IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-04058285.html
   My bibliography  Save this paper

Stock profiling using time–frequency-varying systematic risk measure

Author

Listed:
  • Roman Mestre

    (MRE - Montpellier Recherche en Economie - UM - Université de Montpellier)

Abstract

This study proposes a wavelets approach to estimating time–frequency-varying betas in the capital asset pricing model (CAPM) framework. The dynamic of systematic risk across time and frequency is analyzed to investigate stock risk-profile robustness. Furthermore, we emphasize the effect of an investor's investment horizon on the robustness of portfolio characteristics. We use a daily panel of French stocks from 2012 to 2022. Results show that varying systematic risk varies in time and frequency, and that its short and long-run evolutions differ. We observe differences in short and long dynamics, indicating that a stock's betas differently fluctuate to early announcements or signs of events. However, short-run and long-run betas exhibit similar dynamics during persistent shocks. Betas are more volatile during times of crisis, resulting in greater or lesser robustness of risk profiles. Significant differences exist in short-run and long-run risk profiles, implying a different asset allocation. We conclude that the standard CAPM assumes short-run investment. Then, investors should consider time–frequency CAPM to perform systematic risk analysis and portfolio allocation.

Suggested Citation

  • Roman Mestre, 2023. "Stock profiling using time–frequency-varying systematic risk measure," Post-Print hal-04058285, HAL.
  • Handle: RePEc:hal:journl:hal-04058285
    DOI: 10.1186/s40854-023-00457-7
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    References listed on IDEAS

    as
    1. McNevin, Bruce D. & Nix, Joan, 2018. "The beta heuristic from a time/frequency perspective: A wavelet analysis of the market risk of sectors," Economic Modelling, Elsevier, vol. 68(C), pages 570-585.
    2. Aasif Shah & Arif Tali & Qaiser Farooq, 2018. "Beta through the prism of wavelets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 4(1), pages 1-17, December.
    3. Robert D. Brooks & Robert W. Faff & Michael D. McKenzie, 1998. "Time†Varying Beta Risk of Australian Industry Portfolios: A Comparison of Modelling Techniques," Australian Journal of Management, Australian School of Business, vol. 23(1), pages 1-22, June.
    4. 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.
    5. Zhang, Dayong & Hu, Min & Ji, Qiang, 2020. "Financial markets under the global pandemic of COVID-19," Finance Research Letters, Elsevier, vol. 36(C).
    6. Ramazan Genay & Faruk Seļuk & Brandon Whitcher, 2003. "Systematic risk and timescales," Quantitative Finance, Taylor & Francis Journals, vol. 3(2), pages 108-116.
    7. Paolo Giudici & Gloria Polinesi & Alessandro Spelta, 2022. "Network models to improve robot advisory portfolios," Annals of Operations Research, Springer, vol. 313(2), pages 965-989, June.
    8. Antonis A. Michis, 2022. "Multiscale Partial Correlation Clustering of Stock Market Returns," JRFM, MDPI, vol. 15(1), pages 1-22, January.
    9. Fabozzi, Frank J. & Francis, Jack Clark, 1978. "Beta as a Random Coefficient," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 13(1), pages 101-116, March.
    10. N. Groenewold & P. Fraser, 1997. "Time-varying betas & macroeconomic influences," Economics Discussion / Working Papers 97-09, The University of Western Australia, Department of Economics.
    11. Yajie Yang & Longfeng Zhao & Lin Chen & Chao Wang & Jihui Han, 2021. "Portfolio optimization with idiosyncratic and systemic risks for financial networks," Papers 2111.11286, arXiv.org.
    12. Gian Paolo Clemente & Rosanna Grassi & Asmerilda Hitaj, 2021. "Asset allocation: new evidence through network approaches," Annals of Operations Research, Springer, vol. 299(1), pages 61-80, April.
    13. 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.
    14. 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.
    15. Luís Aguiar-Conraria & Maria Joana Soares, 2014. "The Continuous Wavelet Transform: Moving Beyond Uni- And Bivariate Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 28(2), pages 344-375, April.
    16. Kang Hua Cao & Chi-Keung Woo & Ya Li & Yun Liu, 2022. "Covid-19’s effect on the alpha and beta of a US stock Exchange Traded Fund," Applied Economics Letters, Taylor & Francis Journals, vol. 29(2), pages 123-128, January.
    17. Gencay, Ramazan & Selcuk, Faruk & Whitcher, Brandon, 2005. "Multiscale systematic risk," Journal of International Money and Finance, Elsevier, vol. 24(1), pages 55-70, February.
    18. 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.
    19. Nikolaus Hautsch & Julia Schaumburg & Melanie Schienle, 2015. "Financial Network Systemic Risk Contributions," Review of Finance, European Finance Association, vol. 19(2), pages 685-738.
    20. Seyed Alireza Athari & Ngo Thai Hung, 2022. "Time–frequency return co-movement among asset classes around the COVID-19 outbreak: portfolio implications," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 46(4), pages 736-756, October.
    21. Mustafa Hussein Abd-Alla, 2020. "COVID-19 crisis as a systematic risk: an empirical study in the egyptian stock market," Journal of Financial Studies, Institute of Financial Studies, vol. 9(5), pages 86-100, November.
    22. 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.
    23. 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.
    24. Qing He & Junyi Liu & Sizhu Wang & Jishuang Yu, 2020. "The impact of COVID-19 on stock markets," Economic and Political Studies, Taylor & Francis Journals, vol. 8(3), pages 275-288, July.
    25. Fei Ren & Ya-Nan Lu & Sai-Ping Li & Xiong-Fei Jiang & Li-Xin Zhong & Tian Qiu, 2017. "Dynamic Portfolio Strategy Using Clustering Approach," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-23, January.
    26. Al-Yahyaee, Khamis Hamed & Mensi, Walid & Rehman, Mobeen Ur & Vo, Xuan Vinh & Kang, Sang Hoon, 2020. "Do Islamic stocks outperform conventional stock sectors during normal and crisis periods? Extreme co-movements and portfolio management analysis," Pacific-Basin Finance Journal, Elsevier, vol. 62(C).
    27. Antonios K. Alexandridis & Mohammad S. Hasan, 2020. "Global financial crisis and multiscale systematic risk: Evidence from selected European stock markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 25(4), pages 518-546, October.
    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, 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.
    2. Manuel Monge & Luis A. Gil-Alana, 2020. "The Lithium Industry and Analysis of the Beta Term Structure of Oil Companies," Risks, MDPI, vol. 8(4), pages 1-17, December.
    3. Roman Mestre & Michel Terraza, 2018. "Time-Frequency varying beta estimation -a continuous wavelets approach-," Economics Bulletin, AccessEcon, vol. 38(4), pages 1796-1810.
    4. 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.
    5. 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.
    6. Masih, Mansur & Alzahrani, Mohammed & Al-Titi, Omar, 2010. "Systematic risk and time scales: New evidence from an application of wavelet approach to the emerging Gulf stock markets," International Review of Financial Analysis, Elsevier, vol. 19(1), pages 10-18, January.
    7. Bartłomiej Lisicki, 2023. "Sektorowe zróżnicowanie efektu interwału akcji spółek z GPW w dobie pandemii COVID-19," Ekonomista, Polskie Towarzystwo Ekonomiczne, issue 2, pages 174-194.
    8. Dewandaru, Ginanjar & Bacha, Obiyathulla Ismath & Masih, A. Mansur M. & Masih, Rumi, 2015. "Risk-return characteristics of Islamic equity indices: Multi-timescales analysis," Journal of Multinational Financial Management, Elsevier, vol. 29(C), pages 115-138.
    9. Hearn, Bruce, 2011. "Modelling size and liquidity in North African industrial sectors," Emerging Markets Review, Elsevier, vol. 12(1), pages 21-46, March.
    10. Rua, António & Nunes, Luis C., 2012. "A wavelet-based assessment of market risk: The emerging markets case," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(1), pages 84-92.
    11. Kang, Byoung Uk & In, Francis & Kim, Tong Suk, 2017. "Timescale betas and the cross section of equity returns: Framework, application, and implications for interpreting the Fama–French factors," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 15-39.
    12. Hasan, Md. Bokhtiar & Rashid, Md. Mamunur & Shafiullah, Muhammad & Sarker, Tapan, 2022. "How resilient are Islamic financial markets during the COVID-19 pandemic?," Pacific-Basin Finance Journal, Elsevier, vol. 74(C).
    13. Taufiq Choudhry & Hao Wu, 2008. "Forecasting ability of GARCH vs Kalman filter method: evidence from daily UK time-varying beta," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(8), pages 670-689.
    14. Maik Eisenbeiss & Goran Kauermann & Willi Semmler, 2007. "Estimating Beta-Coefficients of German Stock Data: A Non-Parametric Approach," The European Journal of Finance, Taylor & Francis Journals, vol. 13(6), pages 503-522.
    15. Mustafa Hussein Abd-Alla, 2020. "COVID-19 crisis as a systematic risk: an empirical study in the egyptian stock market," Journal of Financial Studies, Institute of Financial Studies, vol. 9(5), pages 86-100, November.
    16. Zhou, Jian, 2013. "Conditional market beta for REITs: A comparison of modeling techniques," Economic Modelling, Elsevier, vol. 30(C), pages 196-204.
    17. Fernando Vega-Gámez & Pablo J. Alonso-González, 2024. "How likely is it to beat the target at different investment horizons: an approach using compositional data in strategic portfolios," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-17, December.
    18. Ortas, E. & Salvador, M. & Moneva, J.M., 2015. "Improved beta modeling and forecasting: An unobserved component approach with conditional heteroscedastic disturbances," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 27-51.
    19. Bandi, Federico M. & Chaudhuri, Shomesh E. & Lo, Andrew W. & Tamoni, Andrea, 2021. "Spectral factor models," Journal of Financial Economics, Elsevier, vol. 142(1), pages 214-238.
    20. Don U.A. Galagedera, 2004. "A survey on risk-return analysis," Finance 0406010, University Library of Munich, Germany.

    More about this item

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G40 - Financial Economics - - Behavioral Finance - - - General

    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:hal:journl:hal-04058285. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.