近年散戶投資人於股市佔有舉足輕重的地位，是不可忽視的波動因子，再加上效率市場假說之正確性有待驗證，其無法解釋多數市場現象，進而推動許多學者研究投資人情緒的契機，但因為前述研究多數僅探討投資人情緒與市場表現之關聯，故本論文新增經濟變數，以更全面的角度分析經濟、投資人情緒及市場三者間之交互作用。

本研究應用Christopher Sims（1980）提出的向量自我迴歸模型（VAR），探究消費者物價指數（CPI）、M2貨幣供給量（M2SL）、消費者情緒指數（UMCSENT）、CBOE市場波動率指數（VIX）、元大50卓越50基金（_0050_TW）及iShares費城交易所半導體ETF（SOXX）間之相關性。實證結果顯示，三者間具有互相預測之能力，CPI對於VIX及_0050_TW具有長期預測能力，SOXX亦能預測VIX，故符合經濟變數預測市場變數，進而預測情緒變數之假設。在市場連動性方面，SOXX與_0050_TW具有雙向回饋之關聯，驗證美國與台灣市場具有連動性。最後，藉由敏感性分析，分別新增商業信心指數及Nasdaq指數基金得知三者變數間之關聯轉變為情緒指標可預測經濟變數，經濟變數進而預測市場走向之結果。

如上所述，可以發現經濟、投資人情緒及市場表現三項因素互相牽動及影響，於進行投資決策時，需綜合考量多種情況，以利進行有效的資產配置。

Individual investors are crucial in the stock market today. Furthermore, since the validity of the efficient market hypothesis has yet to be verified, and its inability to explain most market events, has motivated many academics to investigate investor sentiment. However, most of the previous studies focused solely on examining the relationship between investor sentiment and market performance. This study includes economic variables to evaluate the economy, investor sentiment, and market interaction in greater depth.

The correlation between Consumer Price Index(CPI), M2(M2SL), University of Michigan: Consumer Sentiment(UMCSENT), Chicago Board Options Exchange Volatility Index(CBOE VIX), Yuanta Taiwan Top 50 ETF(_0050_TW) and iShares Semiconductor ETF(SOXX) is investigated using the vector autoregressive model (VAR) introduced by Christopher Sims (1980). Empirical findings indicate that the three variables can predict each other. In the long term, CPI and _0050 TW can both predict VIX, and SOXX can also predict VIX, hence, it is consistent with the hypothesis that economic variables predict market variables, which in turn predict sentiment variables. In terms of market connectivity, SOXX and _0050_TW have a two-way feedback correlation, validating the connectivity between the U.S. and Taiwan markets.

Finally, the sensitivity analysis of adding two proxy indicators, the Business Confidence Index and the Nasdaq Index Fund, reveals that the correlation between the three variables is transformed into another correlation mode. Sentiment variables predict economic variables, which in turn predicts market direction.

As mentioned above, we can see that the economy, investor sentiment, and market performance are interrelated and affect each other. To support appropriate asset allocation, it is vital to consider a variety of circumstances while making investment decisions.

1. 中文文獻
[1] 王冠閔, & 黃柏農. (2004). 台灣股, 匯市與美國股市關聯性探討. 臺灣經濟預測與政策, 34(2), 31-72.
[2] 周賓凰, 張宇志, & 林美珍. (2019). 投資人情緒與股票報酬互動關係. 證券市場發展季刊: 行為財務學特別專刊, 153.
[3] 洪瑞成, 王偉權, & 紀佳芳. (2014). 開放平盤以下放空與現股當沖對效率市場之影響: 台灣股市之實證. 會計與財金研究, 7(2), 43-69.
[4] 徐煜錡, 徐嘉妤, & 康鶴耀. (2020). 新型冠狀病毒流行前後之台灣加權股價指數預測模型. 創新與經營管理學刊, 9(2), 39-64.
[5] 張士傑, & 蔡政憲. (2011). 通貨膨脹風險, 學習機制與策略性資產配置. 財務金融學刊, 19(2), 73-109.
[6] 張偉諒. (2007). 消費者信心指數與台灣股票市場相關性之研究.
[7] 莊家彰, & 管中閔. (2005). 台灣與美國股市價量關係的分量迴歸分析. 經濟論文, 33(4), 379-404.
[8] 陳旭昇. (2013). 時間序列分析：總體經濟與財務金融之應用. 台北市：東華
[9] 楊奕農. (2017). 時間序列分析：經濟與財務上之應用(三版). 台北市：雙葉書廊
[10] 裴金成.(2021). 貨幣供應量M2對中小板指數的影響研究.中小企業管理與科技. 2021年16期, 118 – 119
[11] 趙理平, 王琮胤, 張阜民, & 賴沂松. (2020). 投資人情緒對台灣上市公司股票報酬之研究. 財金論文叢刊, (33), 54-73.
[12] 劉祥熹, & 涂登才. (2012). 美國股市及其總體經濟變數間關連性與波動性之研究─ VEC GJR DCC-GARCH-M 之模型應用. 經濟研究 (Taipei Economic Inquiry), 48(1), 139-189.
[13] 劉麗萍. (2009). 廣義貨幣供應量 M2 對股市的影響——基於牛熊市的實證分析. 科技廣場, (4), 26-27.
[14] 歐昱廷. (2018). 投資人情緒與基金績效關係之研究. 當代商管論叢, 3(1), 74-96.
[15] 黎明淵, 林修葳, 郭憲章, & 楊聲勇. (2003). 美, 日股市巨幅波動下的股市連動效果-美國, 日本與亞洲四小龍股市實證結果. 證券市場發展季刊, 15(1), 117-148.
 
2. 英文文獻
[1] Andreou, P. C., Kagkadis, A., & Philip, D. (2014). Investor sentiments, rational beliefs and option prices. Available at SSRN.
[2] Arshanapalli, B., Doukas, J., & Lang, L. H. P. (1995). Pre and post-October 1987 stock market linkages between U.S. and Asian markets. Pacific-Basin Finance Journal, 3(1), 57–73.
[3] Baker, M., & Wurgler, J. (2006). Investor sentiment and the cross‐section of stock returns. The journal of Finance, 61(4), 1645-1680.
[4] Bekhet, H. A., & Matar, A. (2013). Co-integration and causality analysis between stock market prices and their determinates in Jordan. Economic Modelling, 35, 508–514.
[5] Bilel, H., & Mondher, K. (2021). What Can explain catering of dividend? Environment information and investor sentiment. Journal of Economics and Finance, 45(3), 428–450.
[6] Brown, G. W., & Cliff, M. T. (2004). Investor sentiment and the near-term stock market. Journal of empirical finance, 11(1), 1-27.
[7] Cai, Y., Chou, R. Y., & Li, D. (2009). Explaining international stock correlations with CPI fluctuations and market volatility. Journal of Banking & Finance, 33(11), 2026–2035.
[8] Cakan, E., Doytch, N., & Upadhyaya, K. P. (2015). Does U.S. macroeconomic news make emerging financial markets riskier? Borsa Istanbul Review, 15(1), 37–43.
[9] Ceylan, Ö. (2021). Dynamics of global stock market correlations: the VIX and attention allocation. Journal of Applied Economics, 24(1), 392-400.
[10] Chan, K. C., Gup, B. E., & Pan, M.-S. (1992). An Empirical Analysis of Stock Prices in Major Asian Markets and the United States. The Financial Review, 27(2), 289–307.
[11] Chandra, A., & Thenmozhi, M. (2013). Investor sentiment, volatility and stock return comovements. Available at SSRN.
[12] Chen, Y.-L., & Tsai, W.-C. (2017). Determinants of price discovery in the VIX futures market. Journal of Empirical Finance, 43, 59–73.
[13] Chow, K. V., Jiang, W., Li, B., & Li, J. (2020). Decomposing the VIX: Implications for the predictability of stock returns. Financial Review, 55(4), 645-668.
[14] Chung, S. L., & Yeh, C. Y. (2011). Predicting market regimes and stock returns using investor sentiment. 證券市場發展季刊, 23(2), 1-28.
[15] Corradi, V., Distaso, W., & Mele, A. (2013). Macroeconomic determinants of stock volatility and volatility premiums. Journal of Monetary Economics, 60(2), 203–220.
[16] Degutis, A., & Novickytė, L. (2014). THE EFFICIENT MARKET HYPOTHESIS: A CRITICAL REVIEW OF LITERATURE AND METHODOLOGY. Ekonomika, 93(2), 7–23.
[17] Dow, J., & Gorton, G. (1997). Stock Market Efficiency and Economic Efficiency: Is There a Connection? The Journal of Finance, 52(3), 1087–1129.
[18] Estrada, M. A. R., Koutronas, E., & Lee, M. (2021). Stagpression: The Economic and Financial Impact of the COVID-19 Pandemic. Contemporary Economics, 15(1), 19–33.
[19] Fisher, K. L., & Statman, M. (2003). Consumer confidence and stock returns. The Journal of Portfolio Management, 30(1), 115-127.
[20] Friedman, M. (1988). Money and the Stock Market. Journal of Political Economy, 96(2), 221–245.
[21] Hsing, Y. (2011). Effects of Macroeconomic Variables on the Stock Market: The Case of the Czech Republic. Theoretical & Applied Economics, 18(7).
[22] Huang, B.-N., Yang, C.-W., & Hu, J. W.-S. (2000). Causality and cointegration of stock markets among the United States, Japan, and the South China Growth Triangle. International Review of Financial Analysis, 17.
[23] Hussin, M. Y. M., Muhammad, F., Abu, M. F., & Awang, S. A. (2012). Macroeconomic Variables and Malaysian Islamic Stock Market: A Time Series Analysis. 3(4), 13.
[24] Jeon, B. N., & Jang, B.-S. (2004). The linkage between the US and Korean stock markets: The case of NASDAQ, KOSDAQ, and the semiconductor stocks. Research in International Business and Finance, 18(3), 319–340.
[25] Kaul, G. (1987). Stock returns and inflation: The role of the monetary sector. Journal of financial economics, 18(2), 253-276.
[26] Kim, S., & In, F. (2005). The relationship between stock returns and inflation: New evidence from wavelet analysis. Journal of Empirical Finance, 12(3), 435–444.
[27] Lin, C. B., Chou, R. K., & Wang, G. H. (2018). Investor sentiment and price discovery: Evidence from the pricing dynamics between the futures and spot markets. Journal of Banking & Finance, 90, 17-31.
[28] Ludvigson, S. C. (2004). Consumer confidence and consumer spending. Journal of Economic perspectives, 18(2), 29-50.
[29] Malkiel, B. G. (2003). The efficient market hypothesis and its critics. Journal of economic perspectives, 17(1), 59-82.
[30] Otoo, M. W. (1999). Consumer sentiment and the stock market. Available at SSRN 205028.
[31] Oxman, J. (2012). Price inflation and stock returns. Economics Letters, 116(3), 385–388.
[32] Renault, T. (2017). Intraday online investor sentiment and return patterns in the US stock market. Journal of Banking & Finance, 84, 25-40.
[33] S Chaves, C., & Silva, A. C. (2018). Inflation and stock returns at B3. Available at SSRN 3178972.
[34] Schmeling, M. (2009). Investor sentiment and stock returns: Some international evidence. Journal of empirical finance, 16(3), 394-408.
[35] Shaikh, I., & Padhi, P. (2015). The implied volatility index: Is ‘investor fear gauge’ or ‘forward-looking’? Borsa Istanbul Review, 15(1), 44–52.
[36] Shen, J., Yu, J., & Zhao, S. (2017). Investor sentiment and economic forces. Journal of Monetary Economics, 86, 1–21.
[37] Srividya, V., & Susana, D. (2019). The Impact of Macroeconomic Announcements on Equity Markets: Empirical Evidence from India. 2, 26.
[38] Thabet, E. H. (2014). Examining the Long Run Relationship between the U.S. Money Supply (M2) and the Canadian Stock Market. International Journal of Economics and Finance, 6(10), 11.
[39] Van Hoang, T. H., & Syed, Q. R. (2021). Investor sentiment and volatility prediction of currencies and commodities during the COVID-19 pandemic. Asian Economics Letters, 1(4), 18642.