IDEAS home Printed from https://ideas.repec.org/a/spr/snbeco/v1y2021i6d10.1007_s43546-021-00080-7.html
   My bibliography  Save this article

Asymmetric dependence of intraday frequency components in the Brazilian stock market

Author

Listed:
  • Marcela de Marillac Carvalho

    (Federal University of Lavras)

  • Luiz Otávio de Oliveira Pala

    (Federal University of Lavras)

  • Gabriel Rodrigo Gomes Pessanha

    (Federal University of Alfenas)

  • Thelma Sáfadi

    (Federal University of Lavras)

Abstract

The multivariate dependence plays an important role in financial instrument management. Due to the inherent characteristics in the financial market, such as heavy tails in the returns unconditional distribution and asymmetry between gain and loss, we obtained the asymmetric dependence structure in different short-term variation scales based on the wavelet technique MODWT. The study sought to capture the relations between financial returns represented by its frequency components. Intraday returns series was used in the 15-min sampling interval from stocks and applied the D-Vine pair-copula to decompose in trade frequencies of 15 min, 1 h, 1 day, and 1 week with margin adjustments of ARIMA-APARCH class and BB7 copula function, responsible for measuring the dependence on tails. The results indicated the prevalence of a high dependence during market upturns, rising over the analyzed frequencies. Being an important tool in financial management and allowing short-term strategies of diversification.

Suggested Citation

  • Marcela de Marillac Carvalho & Luiz Otávio de Oliveira Pala & Gabriel Rodrigo Gomes Pessanha & Thelma Sáfadi, 2021. "Asymmetric dependence of intraday frequency components in the Brazilian stock market," SN Business & Economics, Springer, vol. 1(6), pages 1-18, June.
    • Handle: RePEc:spr:snbeco:v:1:y:2021:i:6:d:10.1007_s43546-021-00080-7
    DOI: 10.1007/s43546-021-00080-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s43546-021-00080-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s43546-021-00080-7?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. Sun, Edward W. & Rezania, Omid & Rachev, Svetlozar T. & Fabozzi, Frank J., 2011. "Analysis of the intraday effects of economic releases on the currency market," Journal of International Money and Finance, Elsevier, vol. 30(4), pages 692-707, June.
    2. Billio, Monica & Getmansky, Mila & Lo, Andrew W. & Pelizzon, Loriana, 2012. "Econometric measures of connectedness and systemic risk in the finance and insurance sectors," Journal of Financial Economics, Elsevier, vol. 104(3), pages 535-559.
    3. Andrew J. Patton, 2004. "On the Out-of-Sample Importance of Skewness and Asymmetric Dependence for Asset Allocation," Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 130-168.
    4. Nikoloulopoulos, Aristidis K. & Joe, Harry & Li, Haijun, 2012. "Vine copulas with asymmetric tail dependence and applications to financial return data," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3659-3673.
    5. Bartels, Mariana & Ziegelmann, Flavio A., 2016. "Market risk forecasting for high dimensional portfolios via factor copulas with GAS dynamics," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 66-79.
    6. Chang, Shao-Chi & Chen, Sheng-Syan & Chou, Robin K. & Lin, Yueh-Hsiang, 2008. "Weather and intraday patterns in stock returns and trading activity," Journal of Banking & Finance, Elsevier, vol. 32(9), pages 1754-1766, September.
    7. Kakouris, Iakovos & Rustem, Berç, 2014. "Robust portfolio optimization with copulas," European Journal of Operational Research, Elsevier, vol. 235(1), pages 28-37.
    8. Schulmeister, Stephan, 2009. "Profitability of technical stock trading: Has it moved from daily to intraday data?," Review of Financial Economics, Elsevier, vol. 18(4), pages 190-201, October.
    9. Marco Gallegati & Willi Semmler (ed.), 2014. "Wavelet Applications in Economics and Finance," Dynamic Modeling and Econometrics in Economics and Finance, Springer, edition 127, number 978-3-319-07061-2, July-Dece.
    10. Aas, Kjersti & Czado, Claudia & Frigessi, Arnoldo & Bakken, Henrik, 2009. "Pair-copula constructions of multiple dependence," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 182-198, April.
    11. Joe, Harry & Li, Haijun & Nikoloulopoulos, Aristidis K., 2010. "Tail dependence functions and vine copulas," Journal of Multivariate Analysis, Elsevier, vol. 101(1), pages 252-270, January.
    12. Yue Peng & Wing Ng, 2012. "Analysing financial contagion and asymmetric market dependence with volatility indices via copulas," Annals of Finance, Springer, vol. 8(1), pages 49-74, February.
    13. 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.
    14. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
    15. Xiaojie Xu, 2018. "Intraday price information flows between the CSI300 and futures market: an application of wavelet analysis," Empirical Economics, Springer, vol. 54(3), pages 1267-1295, May.
    16. Chakrabarty, Anindya & De, Anupam & Gunasekaran, Angappa & Dubey, Rameshwar, 2015. "Investment horizon heterogeneity and wavelet: Overview and further research directions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 429(C), pages 45-61.
    17. Anthony Hatherley & Jamie Alcock, 2007. "Portfolio construction incorporating asymmetric dependence structures: a user's guide," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 47(3), pages 447-472, September.
    18. Biage, Milton, 2019. "Analysis of shares frequency components on daily value-at-risk in emerging and developed markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 532(C).
    19. Patrick M. Crowley, 2007. "A Guide To Wavelets For Economists," Journal of Economic Surveys, Wiley Blackwell, vol. 21(2), pages 207-267, April.
    20. Ibragimov, Rustam & Jaffee, Dwight & Walden, Johan, 2011. "Diversification disasters," Journal of Financial Economics, Elsevier, vol. 99(2), pages 333-348, February.
    21. Chollete, Lorán & de la Peña, Victor & Lu, Ching-Chih, 2011. "International diversification: A copula approach," Journal of Banking & Finance, Elsevier, vol. 35(2), pages 403-417, February.
    22. Jammazi, Rania & Reboredo, Juan C., 2016. "Dependence and risk management in oil and stock markets. A wavelet-copula analysis," Energy, Elsevier, vol. 107(C), pages 866-888.
    23. Ibrahim Ergen, 2014. "Tail dependence and diversification benefits in emerging market stocks: an extreme value theory approach," Applied Economics, Taylor & Francis Journals, vol. 46(19), pages 2215-2227, July.
    24. Yannick Malevergne & Didier Sornette, 2006. "Extreme Financial Risks : From Dependence to Risk Management," Post-Print hal-02298069, HAL.
    25. Osvaldo C. Silva Filho & Flavio A. Ziegelmann & Michael J. Dueker, 2014. "Assessing dependence between financial market indexes using conditional time-varying copulas: applications to Value at Risk (VaR)," Quantitative Finance, Taylor & Francis Journals, vol. 14(12), pages 2155-2170, December.
    26. Mendes, Beatriz Vaz de Melo & Accioly, Victor Bello, 2012. "On the dependence structure of realized volatilities," International Review of Financial Analysis, Elsevier, vol. 22(C), pages 1-9.
    27. Jondeau, Eric, 2016. "Asymmetry in tail dependence in equity portfolios," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 351-368.
    28. Righi, Marcelo Brutti & Ceretta, Paulo Sergio, 2013. "Analyzing the dependence structure of various sectors in the Brazilian market: A Pair Copula Construction approach," Economic Modelling, Elsevier, vol. 35(C), pages 199-206.
    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. Sleire, Anders D. & Støve, Bård & Otneim, Håkon & Berentsen, Geir Drage & Tjøstheim, Dag & Haugen, Sverre Hauso, 2022. "Portfolio allocation under asymmetric dependence in asset returns using local Gaussian correlations," Finance Research Letters, Elsevier, vol. 46(PB).
    2. Zhou, Wei & Chen, Yan & Chen, Jin, 2022. "Risk spread in multiple energy markets: Extreme volatility spillover network analysis before and during the COVID-19 pandemic," Energy, Elsevier, vol. 256(C).
    3. Ojea-Ferreiro, Javier & Reboredo, Juan C., 2022. "Exchange rates and the global transmission of equity market shocks," Economic Modelling, Elsevier, vol. 114(C).
    4. Han, Xuyuan & Liu, Zhenya & Wang, Shixuan, 2022. "An R-vine copula analysis of non-ferrous metal futures with application in Value-at-Risk forecasting," Journal of Commodity Markets, Elsevier, vol. 25(C).
    5. Reboredo, Juan C. & Ugolini, Andrea, 2015. "Downside/upside price spillovers between precious metals: A vine copula approach," The North American Journal of Economics and Finance, Elsevier, vol. 34(C), pages 84-102.
    6. Rand Kwong Yew Low, 2018. "Vine copulas: modelling systemic risk and enhancing higher‐moment portfolio optimisation," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(S1), pages 423-463, November.
    7. Maziar Sahamkhadam, 2021. "Dynamic copula-based expectile portfolios," Journal of Asset Management, Palgrave Macmillan, vol. 22(3), pages 209-223, May.
    8. Fantazzini, Dean, 2011. "Analysis of multidimensional probability distributions with copula functions," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 22(2), pages 98-134.
    9. Koliai, Lyes, 2016. "Extreme risk modeling: An EVT–pair-copulas approach for financial stress tests," Journal of Banking & Finance, Elsevier, vol. 70(C), pages 1-22.
    10. Yuri Salazar & Wing Ng, 2015. "Nonparametric estimation of general multivariate tail dependence and applications to financial time series," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(1), pages 121-158, March.
    11. Pavel Krupskii & Harry Joe, 2015. "Tail-weighted measures of dependence," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(3), pages 614-629, March.
    12. Mensah, Jones Odei & Premaratne, Gamini, 2014. "Dependence patterns among Banking Sectors in Asia: A Copula Approach," MPRA Paper 60119, University Library of Munich, Germany.
    13. Zhichao Zhang & Li Ding & Fan Zhang & Zhuang Zhang, 2015. "Optimal Currency Composition for China's Foreign Reserves: A Copula Approach," The World Economy, Wiley Blackwell, vol. 38(12), pages 1947-1965, December.
    14. Low, Rand Kwong Yew & Alcock, Jamie & Faff, Robert & Brailsford, Timothy, 2013. "Canonical vine copulas in the context of modern portfolio management: Are they worth it?," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3085-3099.
    15. Holger Fink & Yulia Klimova & Claudia Czado & Jakob Stober, 2016. "Regime switching vine copula models for global equity and volatility indices," Papers 1604.05598, arXiv.org.
    16. Hua, Lei & Joe, Harry, 2014. "Strength of tail dependence based on conditional tail expectation," Journal of Multivariate Analysis, Elsevier, vol. 123(C), pages 143-159.
    17. Cerrato, Mario & Crosby, John & Kim, Minjoo & Zhao, Yang, 2015. "US Monetary and Fiscal Policies - Conflict or Cooperation?," 2007 Annual Meeting, July 29-August 1, 2007, Portland, Oregon TN 2015-78, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    18. Hua, Lei & Joe, Harry, 2012. "Tail comonotonicity: Properties, constructions, and asymptotic additivity of risk measures," Insurance: Mathematics and Economics, Elsevier, vol. 51(2), pages 492-503.
    19. Krupskii, Pavel & Joe, Harry, 2013. "Factor copula models for multivariate data," Journal of Multivariate Analysis, Elsevier, vol. 120(C), pages 85-101.
    20. Mo, Guoli & Zhang, Weiguo & Tan, Chunzhi & Liu, Xing, 2022. "Predicting the portfolio risk of high-dimensional international stock indices with dynamic spatial dependence," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).

    More about this item

    Keywords

    Multivariate dependence; Financial returns; Copulas; Wavelets; High frequency;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

    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:spr:snbeco:v:1:y:2021:i:6:d:10.1007_s43546-021-00080-7. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.