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A trading strategy based on Callable Bull/Bear Contracts

Author

Listed:
  • Cheung, Yan-Leung
  • Cheung, Yin-Wong
  • He, Angela W.W.
  • Wan, Alan T.K.

Abstract

The Callable Bull/Bear Contract is a barrier options contract recently introduced to the Hong Kong market. In this study, we propose a trading strategy that defines the entry point and exit point using information on the contract's call price and mandatory call event. Using data on contracts based on the Hong Kong Hang Seng Index, it is shown that the proposed trading strategy, on average, yields some decent trading returns that vary quite substantially across individual trades. Exploratory analyses indicate that trading returns are associated with volatility observed during a contract's lifespan and, to a lesser extent, with volatility in the pre-issuance period. Further, an issuer's relative issuing frequency may bear some implications for the trading strategy's performance.

Suggested Citation

  • Cheung, Yan-Leung & Cheung, Yin-Wong & He, Angela W.W. & Wan, Alan T.K., 2010. "A trading strategy based on Callable Bull/Bear Contracts," Pacific-Basin Finance Journal, Elsevier, vol. 18(2), pages 186-198, April.
    • Handle: RePEc:eee:pacfin:v:18:y:2010:i:2:p:186-198
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Leandro Maciel, 2020. "Technical analysis based on high and low stock prices forecasts: evidence for Brazil using a fractionally cointegrated VAR model," Empirical Economics, Springer, vol. 58(4), pages 1513-1540, April.
    2. He, Angela W.W. & Kwok, Jerry T.K. & Wan, Alan T.K., 2010. "An empirical model of daily highs and lows of West Texas Intermediate crude oil prices," Energy Economics, Elsevier, vol. 32(6), pages 1499-1506, November.
    3. Rima Ayu Shintyawati & Caturida Meiwanto Doktoralina & Nurhasanah & Sri Anah, 2020. "The Volume of Issuance of Government Islamic Securities SR-007 Series, 2015¨C2018," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 11(5), pages 56-68, October.
    4. Xiong, Tao & Li, Chongguang & Bao, Yukun, 2017. "Interval-valued time series forecasting using a novel hybrid HoltI and MSVR model," Economic Modelling, Elsevier, vol. 60(C), pages 11-23.
    5. Caporin, Massimiliano & Ranaldo, Angelo & Santucci de Magistris, Paolo, 2013. "On the predictability of stock prices: A case for high and low prices," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5132-5146.
    6. OlaOluwa S. Yaya & Xuan Vinh Vo & Ahamuefula E. Ogbonna & Adeolu O. Adewuyi, 2022. "Modelling cryptocurrency high–low prices using fractional cointegrating VAR," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 489-505, January.
    7. Sun, Yuying & Zhang, Xinyu & Wan, Alan T.K. & Wang, Shouyang, 2022. "Model averaging for interval-valued data," European Journal of Operational Research, Elsevier, vol. 301(2), pages 772-784.
    8. Henning Fischer & Ángela Blanco‐FERNÁndez & Peter Winker, 2016. "Predicting Stock Return Volatility: Can We Benefit from Regression Models for Return Intervals?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(2), pages 113-146, March.
    9. Adrian C. H. Lei, 2015. "Price and Volume Effects of Exchange‐Traded Barrier Options: Evidence from Callable Bull/Bear Contracts," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 35(11), pages 1042-1066, November.
    10. Alia Afzal & Philipp Sibbertsen, 2021. "Modeling fractional cointegration between high and low stock prices in Asian countries," Empirical Economics, Springer, vol. 60(2), pages 661-682, February.
    11. Park, Seongkyu “Gilbert” & Suen, Wing & Wan, Kam-Ming, 2022. "Call auction design and closing price manipulation: Evidence from the Hong Kong stock exchange," Journal of Financial Markets, Elsevier, vol. 58(C).
    12. Tao Xiong & Yukun Bao & Zhongyi Hu, 2014. "Multiple-output support vector regression with a firefly algorithm for interval-valued stock price index forecasting," Papers 1401.1916, arXiv.org.

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