IDEAS home Printed from https://ideas.repec.org/a/taf/applec/v35y2003i7p791-801.html
   My bibliography  Save this article

Using monthly returns to model conditional heteroscedasticity

Author

Listed:
  • Nathan Lael Joseph

Abstract

This empirical study examines the extent of non-linearity in a multivariate model of monthly financial series. To capture the conditional heteroscedasticity in the series, both the GARCH(1,1) and GARCH(1,1)-in-mean models are employed. The conditional errors are assumed to follow the normal and Student- t distributions. The non-linearity in the residuals of a standard OLS regression are also assessed. It is found that the OLS residuals as well as conditional errors of the GARCH models exhibit strong non-linearity. Under the Student density, the extent of non-linearity in the GARCH conditional errors was generally similar to those of the standard OLS. The GARCH-in-mean regression generated the worse out-of-sample forecasts.

Suggested Citation

  • Nathan Lael Joseph, 2003. "Using monthly returns to model conditional heteroscedasticity," Applied Economics, Taylor & Francis Journals, vol. 35(7), pages 791-801.
    • Handle: RePEc:taf:applec:v:35:y:2003:i:7:p:791-801
    DOI: 10.1080/0003684021000088536
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/0003684021000088536
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/0003684021000088536?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. Philip Hans Franses & Paul van Homelen, 1998. "On forecasting exchange rates using neural networks," Applied Financial Economics, Taylor & Francis Journals, vol. 8(6), pages 589-596.
    2. McFarland, James W & Pettit, R Richardson & Sung, Sam K, 1982. "The Distribution of Foreign Exchange Price Changes: Trading Day Effects and Risk Measurement," Journal of Finance, American Finance Association, vol. 37(3), pages 693-715, June.
    3. Baillie, Richard T & Bollerslev, Tim, 2002. "The Message in Daily Exchange Rates: A Conditional-Variance Tale," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 60-68, January.
    4. Hsieh, David A, 1989. "Testing for Nonlinear Dependence in Daily Foreign Exchange Rates," The Journal of Business, University of Chicago Press, vol. 62(3), pages 339-368, July.
    5. Engle, Robert F & Ng, Victor K, 1993. "Measuring and Testing the Impact of News on Volatility," Journal of Finance, American Finance Association, vol. 48(5), pages 1749-1778, December.
    6. Elyasiani, Elyas & Mansur, Iqbal, 1998. "Sensitivity of the bank stock returns distribution to changes in the level and volatility of interest rate: A GARCH-M model," Journal of Banking & Finance, Elsevier, vol. 22(5), pages 535-563, May.
    7. Franses Philip Hans & van Griensven Kasper, 1998. "Forecasting Exchange Rates Using Neural Networks for Technical Trading Rules," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 2(4), pages 1-8, January.
    8. Franses, Philip Hans & Ghijsels, Hendrik, 1999. "Additive outliers, GARCH and forecasting volatility," International Journal of Forecasting, Elsevier, vol. 15(1), pages 1-9, February.
    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. Geoff Willcocks, 2009. "UK Housing Market: Time Series Processes with Independent and Identically Distributed Residuals," The Journal of Real Estate Finance and Economics, Springer, vol. 39(4), pages 403-414, November.
    2. Ching-Chung Lin & Min-Hsien Chiang, 2005. "Volatility effect of ETFs on the constituents of the underlying Taiwan 50 Index," Applied Financial Economics, Taylor & Francis Journals, vol. 15(18), pages 1315-1322.
    3. Chung-Hua Shen & Shyh-Wei Chen & Chien-Fu Chen, 2010. "The dual characteristics of closed-end country funds: the role of risk," Applied Economics, Taylor & Francis Journals, vol. 42(8), pages 1003-1013.
    4. Mazouz, Khelifa & Bowe, Michael, 2006. "The volatility effect of futures trading: Evidence from LSE traded stocks listed as individual equity futures contracts on LIFFE," International Review of Financial Analysis, Elsevier, vol. 15(1), pages 1-20.
    5. Mojisola Olugbode & Ahmed El-Masry & John Pointon, 2014. "Exchange Rate and Interest Rate Exposure of UK Industries Using First-order Autoregressive Exponential GARCH-in-mean (EGARCH-M) Approach," Manchester School, University of Manchester, vol. 82(4), pages 409-464, July.
    6. Bangassa, Kenbata & Su, Chen & Joseph, Nathan L., 2012. "Selectivity and timing performance of UK investment trusts," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(5), pages 1149-1175.

    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. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    2. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654.
    3. Marcos Álvarez-Díaz & Alberto Álvarez, 2002. "Predicción No-Lineal De Tipos De Cambio: Algoritmos Genéticos, Redes Neuronales Y Fusión De Datos," Working Papers 0205, Universidade de Vigo, Departamento de Economía Aplicada.
    4. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.
    5. Marcos Álvarez-Díaz & Shawkat Hammoudeh & Rangan Gupta, 2013. "Detecting Predictable Non-linear Dynamics in Dow Jones Industrial Average and Dow Jones Islamic Market Indices using Nonparametric Regressions," Working Papers 201385, University of Pretoria, Department of Economics.
    6. Han, Young Wook, 2007. "High frequency perspective on jump process, long memory property and temporal aggregation: Case of $-AUD exchange rates," Japan and the World Economy, Elsevier, vol. 19(2), pages 248-262, March.
    7. Charles, Amelie & Darne, Olivier, 2006. "Large shocks and the September 11th terrorist attacks on international stock markets," Economic Modelling, Elsevier, vol. 23(4), pages 683-698, July.
    8. Amélie Charles, 2008. "Forecasting volatility with outliers in GARCH models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(7), pages 551-565.
    9. Font, Begoña, 1998. "Modelización de series temporales financieras. Una recopilación," DES - Documentos de Trabajo. Estadística y Econometría. DS 3664, Universidad Carlos III de Madrid. Departamento de Estadística.
    10. Kocenda, Evzen, 1998. "Exchange rate in transition," MPRA Paper 32030, University Library of Munich, Germany.
    11. Kian Teng Kwek & Kuan Nee Koay, 2006. "Exchange rate volatility and volatility asymmetries: an application to finding a natural dollar currency," Applied Economics, Taylor & Francis Journals, vol. 38(3), pages 307-323.
    12. Thierry Warin & Aleksandar Stojkov, 2021. "Machine Learning in Finance: A Metadata-Based Systematic Review of the Literature," JRFM, MDPI, vol. 14(7), pages 1-31, July.
    13. Marcos Álvarez-Díaz & Alberto Álvarez, 2003. "Predicción No-Lineal De Tipos De Cambio: Algoritmos Genéticos, Redes Neuronales Y Fusión De Datos," Working Papers 0301, Universidade de Vigo, Departamento de Economía Aplicada.
    14. Menelaos Karanasos & J. Kim, "undated". "Alternative GARCH in Mean Models: An Application to the Korean Stock Market," Discussion Papers 00/25, Department of Economics, University of York.
    15. Noori, Mohammad & Hitaj, Asmerilda, 2023. "Dissecting hedge funds' strategies," International Review of Financial Analysis, Elsevier, vol. 85(C).
    16. Grané, Aurea & Veiga, Helena, 2010. "Outliers in Garch models and the estimation of risk measures," DES - Working Papers. Statistics and Econometrics. WS ws100502, Universidad Carlos III de Madrid. Departamento de Estadística.
    17. Joseph P. Byrne & E. Philip Davis, 2005. "Investment and Uncertainty in the G7," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 141(1), pages 1-32, April.
    18. Ibrahim Chowdhury & Lucio Sarno, 2004. "Time‐Varying Volatility in the Foreign Exchange Market: New Evidence on its Persistence and on Currency Spillovers," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 31(5‐6), pages 759-793, June.
    19. Fidrmuc, Jarko & Horváth, Roman, 2008. "Volatility of exchange rates in selected new EU members: Evidence from daily data," Economic Systems, Elsevier, vol. 32(1), pages 103-118, March.
    20. Kanungo, Rama Prasad, 2021. "Uncertainty of M&As under asymmetric estimation," Journal of Business Research, Elsevier, vol. 122(C), pages 774-793.

    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:applec:v:35:y:2003:i:7:p:791-801. 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/RAEC20 .

    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.