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Retrieving aggregate information from option volume

Author

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  • Lin, William T.
  • Tsai, Shih-Chuan
  • Zheng, Zhenlong
  • Qiao, Shuai

Abstract

This paper studies how to retrieve aggregate information from the trading volume of Taiwan composite stock index options (TXO) with better quality by modifying the two option-information aggregation methods introduced in Holowczak et al. (2014). To study an emerging market such as the Taiwan options market, whose major players are retail investors, we take into consideration the retail participation rate and the trading distribution across moneyness, in addition to factors such as option market depth, liquidity, and investors' trading purposes, as discussed in Holowczak et al. (2014). Retail investors, who are generally less well-informed, have traded mainly nearby TXO options with expirations of less than one month. Therefore, the weights of nearby contracts should be reduced. Furthermore, both institutions and retail investors have traded more at near-the-money TXO options, and consequently the weights of in-the-money options and out-of-the-money options should be discounted to accommodate the uneven option trading across moneyness. In addition, we find that there is a dichotomy in the information roles of out-of-the-money options: the information content of their trades is higher (lower) when market volatility increases (decreases). Based on this finding, we establish a VIX-adjusted put-call ratio which increases (decreases) the weight of out-of-the-money options when the market VIX is larger (smaller) than its previous average level. Our model, as revised for an emerging market such as the Taiwan options market, has outperformed in explaining contemporaneous price changes and has shown very good predictive ability for large downside market moves.

Suggested Citation

  • Lin, William T. & Tsai, Shih-Chuan & Zheng, Zhenlong & Qiao, Shuai, 2018. "Retrieving aggregate information from option volume," International Review of Economics & Finance, Elsevier, vol. 55(C), pages 220-232.
  • Handle: RePEc:eee:reveco:v:55:y:2018:i:c:p:220-232
    DOI: 10.1016/j.iref.2017.07.018
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    Cited by:

    1. Doojin Ryu & Doowon Ryu & Heejin Yang, 2021. "The impact of net buying pressure on index options prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(1), pages 27-45, January.
    2. Yang, Heejin & Kutan, Ali M. & Ryu, Doojin, 2019. "Volatility information trading in the index options market: An intraday analysis," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 412-426.
    3. Zhang, Huiming & Watada, Junzo, 2019. "An analysis of the arbitrage efficiency of the Chinese SSE 50ETF options market," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 474-489.
    4. Avinash & T. Mallikarjunappa, 2020. "Informational Role of Open Interest and Transaction Volume of Options: A Meta-Analytic Review," FIIB Business Review, , vol. 9(4), pages 275-285, December.
    5. Chang, Carolyn W. & Lin, Bing-Huei & Yu, Min-Teh, 2018. "Derivatives trading information, stock market behavior, and financial institutions," International Review of Economics & Finance, Elsevier, vol. 55(C), pages 324-325.
    6. Yossi Shvimer & Avi Herbon, 2022. "Non-tradability interval for heterogeneous rational players in the option markets," Computational Management Science, Springer, vol. 19(1), pages 133-157, January.
    7. Chen, Zhiyu & Xu, Yun & Wang, Yu, 2023. "Can convertible bond trading predict stock returns? Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 79(C).
    8. Liu, Dehong & Qiu, Qi & Hughen, J. Christopher & Lung, Peter, 2019. "Price discovery in the price disagreement between equity and option markets: Evidence from SSE ETF50 options of China," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 557-571.
    9. Kaeck, Andreas & van Kervel, Vincent & Seeger, Norman J., 2022. "Price impact versus bid–ask spreads in the index option market," Journal of Financial Markets, Elsevier, vol. 59(PA).

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    More about this item

    Keywords

    Emerging options market; Option-information aggregation; Retail investors; VIX-adjusted put-call ratio;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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