IDEAS home Printed from https://ideas.repec.org/a/taf/apmtfi/v23y2016i6p465-483.html
   My bibliography  Save this article

Optimal prediction of resistance and support levels

Author

Listed:
  • T. De Angelis
  • G. Peskir

Abstract

Assuming that the asset price X follows a geometric Brownian motion, we study the optimal prediction problem$$\mathop {\inf }\limits_{0\,\le\,\tau\,\le\;T} {\mathfrak{E}}\,\left| {X_\tau ^x - \ell } \right|$$inf0≤τ≤TEXτx−ℓ where the infimum is taken over stopping times $$\tau $$τ of X and $$\ell $$ℓ is a hidden aspiration level (having a potential of creating a resistance or support level for X). Adopting the ‘aspiration-level hypothesis’ and assuming that $$\ell $$ℓ is independent from X, we show that a wide class of admissible (non-oscillatory) laws of $$\ell $$ℓ lead to unique optimal trading boundaries that can be viewed as the ‘conditional median curves’ for the resistance and support levels (with respect to X and T). We prove the existence of these boundaries and derive the (nonlinear) integral equations which characterize them uniquely. The results are illustrated through some specific examples of admissible laws and their conditional median curves.

Suggested Citation

  • T. De Angelis & G. Peskir, 2016. "Optimal prediction of resistance and support levels," Applied Mathematical Finance, Taylor & Francis Journals, vol. 23(6), pages 465-483, November.
  • Handle: RePEc:taf:apmtfi:v:23:y:2016:i:6:p:465-483
    DOI: 10.1080/1350486X.2017.1297729
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/1350486X.2017.1297729
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/1350486X.2017.1297729?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Shefrin, Hersh, 2008. "A Behavioral Approach to Asset Pricing," Elsevier Monographs, Elsevier, edition 2, number 9780123743565.
    2. Sonnemans, Joep, 2006. "Price clustering and natural resistance points in the Dutch stock market: A natural experiment," European Economic Review, Elsevier, vol. 50(8), pages 1937-1950, November.
    3. Carla Gomes & Henri Waelbroeck, 2010. "An empirical study of liquidity dynamics and resistance and support levels," Quantitative Finance, Taylor & Francis Journals, vol. 10(10), pages 1099-1107.
    4. Peskir, Goran, 2012. "Optimal detection of a hidden target: The median rule," Stochastic Processes and their Applications, Elsevier, vol. 122(5), pages 2249-2263.
    5. Herbert A. Simon, 1955. "A Behavioral Model of Rational Choice," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 69(1), pages 99-118.
    6. Carol L. Osler, 2000. "Support for resistance: technical analysis and intraday exchange rates," Economic Policy Review, Federal Reserve Bank of New York, issue Jul, pages 53-68.
    7. Kristoffer Glover & Hardy Hulley & Goran Peskir, 2011. "Three-Dimensional Brownian Motion and the Golden Ratio Rule," Research Paper Series 295, Quantitative Finance Research Centre, University of Technology, Sydney.
    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. Zhenya Liu & Yuhao Mu, 2022. "Optimal Stopping Methods for Investment Decisions: A Literature Review," IJFS, MDPI, vol. 10(4), pages 1-23, October.
    2. Tiziano De Angelis, 2020. "Stopping spikes, continuation bays and other features of optimal stopping with finite-time horizon," Papers 2009.01276, arXiv.org, revised Jan 2022.
    3. Vicky Henderson & Saul Jacka & Ruiqi Liu, 2021. "The Support and Resistance Line Method: An Analysis via Optimal Stopping," Papers 2103.02331, arXiv.org.

    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. von Hagen, Jürgen & Kube, Sebastian & Kaiser, Johannes & Selten, Reinhard & Pope, Robin, 2006. "Prominent Numbers and Ratios in Exchange Rate Determination: Field and Laboratory Evidence," Bonn Econ Discussion Papers 29/2006, University of Bonn, Bonn Graduate School of Economics (BGSE).
    2. Brown, Alasdair & Yang, Fuyu, 2016. "Limited cognition and clustered asset prices: Evidence from betting markets," Journal of Financial Markets, Elsevier, vol. 29(C), pages 27-46.
    3. Danso, Albert & Lartey, Theophilus & Amankwah-Amoah, Joseph & Adomako, Samuel & Lu, Qinye & Uddin, Moshfique, 2019. "Market sentiment and firm investment decision-making," International Review of Financial Analysis, Elsevier, vol. 66(C).
    4. Gapeev, Pavel V., 2020. "Optimal stopping problems for running minima with positive discounting rates," LSE Research Online Documents on Economics 105849, London School of Economics and Political Science, LSE Library.
    5. Gapeev, Pavel V., 2020. "Optimal stopping problems for running minima with positive discounting rates," Statistics & Probability Letters, Elsevier, vol. 167(C).
    6. Pavel V. Gapeev & Neofytos Rodosthenous & V. L. Raju Chinthalapati, 2019. "On the Laplace Transforms of the First Hitting Times for Drawdowns and Drawups of Diffusion-Type Processes," Risks, MDPI, vol. 7(3), pages 1-15, August.
    7. Gapeev, Pavel V. & Rodosthenous, Neofytos & Chinthalapati, V.L Raju, 2019. "On the Laplace transforms of the first hitting times for drawdowns and drawups of diffusion-type processes," LSE Research Online Documents on Economics 101272, London School of Economics and Political Science, LSE Library.
    8. Gapeev, Pavel V. & Rodosthenous, Neofytos, 2016. "Perpetual American options in diffusion-type models with running maxima and drawdowns," Stochastic Processes and their Applications, Elsevier, vol. 126(7), pages 2038-2061.
    9. Torgler, Benno & Schneider, Friedrich & Schaltegger, Christoph A., 2007. "With or Against the People? The Impact of a Bottom-Up Approach on Tax Morale and the Shadow Economy," Berkeley Olin Program in Law & Economics, Working Paper Series qt6331x6vz, Berkeley Olin Program in Law & Economics.
    10. Daniel Fonseca Costa & Francisval Carvalho & Bruno César Moreira & José Willer Prado, 2017. "Bibliometric analysis on the association between behavioral finance and decision making with cognitive biases such as overconfidence, anchoring effect and confirmation bias," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1775-1799, June.
    11. Christina Leuker & Thorsten Pachur & Ralph Hertwig & Timothy J. Pleskac, 2019. "Do people exploit risk–reward structures to simplify information processing in risky choice?," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 5(1), pages 76-94, August.
    12. Jae Wook Yoo & Richard Reed & Shung Jae Shin & David J. Lemak, 2009. "Strategic Choice and Performance in Late Movers: Influence of the Top Management Team's External Ties," Journal of Management Studies, Wiley Blackwell, vol. 46(2), pages 308-335, March.
    13. Giovanni Calice & Levent Kutlu & Ming Zeng, 2021. "Understanding US firm efficiency and its asset pricing implications," Empirical Economics, Springer, vol. 60(2), pages 803-827, February.
    14. Westerhoff, Frank H. & Dieci, Roberto, 2006. "The effectiveness of Keynes-Tobin transaction taxes when heterogeneous agents can trade in different markets: A behavioral finance approach," Journal of Economic Dynamics and Control, Elsevier, vol. 30(2), pages 293-322, February.
    15. José Castro Caldas & Helder Coelho, 1999. "The Origin of Institutions: Socio-Economic Processes, Choice, Norms and Conventions," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 2(2), pages 1-1.
    16. Shi, Yun & Cui, Xiangyu & Zhou, Xunyu, 2020. "Beta and Coskewness Pricing: Perspective from Probability Weighting," SocArXiv 5rqhv, Center for Open Science.
    17. Nagler Matthew G., 2007. "Understanding the Internet's Relevance to Media Ownership Policy: A Model of Too Many Choices," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 7(1), pages 1-28, June.
    18. Ranganathan, Kavitha & Lejarraga, Tomás, 2021. "Elicitation of risk preferences through satisficing," Journal of Behavioral and Experimental Finance, Elsevier, vol. 32(C).
    19. Westerhoff Frank H., 2008. "The Use of Agent-Based Financial Market Models to Test the Effectiveness of Regulatory Policies," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 228(2-3), pages 195-227, April.
    20. Andrew Caplin & Mark Dean & Daniel Martin, 2011. "Search and Satisficing," American Economic Review, American Economic Association, vol. 101(7), pages 2899-2922, December.

    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:taf:apmtfi:v:23:y:2016:i:6:p:465-483. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RAMF20 .

    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.