IDEAS home Printed from https://ideas.repec.org/p/cte/wbrepe/9849.html
   My bibliography  Save this paper

Intraday return and volatily relationships between the IBEX 35 stock index and stock index futures markets

Author

Listed:
  • Lafuente Luengo, Juan Ángel

Abstract

This paper analyses the intraday lead and lag relationships between return and volatilities in the Ibex 35 spot and futures markets. With hourly data we jointly perform the analysis estimating a bivariate error correction model. with GARCH perturbations, which captures stochastically the presence of an intraday U shaped curve for both spot and futures volatility. Consistent with previous studies for U .S., our findings show an unidirectional causal relationship from the futures to spot market, both in returns and volatilities. This empirical pattern suggests that futures markets leads spot market to incorporate the arrival of new information

Suggested Citation

  • Lafuente Luengo, Juan Ángel, 2000. "Intraday return and volatily relationships between the IBEX 35 stock index and stock index futures markets," DEE - Working Papers. Business Economics. WB 9849, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
  • Handle: RePEc:cte:wbrepe:9849
    as

    Download full text from publisher

    File URL: https://e-archivo.uc3m.es/bitstream/handle/10016/9849/wb0002.pdf?sequence=1
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Abhay H. Abhyankar, 1995. "Return and volatility dynamics in the FT‐SE 100 stock index and stock index futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 15(4), pages 457-488, June.
    2. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    3. Robert T. Daigler, 1997. "Intraday futures volatility and theories of market behavior," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 17(1), pages 45-74, February.
    4. Kawaller, Ira G & Koch, Paul D & Koch, Timothy W, 1987. "The Temporal Price Relationship between S&P 500 Futures and the S and P 500 Index," Journal of Finance, American Finance Association, vol. 42(5), pages 1309-1329, December.
    5. Garman, Mark B & Klass, Michael J, 1980. "On the Estimation of Security Price Volatilities from Historical Data," The Journal of Business, University of Chicago Press, vol. 53(1), pages 67-78, January.
    6. Yoshio Iihara & Kiyoshi Kato & Toshifumi Tokunaga, 1996. "Intraday return dynamics between the cash and the futures markets in Japan," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 16(2), pages 147-162, April.
    7. Chan, Kalok & Chan, K C & Karolyi, G Andrew, 1991. "Intraday Volatility in the Stock Index and Stock Index Futures Markets," The Review of Financial Studies, Society for Financial Studies, vol. 4(4), pages 657-684.
    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. Lafuente, Juan A. & Novales, Alfonso, 2003. "Optimal hedging under departures from the cost-of-carry valuation: Evidence from the Spanish stock index futures market," Journal of Banking & Finance, Elsevier, vol. 27(6), pages 1053-1078, June.
    2. Huo, Rui & Ahmed, Abdullahi D., 2018. "Relationships between Chinese stock market and its index futures market: Evaluating the impact of QFII scheme," Research in International Business and Finance, Elsevier, vol. 44(C), pages 135-152.
    3. Antonios Antoniou & Gioia Pescetto & Antonis Violaris, 2003. "Modelling International Price Relationships and Interdependencies Between the Stock Index and Stock Index Futures Markets of Three EU Countries: A Multivariate Analysis," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 30(5‐6), pages 645-667, June.
    4. Mustafa Okur & Emrah Cevik, 2013. "Testing Intraday Volatility Spillovers in Turkish Capital Markets: Evidence from Ise," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 26(3), pages 99-116, January.
    5. Lepone, Andrew & Yang, Jin Young, 2013. "Informational role of market makers: The case of exchange traded CFDs," Journal of Empirical Finance, Elsevier, vol. 23(C), pages 84-92.
    6. Antonakakis, Nikolaos & Floros, Christos & Kizys, Renatas, 2016. "Dynamic spillover effects in futures markets: UK and US evidence," International Review of Financial Analysis, Elsevier, vol. 48(C), pages 406-418.
    7. Wen-Hsiu Kuo & Hsinan Hsu & Min-Hsien Chiang, 2008. "Foreign investment, regulation, volatility spillovers between the futures and spot markets: evidence from Taiwan," Applied Financial Economics, Taylor & Francis Journals, vol. 18(5), pages 421-430.
    8. Tse, Yiuman, 1998. "International transmission of information: evidence from the Euroyen and Eurodollar futures markets," Journal of International Money and Finance, Elsevier, vol. 17(6), pages 909-929, December.
    9. C. Kailash P. & К. Прадхам Ч., 2017. "Движение цен на спотовых и фьючерсных рынках: Подтверждение индексами S&P CNX NIFTY // Price movements in futures and spot markets: Evidence from the S&P CNX Nifty Index," Review of Business and Economics Studies // Review of Business and Economics Studies, Финансовый Университет // Financial University, vol. 5(1), pages 32-41.
    10. Minho Kim & Andrew C. Szakmary & Thomas V. Schwarz, 1999. "Trading costs and price discovery across stock index futures and cash markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 19(4), pages 475-498, June.
    11. Chen, Cathy W.S. & Gerlach, Richard & Hwang, Bruce B.K. & McAleer, Michael, 2012. "Forecasting Value-at-Risk using nonlinear regression quantiles and the intra-day range," International Journal of Forecasting, Elsevier, vol. 28(3), pages 557-574.
    12. Nikkin L. Beronilla & Dennis S. Mapa, 2008. "Range-based models in estimating value-at-risk (VaR)," Philippine Review of Economics, University of the Philippines School of Economics and Philippine Economic Society, vol. 45(2), pages 87-99, December.
    13. Gerlach, Richard & Wang, Chao, 2020. "Semi-parametric dynamic asymmetric Laplace models for tail risk forecasting, incorporating realized measures," International Journal of Forecasting, Elsevier, vol. 36(2), pages 489-506.
    14. Enrique Ter Horst & Abel Rodriguez & Henryk Gzyl & German Molina, 2012. "Stochastic volatility models including open, close, high and low prices," Quantitative Finance, Taylor & Francis Journals, vol. 12(2), pages 199-212, May.
    15. Poshakwale, Sunil S. & Aquino, Katty Pérez, 2008. "The dynamics of volatility transmission and information flow between ADRs and their underlying stocks," Global Finance Journal, Elsevier, vol. 19(2), pages 187-201.
    16. Gonzalo Cortazar & Alejandro Bernales & Diether Beuermann, 2005. "Methodology and Implementation of Value-at-Risk Measures in Emerging Fixed-Income Markets with Infrequent Trading," Finance 0512030, University Library of Munich, Germany.
    17. Marcin Fałdziński & Piotr Fiszeder & Witold Orzeszko, 2020. "Forecasting Volatility of Energy Commodities: Comparison of GARCH Models with Support Vector Regression," Energies, MDPI, vol. 14(1), pages 1-18, December.
    18. Okorie, David Iheke & Lin, Boqiang, 2023. "Cryptocurrency spectrum and 2020 pandemic: Contagion analysis," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 29-38.
    19. Nelson, Daniel B., 1996. "Asymptotic filtering theory for multivariate ARCH models," Journal of Econometrics, Elsevier, vol. 71(1-2), pages 1-47.
    20. Ioannis A. Tampakoudis & Demetres N. Subeniotis & Ioannis G. Kroustalis, 2012. "Modelling volatility during the current financial crisis: an empirical analysis of the US and the UK stock markets," International Journal of Trade and Global Markets, Inderscience Enterprises Ltd, vol. 5(3/4), pages 171-194.

    More about this item

    Keywords

    Futures;

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    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:cte:wbrepe:9849. 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: Ana Poveda (email available below). General contact details of provider: http://www.business.uc3m.es/es/index .

    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.