Skip to main content
Springer Nature Link
Log in

Pairs Trading via Nonlinear Autoregressive GARCH Models

  • Conference paper
  • First Online:
Integrated Uncertainty in Knowledge Modelling and Decision Making (IUKM 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10758))

Abstract

Pairs trading is a well-established speculative investment strategy in financial markets. However, the presence of extreme structural change in economy and financial markets might cause simple pairs trading signals to be wrong. To overcome this problem in detecting the buy/sell signals, we propose the use of three non-linear models consisting of Kink, Threshold and Markov Switching models. We would like to model the return spread of potential stock pairs by these three models with GARCH effects and the upper and lower regimes in each model are used to find the trading entry and exit signals. We also identify the best fit nonlinear model using the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). An application to the Dow Jones Industrial Average (DJIA), New York Stock Exchange (NYSE), and NASDAQ stock markets are presented and the results show that Markov Switching model with GARCH effects can perform better than other models. Finally, the empirical results suggest that the regime-switching rule for pairs trading generates positive returns and so it offers an interesting analytical alternative to traditional pairs trading rules.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Bauwens, L., Preminger, A., Rombouts, J.: Theory and Inference for a Markov Switching GARCH Model, Center for 2009-11

    Google Scholar 

  2. Bock, M., Mestel, R.: A regime-switching relative value arbitrage rule. In: Fleischmann, B., Borgwardt, K.H., Klein, R., Tuma, A. (eds.) Operations Research Proceedings. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-00142-0_2

    Google Scholar 

  3. Bollerslev, T.: Generalized autoregressive conditional heteroskedasticity. J. Econom. 31, 307–328 (1986)

    Article  MathSciNet  MATH  Google Scholar 

  4. Boonyasana, P., Chinnakum, W.: Forecasting Chinese international outbound tourists: Copula Kink AR-GARCH model. Thai J. Math. 215–229 (2016)

    Google Scholar 

  5. Chen, C.W.S., Chen, M., Chen, S.-Y.: Pairs trading via three-regime threshold autoregressive GARCH models. In: Huynh, V.-N., Kreinovich, V., Sriboonchitta, S. (eds.) Modeling Dependence in Econometrics. AISC, vol. 251, pp. 127–140. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-03395-2_8

    Chapter  Google Scholar 

  6. Do, B., Faff, R., Hamza, K.: A new approach to modeling and estimation for pairs trading. In: Proceedings of 2006 Financial Management Association European Conference, pp. 87–99, May 2006

    Google Scholar 

  7. Engle, R.F.: Autoregressive conditional heteroskedasticity with estimates of the variance of United Kingdom inflation. Econometrica 50, 987–1007 (1982)

    Article  MathSciNet  MATH  Google Scholar 

  8. Gatev, E., Goetzmann, W.N., Rouwenhorst, K.G.: Pairs trading: performance of a relative-value arbitrage rule. Rev. Fin. Stud. 19, 797–827 (2006)

    Article  Google Scholar 

  9. Elliott, R.J., Van Der Hoek, J., Malcolm, W.P.: Pairs trading. Quant. Financ. 5(3), 271–276 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  10. Haas, M., Mittnik, S., Paolella, M.S.: A new approach to Markov-switching GARCH models. J. Financ. Econom. 2(4), 493–530 (2004)

    Article  Google Scholar 

  11. Hamilton, J.D.: A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica J. Econ. Soc. 57, 357–384 (1989)

    Article  MathSciNet  MATH  Google Scholar 

  12. Hansen, B.E.: Regression kink with an unknown threshold. J. Bus. Econ. Stat. 35(2), 228–240 (2017)

    Article  MathSciNet  Google Scholar 

  13. Li, C.W., Li, W.K.: On a double-threshold autoregressive heteroscedastic time series model. J. Appl. Econom. 11, 253–274 (1996)

    Article  Google Scholar 

  14. Marcucci, J.: Forecasting stock market volatility with regime-switching GARCH models. Stud. Nonlinear Dyn. Econom. 9(4) (2005)

    Google Scholar 

  15. Miao, G.J.: High frequency and dynamic pairs trading based on statistical arbitrage using a two-stage correlation and cointegration approach. Int. J. Econ. Financ. 6(3), 96 (2014)

    Article  Google Scholar 

  16. Perlin, M.S.: Evaluation of pairs-trading strategy at the Brazilian financial market. J. Deriv. Hedge Funds 15(2), 122–136 (2009)

    Article  MathSciNet  Google Scholar 

  17. Vidyamurthy, G.: Pairs Trading: Quantitative Methods and Analysis, vol. 217. Wiley, Hoboken (2004)

    Google Scholar 

  18. Yang, J.W., Tsai, S.Y., Shyu, S.D., Chang, C.C.: Pairs trading: the performance of a stochastic spread model with regime switching-evidence from the S&P 500. Int. Rev. Econ. Financ. 43, 139–150 (2016)

    Article  Google Scholar 

  19. Zhu, K., Yamaka, W., Sriboonchitta, S.: Pair trading rule with switching regression GARCH model. In: Huynh, V.-N., Inuiguchi, M., Le, B., Le, B.N., Denoeux, T. (eds.) IUKM 2016. LNCS (LNAI), vol. 9978, pp. 586–598. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-49046-5_50

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Economics, Ramkhamhaeng University, Bangkok, Thailand

    Benchawanaree Chodchuangnirun

  2. Faculty of Economics, Chiang Mai University, Chiang Mai, Thailand

    Kongliang Zhu & Woraphon Yamaka

  3. Center of Excellence in Econometrics, Chiang Mai University, Chiang Mai, Thailand

    Woraphon Yamaka

Authors
  1. Benchawanaree Chodchuangnirun
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kongliang Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Woraphon Yamaka
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kongliang Zhu .

Editor information

Editors and Affiliations

  1. Japan Advanced Institute of Science and Technology, Nomi, Japan

    Van-Nam Huynh

  2. Osaka University, Osaka, Japan

    Masahiro Inuiguchi

  3. Hanoi National University of Education, Hanoi, Vietnam

    Dang Hung Tran

  4. Université de Technologie de Compiègne, Compiègne, France

    Thierry Denoeux

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Chodchuangnirun, B., Zhu, K., Yamaka, W. (2018). Pairs Trading via Nonlinear Autoregressive GARCH Models. In: Huynh, VN., Inuiguchi, M., Tran, D., Denoeux, T. (eds) Integrated Uncertainty in Knowledge Modelling and Decision Making. IUKM 2018. Lecture Notes in Computer Science(), vol 10758. Springer, Cham. https://doi.org/10.1007/978-3-319-75429-1_23

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-75429-1_23

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-75428-4

  • Online ISBN: 978-3-319-75429-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics