IDEAS home Printed from https://ideas.repec.org/a/hin/complx/4237471.html
   My bibliography  Save this article

Forecasting Financial Crashes: Revisit to Log-Periodic Power Law

Author

Listed:
  • Bingcun Dai
  • Fan Zhang
  • Domenico Tarzia
  • Kwangwon Ahn

Abstract

We aim to provide an algorithm to predict the distribution of the critical times of financial bubbles employing a log-periodic power law. Our approach consists of a constrained genetic algorithm and an improved price gyration method, which generates an initial population of parameters using historical data for the genetic algorithm. The key enhancements of price gyration algorithm are (i) different window sizes for peak detection and (ii) a distance-based weighting approach for peak selection. Our results show a significant improvement in the prediction of financial crashes. The diagnostic analysis further demonstrates the accuracy, efficiency, and stability of our predictions.

Suggested Citation

  • Bingcun Dai & Fan Zhang & Domenico Tarzia & Kwangwon Ahn, 2018. "Forecasting Financial Crashes: Revisit to Log-Periodic Power Law," Complexity, Hindawi, vol. 2018, pages 1-12, August.
    • Handle: RePEc:hin:complx:4237471
    DOI: 10.1155/2018/4237471
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/8503/2018/4237471.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/8503/2018/4237471.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2018/4237471?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Vladimir Filimonov & Didier Sornette, "undated". "A Stable and Robust Calibration Scheme of the Log-Periodic Power Law Model," Working Papers ETH-RC-11-002, ETH Zurich, Chair of Systems Design.
    2. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Yi, Eojin & Ahn, Kwangwon & Choi, M.Y., 2022. "Cryptocurrency: Not far from equilibrium," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    2. Ryu, Inug & Jang, Hanwool & Kim, Dongshin & Ahn, Kwangwon, 2021. "Market Efficiency of US REITs: A Revisit," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    3. 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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wątorek Marcin & Stawiarski Bartosz, 2016. "Log-Periodic Power Law and Generalized Hurst Exponent Analysis in Estimating an Asset Bubble Bursting Time," Financial Internet Quarterly (formerly e-Finanse), Sciendo, vol. 12(3), pages 49-58, October.
    2. V. Filimonov & G. Demos & D. Sornette, 2017. "Modified profile likelihood inference and interval forecast of the burst of financial bubbles," Quantitative Finance, Taylor & Francis Journals, vol. 17(8), pages 1167-1186, August.
    3. Li Lin & Didier Sornette, 2015. ""Speculative Influence Network" during financial bubbles: application to Chinese Stock Markets," Papers 1510.08162, arXiv.org.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. Bikramaditya Ghosh & Spyros Papathanasiou & Vandita Dar & Dimitrios Kenourgios, 2022. "Deconstruction of the Green Bubble during COVID-19 International Evidence," Sustainability, MDPI, vol. 14(6), pages 1-18, March.
    12. Nathan Burks & Adetokunbo Fadahunsi & Ann Marie Hibbert, 2021. "Financial Contagion: A Tale of Three Bubbles," JRFM, MDPI, vol. 14(5), pages 1-14, May.
    13. Li, Chong, 2017. "Log-periodic view on critical dates of the Chinese stock market bubbles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 305-311.
    14. 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.
    15. 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).
    16. 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).
    17. Shu, Min & Zhu, Wei, 2020. "Real-time prediction of Bitcoin bubble crashes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 548(C).
    18. 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".
    19. 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.
    20. 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.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:complx:4237471. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.