在新冠肺炎影響下，大眾對於ESG相關議題的關注度吸引投資人在這方面議題更高程度的注意。此研究主在探討臺灣的傳統指數與綠能指數之間的因果與擴散關係，尤其在疫情前後之間的差異，探討在疫情後關於永續議題的發展。此研究採用Granger Causality test 及Spillover model(Baruník & Křehlík, 2018; Diebold & Yilmaz, 2012)來檢視指數間的因果與擴散關係。資料內容包括NASDAQ clean energy indexes，其用來代表綠能指數，及NASDAQ Taiwan Index，其用來代表臺灣傳統指數。資料涵蓋期間自2013年1月1日至2021年12月31日。
研究結果顯示，在長期來說，臺灣傳統指數與綠能指數之間存在雙向的因果關係，並且擴散效果在疫情之後顯得更為顯著。而兩者之間的連結頻率在疫情後更是顯著縮短及增強。上述發現可顯示出，在兩種指數相互影響的程度於疫情後加劇的情況下，長期投資者無論投資於傳統市場或綠色能源市場，其報酬可能將無顯著差異。而擴散效果的增強也顯示出投資者對於永續議題的關注日漸提升，隨著投資人的投資行為改變，所有關乎此議題發展的利害關係人，包括企業及政府等，也都必須將公司政策或政府政策轉向趨於永續發展的方向。

The growing concerns of ESG related issues have brought the investors’ attention to a higher level since the breakout of the Covid-19 pandemic. This study explores the causality and spillover over specific time and frequency domain between Taiwan’s conventional index and green indexes to provide insightful meanings of how the green investment has developed specifically after the pandemic. This study applies the Granger-Causality test and the spillover model by Baruník & Křehlík (2018) and Diebold & Yilmaz (2009, 2012) on NASDAQ clean energy indexes, representing as green indexes, and NASDAQ Taiwan Index, representing as Taiwan’s conventional index, with daily data from 1st January 2013 to 31st December 2021. The results show that there exists a bi-directional causality between the two sets of indexes in the long-run, and the spillover effect increases after the pandemic. The connectedness between the indexes also grows stronger in the high frequency domain after the pandemic. The above findings in this study suggest that the investors are paying more attention towards green investment. With the behavior of the investors changing, all concern parties including corporates and governments should be easier to steer their operations towards sustainability.

Table of Contents
論文審定書 i
摘要 ii
Abstract iii
Table of Contents iv
List of Figures v
List of Tables vi
1. Introduction 1
1.1. Sustainability development in recent years 1
1.2. Green finance in different countries and sectors 2
1.3. The causal relationship and spillover effect over time and frequency domain 4
2. Literature review 6
2.1. The development of green finance 6
2.2. Measuring spillovers in time and frequency domain 7
2.3. Connectedness between conventional and green indexes 9
3. Data and Methodology 9
3.1. Data 9
3.1.1. Descriptive statistics and stationary test 11
3.2. Measuring spillovers in time domain 11
3.3. Measuring spillovers in frequency domain 14
4. Results and discussion 24
4.1. Breitung & Candelon Granger Causality test 25
4.2. Diebold & Yilmaz Spillover index (DY12) over time domain in full period 32
4.3. Baruník & Křehlík Spillover index (BK12) over time and frequency domain 33
4.4. Discussion of the results 37
5. Conclusion 44
References 49

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