carvalho, J.A. & Vasconcelos, G.L., 2016. "Exponential model for option prices: Application to the Brazilian market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 445(C), pages 161-168.
    7. Raj Kumar Pan & Sitabhra Sinha, 2006. "Inverse cubic law of index fluctuation distribution in Indian markets," Papers physics/0607014, arXiv.org, revised Dec 2007.

  28. Kaizoji, Taisei, 2003. "Scaling behavior in land markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 326(1), pages 256-264.
    See citations under working paper version above.
  29. Kaizoji, Taisei & Bornholdt, Stefan & Fujiwara, Yoshi, 2002. "Dynamics of price and trading volume in a spin model of stock markets with heterogeneous agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 316(1), pages 441-452.
    See citations under working paper version above.
  30. Kaizoji, Taisei, 2001. "A model of international financial crises," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(1), pages 279-293.

    Cited by:

    1. Guglielmo Maria Caporale & Antoaneta Serguieva & Hao Wu, 2008. "Financial Contagion: Evolutionary Optimisation of a Multinational Agent-Based Model," CESifo Working Paper Series 2444, CESifo.
    2. Taisei Kaizoji, 2013. "Modeling of Stock Returns and Trading Volume," Papers 1309.2416, arXiv.org.
    3. Taisei Kaizoji, 2013. "Modelling of Stock Returns and Trading Volume," IIM Kozhikode Society & Management Review, , vol. 2(2), pages 147-155, July.
    4. Ling-Yun He, 2010. "Is Price Behavior Scaling and Multiscaling in a Dealer Market? Perspectives from Multi-Agent Based Experiments," Computational Economics, Springer;Society for Computational Economics, vol. 36(3), pages 263-282, October.

  31. Kaizoji, Taisei, 2000. "Speculative bubbles and crashes in stock markets: an interacting-agent model of speculative activity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 287(3), pages 493-506.
    See citations under working paper version above.
  32. Kaizouji, Taisei, 1994. "Multiple equilibria and chaotic tatonnement: Applications of the Yamaguti-Matano theorem," Journal of Economic Behavior & Organization, Elsevier, vol. 24(3), pages 357-362, August.

    Cited by:

    1. Kaizoji, Taisei, 2010. "Multiple equilibria and chaos in a discrete tâtonnement process," MPRA Paper 24002, University Library of Munich, Germany.
    2. Ahmad K. Naimzada & Serena Sordi, 2016. "On controlling chaos in a discrete tâtonnement process," Department of Economics University of Siena 729, Department of Economics, University of Siena.
    3. Huang, Weihong, 2001. "Statistical dynamics and Walras' law," Journal of Economic Behavior & Organization, Elsevier, vol. 46(1), pages 57-71, September.
    4. Ahmad K. Naimzada & Serena Sordi, 2018. "On controlling chaos in a discrete†time Walrasian tâtonnement process," Metroeconomica, Wiley Blackwell, vol. 69(1), pages 178-194, February.
    5. Cavalli, Fausto & Naimzada, Ahmad, 2015. "A tâtonnement process with fading memory, stabilization and optimal speed of convergence," Chaos, Solitons & Fractals, Elsevier, vol. 79(C), pages 116-129.

Books

  1. Anindya S. Chakrabarti & Lukáš Pichl & Taisei Kaizoji (ed.), 2019. "Network Theory and Agent-Based Modeling in Economics and Finance," Springer Books, Springer, number 978-981-13-8319-9, June.

    Cited by:

    1. Surajit Borkotokey & Sujata Goala & Niharika Kakoty & Parishmita Boruah, 2022. "The component-wise egalitarian Myerson value for Network Games," Papers 2201.02793, arXiv.org.
    2. Kukacka, Jiri & Sacht, Stephen, 2023. "Estimation of heuristic switching in behavioral macroeconomic models," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
    3. Nils Bertschinger & Axel A. Araneda, 2021. "Cross-ownership as a structural explanation for rising correlations in crisis times," Papers 2112.04824, arXiv.org.

  2. Akira Namatame & Taisei Kaizouji & Yuuji Aruka (ed.), 2006. "The Complex Networks of Economic Interactions," Lecture Notes in Economics and Mathematical Systems, Springer, number 978-3-540-28727-8, October.

    Cited by:

    1. Y.-C. Ni & H. P. Yin & C. Xu & P. M. Hui, 2011. "Analyzing phase diagrams and phase transitions in networked competing populations," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 80(2), pages 233-241, March.
    2. Yuji Aruka, 2024. "Interpreting the Iterated Dilemma Games by Using the Presentation Like “Cellular Automatons”," Springer Texts in Business and Economics, in: Evolutionary Economics, chapter 0, pages 57-72, Springer.
    3. Hayashi, Katsuhiko & Kaizoji, Taisei & Pichl, Lukáš, 2007. "Correlation patterns of NIKKEI index constituents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 383(1), pages 16-21.
    4. Slanina, Frantisek, 2013. "Essentials of Econophysics Modelling," OUP Catalogue, Oxford University Press, number 9780199299683.

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