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Retrieving aggregate information from option volume

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

International Review of Economics & Finance, 2018, vol. 55, issue C, 220-232

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.

Keywords: Emerging options market; Option-information aggregation; Retail investors; VIX-adjusted put-call ratio (search for similar items in EconPapers)
JEL-codes: G10 G14 G15 (search for similar items in EconPapers)
Date: 2018
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