IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/89682.html
   My bibliography  Save this paper

Regression Forward avec fenêtres Tempo-Frequentielles roulantes par ondelettes discretes et continues -Une application à la Droite de Marché -
[Forward Regression with Discrete and Continuous Wavelets Time-Frequency Window -An application to the Market Line-]

Author

Listed:
  • MESTRE, Roman
  • Terraza, Michel

Abstract

The Rolling-Regression are currently used to study the parameters stability over time. In finance, we can analyse the time evolutions of systematic risk relaxing the constant-Beta hypothesis. This method can be associated with a wavelet decomposition of the variables in order to the parameters stability of frequency regression. Then, we compare continuous and discrete wavelets methodologies of rolling regression with the standard rolling regression. The discrete methods are based on time-frequency window but we compare if we have to use it on the wavelets filter output or directly on the series and realize the wavelet decomposition at each step of the window. The continuous method is based on wavelets coherence-phase. We use daily data of AXA returns and the CAC 40 index from 2005 to 2015. We show that the differences between discrete methods are more important at Low-Frequencies and we compare the results with the Continuous Time-Frequency Betas.

Suggested Citation

  • MESTRE, Roman & Terraza, Michel, 2018. "Regression Forward avec fenêtres Tempo-Frequentielles roulantes par ondelettes discretes et continues -Une application à la Droite de Marché - [Forward Regression with Discrete and Continuous Wavel," MPRA Paper 89682, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:89682
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/89682/1/MPRA_paper_89682.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. R.W. Faff & R.D. Brooks, 1998. "Time‐varying Beta Risk for Australian Industry Portfolios: An Exploratory Analysis," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 25(5‐6), pages 721-745, June.
    2. Roman Mestre & Michel Terraza, 2018. "Time-Frequency Analysis of capm: Application to the cac 40," Managing Global Transitions, University of Primorska, Faculty of Management Koper, vol. 16(2 (Summer), pages 141-157.
    3. Fama, Eugene F & MacBeth, James D, 1973. "Risk, Return, and Equilibrium: Empirical Tests," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 607-636, May-June.
    4. Bekiros, Stelios & Nguyen, Duc Khuong & Uddin, Gazi Salah & Sjö, Bo, 2016. "On the time scale behavior of equity-commodity links: Implications for portfolio management," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 41(C), pages 30-46.
    5. Roman Mestre & Michel Terraza, 2018. "Time-Frequency varying beta estimation -a continuous wavelets approach-," Economics Bulletin, AccessEcon, vol. 38(4), pages 1796-1810.
    6. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    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. Roman Mestre & Michel Terraza, 2018. "Time-Frequency varying beta estimation -a continuous wavelets approach-," Economics Bulletin, AccessEcon, vol. 38(4), pages 1796-1810.
    2. Roman Mestre, 2023. "Stock profiling using time–frequency-varying systematic risk measure," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-29, December.
    3. MESTRE, Roman & TERRAZA, Michel, 2017. "Estimation du Beta Tempo-fréquentiel de la Droite de Marché-Une approche par les ondelettes continues- [Time-Frequency varying Beta Estimation -A continuous wavelets approach-]," MPRA Paper 86335, University Library of Munich, Germany.
    4. Roman Mestre, 2021. "A wavelet approach of investing behaviors and their effects on risk exposures," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-37, December.
    5. Rémi Odry & Roman Mestre, 2021. "Monetary Policy and Business Cycle Synchronization in Europe," Working Papers hal-04159759, HAL.
    6. Hearn, Bruce, 2011. "Modelling size and liquidity in North African industrial sectors," Emerging Markets Review, Elsevier, vol. 12(1), pages 21-46, March.
    7. Wang, Daxue, 2008. "Herd behavior towards the market index: Evidence from 21 financial markets," IESE Research Papers D/776, IESE Business School.
    8. Michel Terraza & Roman Mestre, 2021. "Adjusted beta based on an empirical comparison of OLS ‐CAPM and the CAPM with EGARCH errors," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3588-3598, July.
    9. Don U.A. Galagedera, 2004. "A survey on risk-return analysis," Finance 0406010, University Library of Munich, Germany.
    10. Petros Messis & Antonis Alexandridis & Achilleas Zapranis, 2021. "Testing and comparing conditional risk‐return relationship with a new approach in the cross‐sectional framework," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 218-240, January.
    11. Muhammad Kashif & Thomas Leirvik, 2022. "The MAX Effect in an Oil Exporting Country: The Case of Norway," JRFM, MDPI, vol. 15(4), pages 1-16, March.
    12. Radosław Kurach, 2013. "Does Beta Explain Global Equity Market Volatility – Some Empirical Evidence," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 7(2), June.
    13. Shi, Yun & Cui, Xiangyu & Zhou, Xunyu, 2020. "Beta and Coskewness Pricing: Perspective from Probability Weighting," SocArXiv 5rqhv, Center for Open Science.
    14. Abugri, Benjamin A. & Dutta, Sandip, 2014. "Are we overestimating REIT idiosyncratic risk? Analysis of pricing effects and persistence," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 249-259.
    15. Shaikh, Salman, 2013. "Investment Decisions by Analysts: A Case Study of KSE," MPRA Paper 53802, University Library of Munich, Germany.
    16. Turan G. Bali & Robert F. Engle & Yi Tang, 2017. "Dynamic Conditional Beta Is Alive and Well in the Cross Section of Daily Stock Returns," Management Science, INFORMS, vol. 63(11), pages 3760-3779, November.
    17. Cakici, Nusret & Zaremba, Adam, 2022. "Salience theory and the cross-section of stock returns: International and further evidence," Journal of Financial Economics, Elsevier, vol. 146(2), pages 689-725.
    18. Ciciretti, Rocco & Dalò, Ambrogio & Dam, Lammertjan, 2023. "The contributions of betas versus characteristics to the ESG premium," Journal of Empirical Finance, Elsevier, vol. 71(C), pages 104-124.
    19. Ladislav Kristoufek & Paulo Ferreira, 2018. "Capital asset pricing model in Portugal: Evidence from fractal regressions," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 17(3), pages 173-183, November.
    20. Warnes, Ignacio & Warnes, Pablo E., 2014. "Country risk and the cost of equity in emerging markets," Journal of Multinational Financial Management, Elsevier, vol. 28(C), pages 15-27.

    More about this item

    Keywords

    Time-Frequency Rolling Regression; Wavelets; Time-Frequency Betas; CWT; MODWT;
    All these keywords.

    JEL classification:

    • G00 - Financial Economics - - General - - - General
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    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:pra:mprapa:89682. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    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.