本文利用GARCH模型 (generalized autoregressive conditional heteroskedasticity model) 探討標的股票與ADR (American Depositary Receipt) 之間錯價 (mispricing) 關係，了解兩者間是否有套利空間。本研究將COVID-19疫情衝擊納入考量，以台積電和聯電作為研究標的，發現錯價主要受美國市場影響，且在疫情過後美國市場的影響有顯著增加。模型中也加入錯價自身落遲項以了解收斂速度，研究發現聯電收斂的時間和幅度都大於台積電，受疫情的程度也台積電大。除了利用單變量GARCH模型分析錯價走勢外，本文也使用雙變量GARCH中的DCC 模型(dynamic conditional correlation model) 探討標的股票和ADR相關性的變化，結果顯示台積電較適合使用CCC模型 (constant conditional correlation model)，其標的股票和ADR之間的關係較穩定。

This paper studies the mispricing relationship between the underlying stock and ADR (American Depositary Receipt) and investigates whether there exists an arbitrage opportunity between them by the GARCH model (generalized autoregressive conditional heteroskedasticity model). Taking TSMC and UMC as examples, we found that the mispricing is mainly affected by the US market, and the impact of the US market has increased significantly after the COVID-19 pandemic. Furthermore, the time and amplitude of the convergence of UMC are greater than that of TSMC, and the pandemic has more impacts on UMC than on TSMC. In addition to the univariate GARCH model, this paper also adopts the DCC model (dynamic conditional correlation model) in the bivariate GARCH to explore the changes in the correlation between the underlying stock and ADR. The results show that the CCC model (constant conditional correlation model) fits better for TSMC and its relationship is more stable between the underlying stock and ADR.

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