IDEAS home Printed from https://ideas.repec.org/a/wsi/ijmpcx/v18y2007i07ns0129183107011261.html
   My bibliography  Save this article

Why Does The Standard Garch(1, 1) Model Work Well?

Author

Listed:
  • G. R. JAFARI

    (Department of Physics, Shahid Beheshti University, Evin, Tehran 19839, Iran;
    Department of Nano-Science, IPM, P. O. Box 19395-5531, Tehran, Iran)

  • A. BAHRAMINASAB

    (Department of Physics, Lancaster University, Lancaster LA1 4YB, United Kingdom;
    The Abdus Salam International Center for Theoretical Physics (ICTP), Strada Costiera 11, I-34100 Trieste, Italy)

  • P. NOROUZZADEH

    (Department of Physics, University of Antwerp, Groenenborgerlaan 171, B-2020 Antwerpen, Belgium)

Abstract

The AutoRegressive Conditional Heteroskedasticity (ARCH) and its generalized version (GARCH) family of models have grown to encompass a wide range of specifications, each of them is designed to enhance the ability of the model to capture the characteristics of stochastic data, such as financial time series. The existing literature provides little guidance on how to select optimal parameters, which are critical in efficiency of the model, among the infinite range of available parameters. We introduce a new criterion to find suitable parameters in GARCH models by using Markov length, which is the minimum time interval over which the data can be considered as constituting a Markov process. This criterion is applied to various time series and its results support the known idea that GARCH(1, 1) model works well.

Suggested Citation

  • G. R. Jafari & A. Bahraminasab & P. Norouzzadeh, 2007. "Why Does The Standard Garch(1, 1) Model Work Well?," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 18(07), pages 1223-1230.
    • Handle: RePEc:wsi:ijmpcx:v:18:y:2007:i:07:n:s0129183107011261
    DOI: 10.1142/S0129183107011261
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0129183107011261
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S0129183107011261?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. Higgs, Robert, 1990. "Markets in History: Economic Studies of the Past. Edited byDavid W. Galenson · New York: Cambridge University Press, 1990. xiv + 354 pp. Charts, tables, notes, references, and index. Cloth, $39.50; pa," Business History Review, Cambridge University Press, vol. 64(1), pages 187-189, April.
    2. West, Kenneth D. & Cho, Dongchul, 1995. "The predictive ability of several models of exchange rate volatility," Journal of Econometrics, Elsevier, vol. 69(2), pages 367-391, October.
    3. Perez, A.A, 2001. "Comment on “On the multinomial logic model” [Physica A 269 (1999) 9–15]," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 289(3), pages 606-606.
    4. Goodhart, C. A. E. & Figliuoli, L., 1991. "Every minute counts in financial markets," Journal of International Money and Finance, Elsevier, vol. 10(1), pages 23-52, March.
    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. da Cunha, C.R. & da Silva, R., 2020. "Relevant stylized facts about bitcoin: Fluctuations, first return probability, and natural phenomena," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
    2. Un, Kuok Sin & Ausloos, Marcel, 2022. "Equity premium prediction: Taking into account the role of long, even asymmetric, swings in stock market behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).
    3. Park, Jungyeon & Alvarenga, Estêvão & Jeon, Jooyoung & Li, Ran & Petropoulos, Fotios & Kim, Hokyun & Ahn, Kwangwon, 2024. "Probabilistic forecast-based portfolio optimization of electricity demand at low aggregation levels," Applied Energy, Elsevier, vol. 353(PB).
    4. Shafiqah Azman & Dharini Pathmanathan & Aerambamoorthy Thavaneswaran, 2022. "Forecasting the Volatility of Cryptocurrencies in the Presence of COVID-19 with the State Space Model and Kalman Filter," Mathematics, MDPI, vol. 10(17), pages 1-15, September.
    5. Amir H Shirazi & Mohammad R Raoufy & Haleh Ebadi & Michele De Rui & Sami Schiff & Roham Mazloom & Sohrab Hajizadeh & Shahriar Gharibzadeh & Ahmad R Dehpour & Piero Amodio & G Reza Jafari & Sara Montag, 2013. "Quantifying Memory in Complex Physiological Time-Series," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-8, September.

    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. Woerner Jeannette H. C., 2003. "Variational sums and power variation: a unifying approach to model selection and estimation in semimartingale models," Statistics & Risk Modeling, De Gruyter, vol. 21(1), pages 47-68, January.
    2. Richard K. Lyons, 1996. "Foreign Exchange Volume: Sound and Fury Signifying Nothing?," NBER Chapters, in: The Microstructure of Foreign Exchange Markets, pages 183-208, National Bureau of Economic Research, Inc.
    3. Rouhang Chen & Bing Qiu & Chaoying Zhang & Lingjiang Kong & Muren Liu, 2007. "A Study On The Evacuation Of People In A Hall Using The Cellular Automaton Model," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 18(03), pages 359-367.
    4. Mittnik, Stefan & Robinzonov, Nikolay & Spindler, Martin, 2015. "Stock market volatility: Identifying major drivers and the nature of their impact," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 1-14.
    5. Stephan Schulmeister, 2000. "Technical Analysis and Exchange Rate Dynamics," WIFO Studies, WIFO, number 25857, April.
    6. Bing Qiu & Huili Tan & Chaoying Zhang & Lingjiang Kong & Muren Liu, 2005. "Cellular Automaton Simulation Of The Escaping Pedestrian Flow In Corridor," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 16(02), pages 225-235.
    7. Novkovska, Blagica & Serafimovic, Gordana, 2018. "Recognizing The Vulnerability Of Generation Z To Economic And Social Risks," UTMS Journal of Economics, University of Tourism and Management, Skopje, Macedonia, vol. 9(1), pages 29-37.
    8. de Goeij, Peter & Marquering, Wessel, 2009. "Stock and bond market interactions with level and asymmetry dynamics: An out-of-sample application," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 318-329, March.
    9. Christopher J. Neely & Brett W. Fawley, 2012. "Capital Flows And Japanese Asset Volatility," Pacific Economic Review, Wiley Blackwell, vol. 17(3), pages 391-414, August.
    10. Huang, Alex YiHou & Peng, Sheng-Pen & Li, Fangjhy & Ke, Ching-Jie, 2011. "Volatility forecasting of exchange rate by quantile regression," International Review of Economics & Finance, Elsevier, vol. 20(4), pages 591-606, October.
    11. Funke, Michael & Shu, Chang & Cheng, Xiaoqiang & Eraslan, Sercan, 2015. "Assessing the CNH–CNY pricing differential: Role of fundamentals, contagion and policy," Journal of International Money and Finance, Elsevier, vol. 59(C), pages 245-262.
    12. Tetsuya Takaishi, 2005. "Simulations Of Financial Markets In A Potts-Like Model," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 16(08), pages 1311-1317.
    13. West, Kenneth D., 2006. "Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 3, pages 99-134, Elsevier.
    14. Xiufeng Yan, 2021. "Autoregressive conditional duration modelling of high frequency data," Papers 2111.02300, arXiv.org.
    15. Fan Jia & Di Xie, 2011. "Dempster–Shafer Evidence Theory-Based Updating Rule For Continuous Opinions And Discrete Actions," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 22(06), pages 595-606.
    16. Annina Kaltenbrunner & Machiko Nissanke, 2009. "The Case for an Intermediate Exchange Rate Regime with Endogenizing Market Structures and Capital Mobility: The Empirical Study of Brazil," WIDER Working Paper Series RP2009-29, World Institute for Development Economic Research (UNU-WIDER).
    17. Bretó, Carles & Veiga, Helena, 2011. "Forecasting volatility: does continuous time do better than discrete time?," DES - Working Papers. Statistics and Econometrics. WS ws112518, Universidad Carlos III de Madrid. Departamento de Estadística.
    18. Degiannakis, Stavros & Xekalaki, Evdokia, 2007. "Assessing the Performance of a Prediction Error Criterion Model Selection Algorithm in the Context of ARCH Models," MPRA Paper 96324, University Library of Munich, Germany.
    19. Li, Gang & Li, Yong, 2015. "Forecasting copper futures volatility under model uncertainty," Resources Policy, Elsevier, vol. 46(P2), pages 167-176.
    20. Chelley-Steeley, Patricia L. & Tsorakidis, Nikos, 2013. "Bid-ask spread dynamics in foreign exchange markets," International Review of Financial Analysis, Elsevier, vol. 29(C), pages 119-131.

    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:wsi:ijmpcx:v:18:y:2007:i:07:n:s0129183107011261. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/ijmpc/ijmpc.shtml .

    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.