IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1210.1966.html
   My bibliography  Save this paper

How We Tend To Overestimate Powerlaw Tail Exponents

Author

Listed:
  • Nassim N. Taleb

Abstract

In the presence of a layer of metaprobabilities (from uncertainty concerning the parameters), the asymptotic tail exponent corresponds to the lowest possible tail exponent regardless of its probability. The problem explains "Black Swan" effects, i.e., why measurements tend to chronically underestimate tail contributions, rather than merely deliver imprecise but unbiased estimates.

Suggested Citation

  • Nassim N. Taleb, 2012. "How We Tend To Overestimate Powerlaw Tail Exponents," Papers 1210.1966, arXiv.org.
    • Handle: RePEc:arx:papers:1210.1966
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1210.1966
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. N. N. Taleb & R. Douady, 2013. "Mathematical definition, mapping, and detection of (anti)fragility," Quantitative Finance, Taylor & Francis Journals, vol. 13(11), pages 1677-1689, November.
    2. Rafał Weron, 2001. "Levy-Stable Distributions Revisited: Tail Index> 2does Not Exclude The Levy-Stable Regime," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 12(02), pages 209-223.
    3. repec:hum:wpaper:sfb649dp2005-008 is not listed on IDEAS
    4. Borak, Szymon & Härdle, Wolfgang Karl & Weron, Rafał, 2005. "Stable distributions," SFB 649 Discussion Papers 2005-008, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    Full references (including those not matched with items on IDEAS)

    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. Weron, Rafał, 2004. "Computationally intensive Value at Risk calculations," Papers 2004,32, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    2. Taleb, Nassim Nicholas, 2009. "Errors, robustness, and the fourth quadrant," International Journal of Forecasting, Elsevier, vol. 25(4), pages 744-759, October.
    3. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2007. "Agent-based Models of Financial Markets," Papers physics/0701140, arXiv.org.
    4. Raul Matsushita & Iram Gleria & Annibal Figueiredo & Sergio Da Silva, 2004. "The Econophysics of the Brazilian Real-US Dollar Rate," Finance 0407012, University Library of Munich, Germany.
    5. Figueiredo, Annibal & Gleria, Iram & Matsushita, Raul & Da Silva, Sergio, 2005. "Financial volatility and independent and identically distributed variables," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 346(3), pages 484-498.
    6. Barunik, Jozef & Vacha, Lukas, 2010. "Monte Carlo-based tail exponent estimator," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4863-4874.
    7. Kenneth Bruninx & Erik Delarue & William D'haeseleer, 2013. "Statistical description of the error on wind power forecasts via a Lévy α-stable distribution," RSCAS Working Papers 2013/50, European University Institute.
    8. Ayoub Ammy-Driss & Matthieu Garcin, 2021. "Efficiency of the financial markets during the COVID-19 crisis: time-varying parameters of fractional stable dynamics," Working Papers hal-02903655, HAL.
    9. Mahata, Ajit & Rai, Anish & Nurujjaman, Md. & Prakash, Om, 2021. "Modeling and analysis of the effect of COVID-19 on the stock price: V and L-shape recovery," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    10. Greg Hannsgen, 2011. "Infinite-variance, Alpha-stable Shocks in Monetary SVAR: Final Working Paper Version," Economics Working Paper Archive wp_682, Levy Economics Institute.
    11. Jabłońska-Sabuka, Matylda & Teuerle, Marek & Wyłomańska, Agnieszka, 2017. "Bivariate sub-Gaussian model for stock index returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 628-637.
    12. Apanisile Temitope Samuel, 2024. "The Justification of Complex Systems Analysis in Better Informing Project Decisions: A Study of the us Surface Transportation Board," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 11(8), pages 263-280, August.
    13. Fajardo, Jose Santiago, 2006. "Equivalent Martingale Measures and Lévy Processes," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 60(4), February.
    14. 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.
    15. Wang, Yi & Sun, Qi & Zhang, Zilu & Chen, Liqing, 2022. "A risk measure of the stock market that is based on multifractality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    16. Salhi, Khaled & Deaconu, Madalina & Lejay, Antoine & Champagnat, Nicolas & Navet, Nicolas, 2016. "Regime switching model for financial data: Empirical risk analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 148-157.
    17. Ece Oral, 2016. "Measuring Consumer Inflation Expectations in Turkey," Eastern European Business and Economics Journal, Eastern European Business and Economics Studies Centre, vol. 2(1), pages 43-74.
    18. Yuri Biondi & Pierpaolo Giannoccolo, 2015. "Share price formation, market exuberance and financial stability under alternative accounting regimes," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 10(2), pages 333-362, October.
    19. Stachura Michał & Wodecka Barbara, 2022. "k-th record estimator of the scale parameter of the α-stable distribution," Statistics in Transition New Series, Statistics Poland, vol. 23(4), pages 203-215, December.
    20. Raphaël Douady, 2019. "Managing the Downside of Active and Passive Strategies: Convexity and Fragilities," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-02488589, HAL.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:arx:papers:1210.1966. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.