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Asymmetric volume volatility causality in dual listing H-shares

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Abstract

Using Granger causality test, we investigate the lead-lag relation between volume and volatility in 14 Chinese ADRs and those of their underlying H-shares. We consider volume as denoting liquidity. We model and forecast volatility using a TARCH model and find evidence of leverage effect and persistence in volatility among the ADRs and H-shares. We document significant but asymmetric bidirectional Granger causality between volume and volatility in ADRs and their underlying H-shares. The asymmetry seems to have declined in recent years, during the latter half of the sample period. We conclude that the relation between liquidity denoted by volume and volatility are time- varying and asymmetric between ADRs and their underlying H-shares.

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Notes

  1. For a comprehensive, albeit a little outdated survey of the literature on volume-volatility relations including causality, please refer to Chen and Daigler (2009). Briefly, on causality, the Sequential Information Arrival hypothesis proposed by Copeland (1976, 1977) and Jennings et al. (1981) suggest a positive bidirectional causal lead lag relation between trading volume and volatility. Using data on broad US markets, Hiemstra and Jones (1994), Brooks (1998) find causality between trading volume and volatility, albeit the direction of such causality is mixed. Lee and Rui (2002) find expected trading volumes Granger cause return variances in USA, UK, and Japan.

  2. As of September 2010, there are 51 Chinese ADRs listed on NYSE but only 14 of them have underlying H-shares listed on the Stock Exchange of Hong Kong (SEHK). The seemingly low sample size is dictated by the actual number of dual-listing Chinese H-shares and is common in published research on the subject (please refer to Xu and Fung 2002; Kutan and Zhou 2006; Poshakwale and Aquino 2008; He and Yang 2012; Dey and Wang 2012, 2021).

  3. Due to the unavailability of current data since its delisting in 2021, we could not update China Unicom (CHU) sample and leave the pre-updated sample ending in 2012.

  4. We follow Dey and Wang (2021) and detrend volume with a linear and a quadratic time trend filter.

  5. We compare TARCH (1,1) and EGARCH (1,1) results and find little differences between the parameter estimates. The likelihood ratios of both models reported in Table 3 show that for most securities TARCH (1,1), values are slightly higher than those related to EGARCH (1,1). We do not report comparative LL estimates corresponding to TARCH and EGARCH models in Table 4.

  6. For details on the the volume forecast, please refer to footnote 3; volatility forecasts, on the other hand, are due to Eqs. (1c) and (1d).

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Authors and Affiliations

  1. FINQ, 1091 Stillson Road, Fairfield, CT, 06824, USA

    Malay K. Dey

  2. School of Economics, University of Nottingham, Ningbo, China

    Chaoyan Wang

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  1. Malay K. Dey
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Dey, M.K., Wang, C. Asymmetric volume volatility causality in dual listing H-shares. J Asset Manag 23, 419–428 (2022). https://doi.org/10.1057/s41260-022-00275-z

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