第一篇台灣匯率與進出口之間的非對稱與因果關係探討。本研究旨在討論匯率與進出口之間的雙向關係，本文利用美聯儲提供的新台幣兌美元匯率，並包括了從2011年6月到2021年5月的歷史數據，檢驗了台灣海關的進出口貿易統計金額，以分析動態非線性關係。此外，本研究運用Enders和Granger（1998）、Enders and Siklos (2001)以及Enders and Siklos (2001) 門檻誤差差修正（TECM）方法，結合自回歸模型選擇並全面測試了短期因果關係和長期均衡。研究結果顯示，長期關係表明匯率作為重要指標並分別影響了台灣進口和出口的國際貿易。相比之下，進口和出口對匯率趨勢的影響不存在顯著關係。本研究通過數據分析台灣進出口貿易十年的數據，以證明雙向關係分析的重要性，擴展了誤差修正模型，有效地提供了實證證據。第二篇探討匯率對於中國大陸上海及深圳股市的動態非線性因果關係。延續第一篇的時間序列研究方法，本研究探討人民幣兌美元匯率以及對上海與深圳股市間的雙向非線性因果關係。經由最具解釋利模型選擇進行落後期檢驗與短期長期之門檻值研究。實證中發現人民匯率對上海股市存在領先並在門檻值之下有顯著影響，而匯率對深圳股市一樣在門檻值之下被捕捉到存在長期因果關係。上海與深圳股市相同的是存在拒絕共整合假說與初始落後期變數間的交互影響，以及不顯著的短期因果和非線性關係。不同的是，深圳股市與人民幣匯率在門檻值之下於數列分析中呈現交互影響並顯示長期顯著關係。第三篇研究東協國家 (ASEAN): 印尼、馬來西亞、菲律賓、新加坡、泰國與越南的主要股市與主要經濟變數間的互動關係。本文採用Hansen (1999) 、Gonzalez et al. (2004, 2005) 提出的panel threshold model 與panel smooth transition model 作為研究方法。以各國匯率、CPI、各國十年期公債殖利率及貿易餘額作為主要經濟變數，探討股市波動於門檻值之下及之下的非線性影響。本文利用 AIC、BIC 的比較，選擇出邏輯型模式作為具有解釋力的平滑移轉模型，並於實證中發現在 2014 至 2024 年間主要經濟變數在門檻值之上下互為反向效應呈現。當股市波動度在門檻值之下，匯率與十年期公債殖利率會顯著領先股市而CPI與貿易餘額則是落後效果，但CPI是顯著落後而貿易餘額則不顯著。反之當股市波動度在門檻值之上時，匯率(不顯著)與十年期公債殖利率(顯著)會受東協股市影響而CPI(顯著)與貿易餘額(不顯著)則是會影響東協股市。

The second chapter explored the asymmetric and causal relationships between the exchange rate and imports-exports in Taiwan. The study used the NTD/USD that provided by the Federal Reserve and historical data from June 2011 to May 2021. It examined the trade statistics from Taiwan Customs to analyze dynamic non-linear relationships. Utilizing the threshold error correction model (TECM) developed by Enders and Granger (1998), Enders and Siklos (2001), and Enders and Siklos (2001), the study combined autoregressive models to comprehensively test short-run causal relationships and long-run equilibrium. Results in the long-term that the exchange rate significantly affected Taiwan’s international trade in imports and exports, while the impacts of imports-exports on exchange rate trends were not significant. This research through ten years of data analysis underscored the importance of bidirectional relationship analysis and extended the error correction model and provided empirical evidence effectively. The third chapter investigated the dynamic non-linear causal relationships between the Renminbi exchange rate (CNY/USD) and the stock market indexes of Shanghai and Shenzhen in China. Building on the time series research methods be leveraged from the second chapter, this study examined the two-way non-linear causal relationships between the exchange rate and the stock markets. The most explanatory models were chosen, for lag period testing and threshold value research to both short-term and long-term effects were followed in procedure. Empirical findings revealed that the exchange rate leaded the Shanghai stock market with significant effects while below the threshold value, and long-term causal relationship was captured between the exchange rate and the Shenzhen stock market at condition below the threshold. Both Shanghai and Shenzhen stock markets shown a rejection of the co-integration hypothesis and interaction effects between initial lagged variables with insignificant short-term causal and non-linear relationships. However, the Shenzhen stock market showed significant long-term interaction effects with the Renminbi exchange rate below the threshold. The fourth chapter studied the interactions between major stock markets and key economic variables in ASEAN countries: Indonesia, Malaysia, the Philippines, Singapore, Thailand, and Vietnam. The research employed panel threshold models and panel smooth transition models proposed by Hansen (1999) and Gonzalez et al. (2004, 2005) as the research methods. Key economic variables included exchange rates, CPI, ten-year government bond yields, and trade balances. The study investigated the non-linear effects of stock market volatility to cover both sides at above and below the threshold value. By comparing AIC and BIC, the study selected logical model as the explanatory smooth transition model. Empirical results from 2014 to 2024 shown bidirectional inversed effects of key economic variables around the threshold value. When stock market volatility is below the threshold, exchange rates and ten-year government bond yields significantly led the stock market, with CPI showing significant lag and trade balances was not significant. Conversely when stock market volatility was above the threshold, exchange rates (insignificant) and ten-year government bond yields (significant) were affected by ASEAN stock markets, while CPI (significant) and trade balances (insignificant) impacted ASEAN stock markets.

Table of Contents

Acknowledgement	I
Abstract in Chinese	II
Abstract in English	IV
Table of Contents	VII
List of Tables	IX
List of Figures	X
Chapter 1 Introduction	1
Chapter 2 Study on the Non-Linear Causal Relationship between Exchange Rate and Import and Export Respectively– Taiwan Evidence	7
2.1 Introduction and literature review	7
2.2 Data	10
2.3 Methodologies and empirical results	11
	2.3.1 Threshold autoregressive model	15
	2.3.2 Threshold error correction (TECM) Granger-Causality test	16
2.4 Conclusion for this chapter	19
Chapter 3
Asymmetrical Causal Relationships between Exchange Rate and Stock Price in China	21
3.1 Introduction and literature review	21
3.2	Data	23
3.3 Methodologies and empirical results	24
	3.3.1 Threshold autoregressive model	25
	3.3.2 Threshold error correction (TECM) Granger-Causality test	28
3.4. Conclusion for this chapter	32
Chapter 4
Threshold Effect of Exchange Rate Volatility on ASEAN Stock Markets	34
4.1 Introduction and literature review	34
4.2 Data	36
4.3 Methodologies	39
	4.3.1 PSTR model	39
	4.3.2 Model specification	40
	4.3.2.1 Homogeneity test	  41
4.3.2.2 Function of logic and exponent	41
4.3.2.3 Number of threshold value test	42
4.4 Empirical results	43
4.5 Conclusion for this chapter	48
Appendix	50
Chapter 5 Conclusion	54
References	57

List of Tables

Table 2.3.1 Model specification in the effect of IM-1.	12
Table 2.3.2 Model specification in the effect of IM-2.	12
Table 2.3.3 Model specification in the effect of EX-1.	13
Table 2.3.4 Model specification in the effect of EX-2.	13
Table 2.3.5 M-TECM estimators in the effect of export and NTD/USD.	17
Table 2.3.6 TECM estimators in the effect of import and NTD/USD.	18
Table 3.3.1 Model specification in the effect of SS-1.	26
Table 3.3.2 Model specification in the effect of SS-2.	27
Table 3.3.3 Model specification in the effect of SZ-1.	28
Table 3.3.4 Model specification in the effect of SZ-2.	28
Table 3.3.5 M-TECM estimators in the effect of SS and CNY/USD.	30
Table 3.3.6 M-TECM estimators in the effect of SZ and CNY/USD.	31
Table 4.4.1 Panel descriptive statistics of macroeconomics variables	43
Table 4.4.2 Homogeneity test for m=1	44
Table 4.4.3 Homogeneity test for m=2	44
Table 4.4.4 Transition model specification	45
Table 4.4.5
Parameter estimation of the Logistic Smooth Transition Regression (LSTR) model	46
Table 4.4.6
Estimation of parameter effects in the Logical Smooth Transition Regression (LSTR) model	47
Table A-1 Descriptive statistics of macroeconomics variables in Indonesia	50
Table A-2 Descriptive statistics of macroeconomics variables in Malaysia	50
Table A-3 Descriptive statistics of macroeconomics variables in Philippine	51
Table A-4 Descriptive statistics of macroeconomics variables in Singapore	51
Table A-5 Descriptive statistics of macroeconomics variables in Thailand	52
Table A-6 Descriptive statistics of macroeconomics variables in Vietnam	53

List of Figures

Figure 2.2.1
Taiwan import-export and exchange rate historical data from 2011 to 2021	10
Figure 3.2.1
Trend Series in exchange rate of CNY/USD, SZSE and SSEC from 2004 to 2024	23
Figure 4.2.1 Trend series in exchange rate volatility and JKSE.	37
Figure 4.2.2 Trend series in exchange rate volatility and KLSE.	37
Figure 4.2.3 Trend series in exchange rate volatility and PSI.	37
Figure 4.2.4 Trend series in exchange rate volatility and STI.	38
Figure 4.2.5 Trend series in exchange rate volatility and SETI.	38
Figure 4.2.6 Trend series in exchange rate volatility and VNI.	38

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