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Analysis and Forecast of Tracking Performance of Hong Kong Exchange-Traded Funds: Evidence from Tracker Fund and X iShares A50

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  • Patrick Kuok-Kun Chu

    (Department of Accounting and Information Management, FBA, University of Macau, Avenida da Universidade, Taipa, Macao)

Abstract

This study examines the tracking performance of two Hong Kong exchange-traded funds (ETFs): Tracker Fund and X iShares A50. The turnover of these two ETFs was more than half the total turnover of the 141 ETFs in the Hong Kong market during 2005–2013. Tracking performance is assessed using pricing deviation, which is found to be nonzero and predictable. This indicates that the premium paid by investors is of considerable economic interest. The significant differences in the tracking performance of physical ETFs and synthetic ETFs highlight the relative inability of synthetic ETF to track the market. Additionally, we document the existence of co-integration between the ETF prices and stock market prices. An econometric model is estimated to forecast the pricing deviation, which shows different price dynamics between the two ETFs, but an absence of arbitrage opportunities. The time series regression model of pricing deviation is significantly influenced by market value, dividend yield, trading volume, bid-ask spread, and market risk. The size of the regression coefficients indicates that synthetic ETFs have relatively poor ability to track the market during market fluctuations.

Suggested Citation

  • Patrick Kuok-Kun Chu, 2016. "Analysis and Forecast of Tracking Performance of Hong Kong Exchange-Traded Funds: Evidence from Tracker Fund and X iShares A50," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 19(04), pages 1-26, December.
  • Handle: RePEc:wsi:rpbfmp:v:19:y:2016:i:04:n:s0219091516500223
    DOI: 10.1142/S0219091516500223
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    2. Angelos Kanas & Angelos Kotios & Panagiotis D. Zervopoulos, 2019. "Semi-parametric real exchange rates dynamics," Review of Quantitative Finance and Accounting, Springer, vol. 52(2), pages 643-656, February.

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