IDEAS home Printed from https://ideas.repec.org/a/oup/jfinec/v19y2021i4p707-745..html
   My bibliography  Save this article

Time-Varying Coefficient Estimation in SURE Models. Application to Portfolio Management

Author

Listed:
  • Isabel Casas
  • Eva Ferreira
  • Susan Orbe

Abstract

This paper provides a detailed analysis of the asymptotic properties of a kernel estimator for a seemingly unrelated regression equations model with time-varying coefficients (tv-SURE) under general conditions. Theoretical results together with a simulation study differentiate the cases for which the estimation of a tv-SURE outperforms the estimation of a single regression equations model with time-varying coefficients. The study shows that Zellner’s results cannot be straightforwardly extended to the time-varying case. The tv-SURE is applied to the Fama and French five-factor model using data from four different international markets. Finally, we provide the estimation under cross-restriction and discuss a testing procedure.

Suggested Citation

  • Isabel Casas & Eva Ferreira & Susan Orbe, 2021. "Time-Varying Coefficient Estimation in SURE Models. Application to Portfolio Management," Journal of Financial Econometrics, Oxford University Press, vol. 19(4), pages 707-745.
  • Handle: RePEc:oup:jfinec:v:19:y:2021:i:4:p:707-745.
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1093/jjfinec/nbz010
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

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

    Other versions of this item:

    References listed on IDEAS

    as
    1. Ang, Andrew & Kristensen, Dennis, 2012. "Testing conditional factor models," Journal of Financial Economics, Elsevier, vol. 106(1), pages 132-156.
    2. Fama, Eugene F. & French, Kenneth R., 2017. "International tests of a five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 123(3), pages 441-463.
    3. Henderson, Daniel J. & Kumbhakar, Subal C. & Li, Qi & Parmeter, Christopher F., 2015. "Smooth coefficient estimation of a seemingly unrelated regression," Journal of Econometrics, Elsevier, vol. 189(1), pages 148-162.
    4. Orbe, Susan & Ferreira, Eva & Rodriguez-Poo, Juan, 2003. "An algorithm to estimate time-varying parameter SURE models under different types of restriction," Computational Statistics & Data Analysis, Elsevier, vol. 42(3), pages 363-383, March.
    5. Tomohiro Ando & Jushan Bai, 2015. "Asset Pricing with a General Multifactor Structure," Journal of Financial Econometrics, Oxford University Press, vol. 13(3), pages 556-604.
    6. Cai, Zongwu, 2007. "Trending time-varying coefficient time series models with serially correlated errors," Journal of Econometrics, Elsevier, vol. 136(1), pages 163-188, January.
    7. Aharoni, Gil & Grundy, Bruce & Zeng, Qi, 2013. "Stock returns and the Miller Modigliani valuation formula: Revisiting the Fama French analysis," Journal of Financial Economics, Elsevier, vol. 110(2), pages 347-357.
    8. Cai, Zongwu & Li, Qi & Park, Joon Y., 2009. "Functional-coefficient models for nonstationary time series data," Journal of Econometrics, Elsevier, vol. 148(2), pages 101-113, February.
    9. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    10. Granger Clive W.J., 2008. "Non-Linear Models: Where Do We Go Next - Time Varying Parameter Models?," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(3), pages 1-11, September.
    11. Phillips, Peter C.B. & Li, Degui & Gao, Jiti, 2017. "Estimating smooth structural change in cointegration models," Journal of Econometrics, Elsevier, vol. 196(1), pages 180-195.
    12. Das, M., 2005. "Instrumental variables estimators of nonparametric models with discrete endogenous regressors," Journal of Econometrics, Elsevier, vol. 124(2), pages 335-361, February.
    13. Aretz, Kevin & Bartram, Söhnke M. & Pope, Peter F., 2010. "Macroeconomic risks and characteristic-based factor models," Journal of Banking & Finance, Elsevier, vol. 34(6), pages 1383-1399, June.
    14. Novy-Marx, Robert, 2013. "The other side of value: The gross profitability premium," Journal of Financial Economics, Elsevier, vol. 108(1), pages 1-28.
    15. Orbe, Susan & Ferreira, Eva & Rodriguez-Poo, Juan, 2005. "Nonparametric estimation of time varying parameters under shape restrictions," Journal of Econometrics, Elsevier, vol. 126(1), pages 53-77, May.
    16. M. V. Esteban & E. Ferreira & S. Orbe-Mandaluniz, 2015. "Nonparametric methods for estimating and testing for constant betas in asset pricing models," Applied Economics, Taylor & Francis Journals, vol. 47(25), pages 2577-2607, May.
    17. Cai, Zongwu & Ren, Yu & Yang, Bingduo, 2015. "A semiparametric conditional capital asset pricing model," Journal of Banking & Finance, Elsevier, vol. 61(C), pages 117-126.
    18. Ferreira, Eva & Gil-Bazo, Javier & Orbe, Susan, 2011. "Conditional beta pricing models: A nonparametric approach," Journal of Banking & Finance, Elsevier, vol. 35(12), pages 3362-3382.
    19. Eva Ferreira, 2004. "Beyond Single-Factor Affine Term Structure Models," Journal of Financial Econometrics, Oxford University Press, vol. 2(4), pages 565-591.
    20. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    21. Aslanidis, Nektarios & Casas, Isabel, 2013. "Nonparametric correlation models for portfolio allocation," Journal of Banking & Finance, Elsevier, vol. 37(7), pages 2268-2283.
    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. Dean Fantazzini & Julia Pushchelenko & Alexey Mironenkov & Alexey Kurbatskii, 2021. "Forecasting Internal Migration in Russia Using Google Trends: Evidence from Moscow and Saint Petersburg," Forecasting, MDPI, vol. 3(4), pages 1-30, October.
    2. E. Ferreira & S. Orbe & J. Ascorbebeitia & B. 'Alvarez Pereira & E. Estrada, 2021. "Loss of structural balance in stock markets," Papers 2104.06254, arXiv.org.
    3. Casas Villalba, Maria Isabel, 2020. "Adaptative predictability of stock market returns," DES - Working Papers. Statistics and Econometrics. WS 31648, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Isabel Casas & Xiuping Mao & Helena Veiga, 2018. "Reexamining financial and economic predictability with new estimators of realized variance and variance risk premium," CREATES Research Papers 2018-10, Department of Economics and Business Economics, Aarhus University.
    5. Fu, Zhonghao & Hong, Yongmiao & Su, Liangjun & Wang, Xia, 2023. "Specification tests for time-varying coefficient models," Journal of Econometrics, Elsevier, vol. 235(2), pages 720-744.
    6. Armin Pourkhanali & Jonathan Keith & Xibin Zhang, 2021. "Conditional Heteroscedasticity Models with Time-Varying Parameters: Estimation and Asymptotics," Monash Econometrics and Business Statistics Working Papers 15/21, Monash University, Department of Econometrics and Business Statistics.
    7. Loïc Maréchal, 2021. "Do economic variables forecast commodity futures volatility?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(11), pages 1735-1774, November.

    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. Isabel Casas & Xiuping Mao & Helena Veiga, 2018. "Reexamining financial and economic predictability with new estimators of realized variance and variance risk premium," CREATES Research Papers 2018-10, Department of Economics and Business Economics, Aarhus University.
    2. Casas Villalba, Maria Isabel, 2020. "Adaptative predictability of stock market returns," DES - Working Papers. Statistics and Econometrics. WS 31648, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. Henderson, Daniel J. & Kumbhakar, Subal C. & Li, Qi & Parmeter, Christopher F., 2015. "Smooth coefficient estimation of a seemingly unrelated regression," Journal of Econometrics, Elsevier, vol. 189(1), pages 148-162.
    4. Rocciolo, Francesco & Gheno, Andrea & Brooks, Chris, 2022. "Explaining abnormal returns in stock markets: An alpha-neutral version of the CAPM," International Review of Financial Analysis, Elsevier, vol. 82(C).
    5. Wahal, Sunil, 2019. "The profitability and investment premium: Pre-1963 evidence," Journal of Financial Economics, Elsevier, vol. 131(2), pages 362-377.
    6. Russell Davidson & Niels S. Grønborg, 2018. "Time-varying parameters: New test tailored to applications in finance and macroeconomics," CREATES Research Papers 2018-22, Department of Economics and Business Economics, Aarhus University.
    7. Güler ARAS & İlhan ÇAM & Bilal ZAVALSIZ & Serkan KESKİN, 2018. "Fama-French Çok Faktör Varlık Fiyatlama Modellerinin Performanslarının Karşılaştırılması: Borsa İstanbul Üzerine Bir Uygulama," Istanbul Business Research, Istanbul University Business School, vol. 47(2), pages 183-207, November.
    8. Mehmet Balcilar & Riza Demirer & Festus V. Bekun, 2021. "Flexible Time-Varying Betas in a Novel Mixture Innovation Factor Model with Latent Threshold," Mathematics, MDPI, vol. 9(8), pages 1-20, April.
    9. Doha Belimam & Yong Tan & Ghizlane Lakhnati, 2018. "An Empirical Comparison of Asset-Pricing Models in the Shanghai A-Share Exchange Market," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 25(3), pages 249-265, September.
    10. Yao, Haixiang & Xia, Shenghao & Liu, Hao, 2022. "Six-factor asset pricing and portfolio investment via deep learning: Evidence from Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 76(C).
    11. James Foye, 2018. "Testing alternative versions of the Fama–French five-factor model in the UK," Risk Management, Palgrave Macmillan, vol. 20(2), pages 167-183, May.
    12. Lianqian Yin & Qiuju Wang, 2022. "China's Green Finance Premium Anomalies Based on Factor Models," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 12(6), pages 1-4.
    13. Mamdouh Medhat & Maik Schmeling, 2022. "Short-term Momentum," The Review of Financial Studies, Society for Financial Studies, vol. 35(3), pages 1480-1526.
    14. Berggrun, Luis & Cardona, Emilio & Lizarzaburu, Edmundo, 2020. "Firm profitability and expected stock returns: Evidence from Latin America," Research in International Business and Finance, Elsevier, vol. 51(C).
    15. Sara Kelly Anzinger & Chinmoy Ghosh & Milena Petrova, 2017. "The Other Side of Value: The Effect of Quality on Price and Return in Real Estate," The Journal of Real Estate Finance and Economics, Springer, vol. 54(3), pages 429-457, April.
    16. Čížek, Pavel & Koo, Chao Hui, 2021. "Jump-preserving varying-coefficient models for nonlinear time series," Econometrics and Statistics, Elsevier, vol. 19(C), pages 58-96.
    17. Gagliardini, Patrick & Ossola, Elisa & Scaillet, Olivier, 2019. "A diagnostic criterion for approximate factor structure," Journal of Econometrics, Elsevier, vol. 212(2), pages 503-521.
    18. José Luis Miralles-Quirós & María Mar Miralles-Quirós & José Manuel Nogueira, 2020. "Sustainable Development Goals and Investment Strategies: The Profitability of Using Five-Factor Fama-French Alphas," Sustainability, MDPI, vol. 12(5), pages 1-16, February.
    19. Clarke, Charles, 2022. "The level, slope, and curve factor model for stocks," Journal of Financial Economics, Elsevier, vol. 143(1), pages 159-187.
    20. Lu Zhang, 2017. "The Investment CAPM," European Financial Management, European Financial Management Association, vol. 23(4), pages 545-603, September.

    More about this item

    Keywords

    asset pricing; five-factor model; nonparametric; SURE; time-varying;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: 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:oup:jfinec:v:19:y:2021:i:4:p:707-745.. 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: Oxford University Press (email available below). General contact details of provider: https://edirc.repec.org/data/sofieea.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.