IDEAS home Printed from https://ideas.repec.org/p/zbw/zewdip/9625.html
   My bibliography  Save this paper

Delta-neutral volatility trading with intra-day prices: an application to options on the DAX

Author

Listed:
  • Schmitt, Christian
  • Kaehler, Jürgen

Abstract

This paper evaluates the profitability of applying four different volatility forecasting models to the trading of straddles on the German stock market index DAX. Special care has been taken to use simultaneous intra-day prices and realistic transaction costs. Furthermore, straddle positions were evaluated on a daily basis to preserve delta neutrality. The four models applied in this paper are: historical volatility, two ARCH models, and an autoregressive model for the volatility index. VDAX. The ARCH models perform best in generating profits for market makers. Forecasts based on historical volatility also produce statistically and economically significant profits over the two-year simulation period of 1993 and 1994. In general, a filter1rule with a small filter of0.5 per cent produces the best results for both the ARCH models and historical volatility. However, the VDAX-AR model generates much lower and usually insignificant profits, and for some filter rules this model even has cumulative losses for market makers. For non-market-makers and non-members of exchange, however, larger transaction\costs imply that no significant profits can be gained with any model of volatility forecasts.

Suggested Citation

  • Schmitt, Christian & Kaehler, Jürgen, 1996. "Delta-neutral volatility trading with intra-day prices: an application to options on the DAX," ZEW Discussion Papers 96-25, ZEW - Leibniz Centre for European Economic Research.
    • Handle: RePEc:zbw:zewdip:9625
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/29476/1/257997660.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    2. Taehoon Kang & B. Wade Brorsen, 1995. "Conditional heteroskedasticity, asymmetry, and option pricing," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 15(8), pages 901-928, December.
    3. Schmitt, Christian, 1996. "Option pricing using EGARCH models," ZEW Discussion Papers 96-20, ZEW - Leibniz Centre for European Economic Research.
    4. French, Kenneth R. & Schwert, G. William & Stambaugh, Robert F., 1987. "Expected stock returns and volatility," Journal of Financial Economics, Elsevier, vol. 19(1), pages 3-29, September.
    5. repec:adr:anecst:y:1995:i:40:p:04 is not listed on IDEAS
    6. Robert F. Engle & Alex Kane & Jaesun Noh, 1993. "Index-Option Pricing with Stochastic Volatility and the Value of Accurate Variance Forecasts," NBER Working Papers 4519, National Bureau of Economic Research, Inc.
    7. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    8. C. W. J. Granger & Zhuanxin Ding, 1995. "Some Properties of Absolute Return: An Alternative Measure of Risk," Annals of Economics and Statistics, GENES, issue 40, pages 67-91.
    9. Robert F. Engle & Che-Hsiung Hong & Alex Kane, 1990. "Valuation of Variance Forecast with Simulated Option Markets," NBER Working Papers 3350, National Bureau of Economic Research, Inc.
    10. Bera, Anil K & Higgins, Matthew L, 1993. "ARCH Models: Properties, Estimation and Testing," Journal of Economic Surveys, Wiley Blackwell, vol. 7(4), pages 305-366, December.
    11. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
    12. Hull, John C & White, Alan D, 1987. "The Pricing of Options on Assets with Stochastic Volatilities," Journal of Finance, American Finance Association, vol. 42(2), pages 281-300, June.
    13. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    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. Christian Schittenkopf & Peter Tino & Georg Dorffner, 2002. "The benefit of information reduction for trading strategies," Applied Economics, Taylor & Francis Journals, vol. 34(7), pages 917-930.
    2. Krishnamurti, Chandrasekhar & Hoque, Ariful, 2011. "Efficiency of European emissions markets: Lessons and implications," Energy Policy, Elsevier, vol. 39(10), pages 6575-6582, October.

    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. Xekalaki, Evdokia & Degiannakis, Stavros, 2005. "Evaluating volatility forecasts in option pricing in the context of a simulated options market," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 611-629, April.
    2. Schmitt, Christian, 1996. "Option pricing using EGARCH models," ZEW Discussion Papers 96-20, ZEW - Leibniz Centre for European Economic Research.
    3. Koopman, Siem Jan & Jungbacker, Borus & Hol, Eugenie, 2005. "Forecasting daily variability of the S&P 100 stock index using historical, realised and implied volatility measurements," Journal of Empirical Finance, Elsevier, vol. 12(3), pages 445-475, June.
    4. Jiangze Du & Shaojie Lai & Kin Keung Lai & Shifei Zhou, 2021. "A novel term structure stochastic model with adaptive correlation for trend analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5485-5498, October.
    5. Nelson, Daniel B., 1996. "Asymptotic filtering theory for multivariate ARCH models," Journal of Econometrics, Elsevier, vol. 71(1-2), pages 1-47.
    6. Sung Ik Kim, 2022. "ARMA–GARCH model with fractional generalized hyperbolic innovations," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-25, December.
    7. 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.
    8. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, January.
    9. Stavros Degiannakis & Evdokia Xekalaki, 2005. "Predictability and model selection in the context of ARCH models," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 21(1), pages 55-82, January.
    10. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.
    11. BAUWENS, Luc & HAFNER, Christian & LAURENT, Sébastien, 2011. "Volatility models," LIDAM Discussion Papers CORE 2011058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
      • Bauwens, L. & Hafner C. & Laurent, S., 2011. "Volatility Models," LIDAM Discussion Papers ISBA 2011044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
      • Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    12. Siem Jan Koopman & Eugenie Hol Uspensky, 2000. "The Stochastic Volatility in Mean Model," Tinbergen Institute Discussion Papers 00-024/4, Tinbergen Institute.
    13. Bollerslev, Tim & Engle, Robert F. & Nelson, Daniel B., 1986. "Arch models," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 49, pages 2959-3038, Elsevier.
    14. Peter Christoffersen & Kris Jacobs, 2004. "Which GARCH Model for Option Valuation?," Management Science, INFORMS, vol. 50(9), pages 1204-1221, September.
    15. Daly, Kevin, 2008. "Financial volatility: Issues and measuring techniques," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(11), pages 2377-2393.
    16. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Volatility Forecasting," PIER Working Paper Archive 05-011, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    17. Gonzalez-Rivera, Gloria & Lee, Tae-Hwy & Mishra, Santosh, 2004. "Forecasting volatility: A reality check based on option pricing, utility function, value-at-risk, and predictive likelihood," International Journal of Forecasting, Elsevier, vol. 20(4), pages 629-645.
    18. Piotr Wdowinski & Marta Malecka, 2010. "Asymmetry in Volatility: A Comparison of Developed and Transition Stock Markets," CESifo Working Paper Series 2974, CESifo.
    19. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    20. Alagidede, Paul & Panagiotidis, Theodore, 2009. "Modelling stock returns in Africa's emerging equity markets," International Review of Financial Analysis, Elsevier, vol. 18(1-2), pages 1-11, March.

    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:zbw:zewdip:9625. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/zemande.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.