IDEAS home Printed from https://ideas.repec.org/r/pra/mprapa/47869.html
   My bibliography  Save this item

Everything You Always Wanted to Know about Log Periodic Power Laws for Bubble Modelling but Were Afraid to Ask

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Yao, Can-Zhong & Li, Hong-Yu, 2021. "A study on the bursting point of Bitcoin based on the BSADF and LPPLS methods," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
  2. Zhang, Yue-Jun & Yao, Ting, 2016. "Interpreting the movement of oil prices: Driven by fundamentals or bubbles?," Economic Modelling, Elsevier, vol. 55(C), pages 226-240.
  3. G. Demos & D. Sornette, 2017. "Birth or burst of financial bubbles: which one is easier to diagnose?," Quantitative Finance, Taylor & Francis Journals, vol. 17(5), pages 657-675, May.
  4. Fantazzini, Dean, 2016. "The oil price crash in 2014/15: Was there a (negative) financial bubble?," Energy Policy, Elsevier, vol. 96(C), pages 383-396.
  5. Cheah, Eng-Tuck & Fry, John, 2015. "Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin," Economics Letters, Elsevier, vol. 130(C), pages 32-36.
  6. Fantazzini, Dean & Nigmatullin, Erik & Sukhanovskaya, Vera & Ivliev, Sergey, 2016. "Everything you always wanted to know about bitcoin modelling but were afraid to ask. I," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 44, pages 5-24.
  7. Kristoffer Pons Bertelsen, 2019. "Comparing Tests for Identification of Bubbles," CREATES Research Papers 2019-16, Department of Economics and Business Economics, Aarhus University.
  8. Papastamatiou, Konstantinos & Karakasidis, Theodoros, 2022. "Bubble detection in Greek Stock Market: A DS-LPPLS model approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 587(C).
  9. Daniel T. Pele, 2012. "An Lppl Algorithm For Estimating The Critical Time Of A Stock Market Bubble," Journal of Social and Economic Statistics, Bucharest University of Economic Studies, vol. 1(2), pages 14-22, DECEMBER.
  10. Marco Bianchetti & Davide Galli & Camilla Ricci & Angelo Salvatori & Marco Scaringi, 2016. "Brexit or Bremain ? Evidence from bubble analysis," Papers 1606.06829, arXiv.org.
  11. Giulio Cifarelli and Paolo Paesani, 2021. "Navigating the Oil Bubble: A Non-linear Heterogeneous-agent Dynamic Model of Futures Oil Pricing," The Energy Journal, International Association for Energy Economics, vol. 0(Number 5).
  12. Khalid Khan & Chi-Wei Su & Adnan Khurshid & Muhammad Umar, 2022. "Are there bubbles in the vanilla price?," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 10(1), pages 1-16, December.
  13. Guilherme Demos & Didier Sornette, 2017. "Lagrange regularisation approach to compare nested data sets and determine objectively financial bubbles' inceptions," Papers 1707.07162, arXiv.org.
  14. MITRACHE, Mihai-Andrei & BOITOUT, Nicolas, 2017. "Tracking Financial Bubbles On Romania Stock Market," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 21(1), pages 41-62.
  15. Kozłowska, M. & Denys, M. & Wiliński, M. & Link, G. & Gubiec, T. & Werner, T.R. & Kutner, R. & Struzik, Z.R., 2016. "Dynamic bifurcations on financial markets," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 126-142.
  16. Shu, Min & Zhu, Wei, 2020. "Detection of Chinese stock market bubbles with LPPLS confidence indicator," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).
  17. Pele, Daniel Traian & Mazurencu-Marinescu-Pele, Miruna, 2018. "Cryptocurrencies, Metcalfe's law and LPPL models," IRTG 1792 Discussion Papers 2018-056, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
  18. Sandro Lera & Didier Sornette, 2015. "Secular bipolar growth rate of the real US GDP per capita: implications for understanding past and future economic growth," Papers 1607.04136, arXiv.org.
  19. Mark Mizraki, 2015. "Conversation with Mark Mizruchi:“There is Very Little Organizational Theory Left in Sociology Departments”," Journal of Economic Sociology, National Research University Higher School of Economics, vol. 16(3), pages 14-25.
  20. Fry, John, 2012. "Exogenous and endogenous crashes as phase transitions in complex financial systems," MPRA Paper 36202, University Library of Munich, Germany.
  21. Min Shu & Ruiqiang Song & Wei Zhu, 2021. "The 2021 Bitcoin Bubbles and Crashes—Detection and Classification," Stats, MDPI, vol. 4(4), pages 1-21, November.
  22. Zhang, Qunzhi & Sornette, Didier & Balcilar, Mehmet & Gupta, Rangan & Ozdemir, Zeynel Abidin & Yetkiner, Hakan, 2016. "LPPLS bubble indicators over two centuries of the S&P 500 index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 126-139.
  23. Sornette, Didier & Woodard, Ryan & Yan, Wanfeng & Zhou, Wei-Xing, 2013. "Clarifications to questions and criticisms on the Johansen–Ledoit–Sornette financial bubble model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(19), pages 4417-4428.
  24. Hanwool Jang & Yena Song & Sungbin Sohn & Kwangwon Ahn, 2018. "Real Estate Soars and Financial Crises: Recent Stories," Sustainability, MDPI, vol. 10(12), pages 1-12, December.
  25. Daniel Traian Pele & Miruna Mazurencu-Marinescu & Peter Nijkamp, 2013. "Herding Behaviour, Bubbles and Log Periodic Power Laws in Illiquid Stock Markets. A Case Study on the Bucharest Stock Exchange," Tinbergen Institute Discussion Papers 13-109/VIII, Tinbergen Institute.
  26. Riza Demirer & Guilherme Demos & Rangan Gupta & Didier Sornette, 2019. "On the predictability of stock market bubbles: evidence from LPPLS confidence multi-scale indicators," Quantitative Finance, Taylor & Francis Journals, vol. 19(5), pages 843-858, May.
  27. John Fry & McMillan David, 2015. "Stochastic modelling for financial bubbles and policy," Cogent Economics & Finance, Taylor & Francis Journals, vol. 3(1), pages 1002152-100, December.
  28. Jang, Hanwool & Song, Yena & Ahn, Kwangwon, 2020. "Can government stabilize the housing market? The evidence from South Korea," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
  29. John Fry, 2014. "Bubbles, shocks and elementary technical trading strategies," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 87(1), pages 1-13, January.
  30. Fry, John & Cheah, Eng-Tuck, 2016. "Negative bubbles and shocks in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 343-352.
  31. Charalambos Pitros, 2014. "UK housing bubble case study analysis: The ‘‘behaviour’’ of UK housing bubbles and the ‘‘affordability’’ parameter," ERES eres2014_4, European Real Estate Society (ERES).
  32. José Parra-Moyano & Daniel Partida & Moritz Gessl & Somnath Mazumdar, 2024. "Analyzing swings in Bitcoin returns: a comparative study of the LPPL and sentiment-informed random forest models," Digital Finance, Springer, vol. 6(3), pages 427-439, September.
  33. Shihai Dong & Yandong Wang & Yanyan Gu & Shiwei Shao & Hui Liu & Shanmei Wu & Mengmeng Li, 2020. "Predicting the turning points of housing prices by combining the financial model with genetic algorithm," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-20, April.
  34. Ji, Hongyun & Zhang, Han, 2024. "Application of the LPPL model in the identification and measurement of structural bubbles in the Chinese stock market," The North American Journal of Economics and Finance, Elsevier, vol. 70(C).
  35. Martin Herdegen & Sebastian Herrmann, 2017. "Strict Local Martingales and Optimal Investment in a Black-Scholes Model with a Bubble," Papers 1711.06679, arXiv.org.
  36. Fantazzini, Dean & Nigmatullin, Erik & Sukhanovskaya, Vera & Ivliev, Sergey, 2017. "Everything you always wanted to know about bitcoin modelling but were afraid to ask. Part 2," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 45, pages 5-28.
  37. Hideyuki Takagi, 2021. "Exploring the Endogenous Nature of Meme Stocks Using the Log-Periodic Power Law Model and Confidence Indicator," Papers 2110.06190, arXiv.org.
  38. Demos, G. & Sornette, D., 2019. "Comparing nested data sets and objectively determining financial bubbles’ inceptions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 661-675.
  39. Dean Fantazzini, 2011. "Forecasting the Global Financial Crisis in the Years 2009-2010: Ex-post Analysis," Economics Bulletin, AccessEcon, vol. 31(4), pages 3259-3267.
  40. Jovanovic, Franck & Schinckus, Christophe, 2017. "Econophysics and Financial Economics: An Emerging Dialogue," OUP Catalogue, Oxford University Press, number 9780190205034.
  41. Filimonov, V. & Sornette, D., 2013. "A stable and robust calibration scheme of the log-periodic power law model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3698-3707.
  42. C. Vladimir Rodríguez-Caballero & Mauricio Villanueva-Domínguez, 2022. "Predicting cryptocurrency crash dates," Empirical Economics, Springer, vol. 63(6), pages 2855-2873, December.
  43. Christopher Lynch & Benjamin Mestel, 2017. "Logistic Model For Stock Market Bubbles And Anti-Bubbles," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(06), pages 1-24, September.
  44. Kwangwon Ahn & Hanwool Jang & Jinu Kim & Inug Ryu, 2024. "COVID-19 and REITs Crash: Predictability and Market Conditions," Computational Economics, Springer;Society for Computational Economics, vol. 63(3), pages 1159-1172, March.
  45. Hardik Rajpal & Deepak Dhar, 2018. "Achieving Perfect Coordination amongst Agents in the Co-Action Minority Game," Games, MDPI, vol. 9(2), pages 1-13, May.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.