博碩士論文 107428017 詳細資訊




以作者查詢圖書館館藏 以作者查詢臺灣博碩士 以作者查詢全國書目 勘誤回報 、線上人數:2 、訪客IP:3.94.202.172
姓名 梁可靖(Ko-Chin)  查詢紙本館藏   畢業系所 財務金融學系
論文名稱 預測熊市的總體經濟聯合指標
(Aligned Macroeconomic Index for Forecasting the Bear Markets)
相關論文
★ 從巴塞爾協定三談商業銀行資金流動性穩健指標★ 三大法人於台灣期貨市場擇時能力之探討
★ 奢侈稅課徵對於台灣房價之影響★ 外匯曝險對台灣半導體產業之現金流量的影響
★ 金控法規範的利害關係人非授信交易之探討★ 歐債危機是否會影響台灣股市?以台灣指數股票型基金為例
★ 寬鬆貨幣政策對於歐元匯率的影響★ 影響境外人民幣和境內人民幣價差變化的因素
★ 台灣銀行業高階經理人薪酬與銀行特性之關連性分析★ 承銷業務對證券分析師盈餘預測之影響
★ 經紀業務對分析師盈餘預測影響★ 領導者或追隨者:被忽略公司分析師盈 餘預測行為之研究
★ 個別投資人日內交易損益:臺灣期貨市場實證分析★ 外匯市場私有訊息之程度對於匯率變動之影響
★ 外國機構投資人和外匯市場:以臺北外匯交易市場為例★ 散戶與三大法人之處份效果研究:以台灣加權股價指數期貨為例
檔案 [Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   [檢視]  [下載]
  1. 本電子論文使用權限為同意立即開放。
  2. 已達開放權限電子全文僅授權使用者為學術研究之目的,進行個人非營利性質之檢索、閱讀、列印。
  3. 請遵守中華民國著作權法之相關規定,切勿任意重製、散佈、改作、轉貼、播送,以免觸法。

摘要(中) 我們透過 PLS 方法建構總體經濟聯合指標,並成為一強大的熊市預測指標。藉由將馬可夫轉換模型應用於美國標普五百指數報酬率上,我們可以辨識出熊市期間與該期間對應之熊市機率。不論在樣本內或樣本外的檢定,總體經濟聯合指標在預測熊市機率都統計上顯著優於其他指標,包含投資人情緒指標以及其他二十五個總體經濟指標。此外,將 PLS 應用在不同市場指標時,此方法仍可以維持其預測能力。
摘要(英) We use the PLS method to construct an aligned macroeconomic index, which is powerful in forecasting the bear markets. By using the Markov-switching model to return of the S&P 500 index, we identify the bear market and obtain the probability of each period. No matter in- and out-of-sample test, this index statistically outperforms twenty-five macroeconomic variables and the investor sentiment index in prediction bear markets. What is more, this method also could be applied to different market indicators, and the results remain robust.
關鍵字(中) ★ 總體經濟
★  熊市
關鍵字(英) ★ Macroeconomic
★  PLS
★  Bear Markets
論文目次 中文摘要 i
Abstract ii
Acknowledgements iii
Table of Contents iv
List of Figures v
List of Tables vi
1 Introduction 1
2 Methodology 3
2-1 Identify bear market 3
2-2 Aligned macroeconomic index ECON PLS 4
2-3 Predictive regression evaluation 6
3 Data and Empirical Results 8
3-1 Data 8
3-2 Result of Markov-switching models 12
3-3 In-sample and out-of-sample results 12
4 Robustness Check 15
4-1 Smoothing probabilities 15
4-2 Other market indicators 15
4-3 Nonparametric approach 15
5 Conclusion 17
參考文獻 Baker, M., & Wurgler, J. (2006). Investor sentiment and the cross‐section of stock returns. The Journal of Finance, 61(4), 1645-1680.
Baker, M., & Wurgler, J. (2007). Investor sentiment in the stock market. Journal of Economic Perspectives, 21(2), 129-152.
Brogaard, J., & Detzel, A. (2015). The asset-pricing implications of government economic policy uncertainty. Management Science, 61(1), 3-18.
Bry, G., & Boschan, C. (1971). Front matter to" Cyclical Analysis of Time Series: Selected Procedures and Computer Programs". In Cyclical analysis of time series: Selected procedures and computer programs (pp. 13-2). NBER.
Campbell, J. Y., & Shiller, R. J. (1988). The dividend-price ratio and expectations of future dividends and discount factors. Review of Financial Studies, 1(3), 195-228.
Campbell, J. Y., & Shiller, R. J. (1989). The dividend ratio model and small sample bias: a Monte Carlo study. Economics Letters, 29(4), 325-331.
Campbell, J. Y., & Thompson, S. B. (2007). Predicting excess stock returns out of sample: Can anything beat the historical average?. Review of Financial Studies, 21(4), 1509-1531.
Candelon, B., Piplack, J., & Straetmans, S. (2008). On measuring synchronization of bulls and bears: The case of East Asia. Journal of Banking & Finance, 32(6), 1022-1035.
Chen, N. F., Roll, R., & Ross, S. A. (1986). Economic forces and the stock market. Journal of Business, 383-403.
Chen, N. K., Chen, S. S., & Chou, Y. H. (2017). Further evidence on bear market predictability: The role of the external finance premium. International Review of Economics & Finance, 50, 106-121.
Chen, S. S. (2007). Does monetary policy have asymmetric effects on stock returns?. Journal of Money, Credit and Banking, 39(2‐3), 667-688.
Chen, S. S. (2009). Predicting the bear stock market: Macroeconomic variables as leading indicators. Journal of Banking & Finance, 33(2), 211-223.
Chronopoulos, D. K., Papadimitriou, F. I., & Vlastakis, N. (2018). Information demand and stock return predictability. Journal of International Money and Finance, 80, 59-74.
Clark, T. E., & West, K. D. (2007). Approximately normal tests for equal predictive accuracy in nested models. Journal of Econometrics, 138(1), 291-311.
Fama, E. F., & French, K. R. (1988). Dividend yields and expected stock returns. Journal of Financial Economics, 22(1), 3-25.
Fama, E. F., & Gibbons, M. R. (1984). A comparison of inflation forecasts. Journal of monetary Economics, 13(3), 327-348.
Frauendorfer, K., Jacoby, U., & Schwendener, A. (2007). Regime switching based portfolio selection for pension funds. Journal of Banking & Finance, 31(8), 2265-2280.
Hodrick, R. J. (1992). Dividend yields and expected stock returns: Alternative procedures for inference and measurement. Review of Financial Studies, 5(3), 357-386.
Huang, D., Jiang, F., Tu, J., & Zhou, G. (2015). Investor sentiment aligned: A powerful predictor of stock returns. Review of Financial Studies, 28(3), 791-837.
Jagannathan, R., & Wang, Z. (1996). The conditional CAPM and the cross‐section of expected returns. Journal of Finance, 51(1), 3-53.
Jiang, F., Lee, J., Martin, X., & Zhou, G. (2019). Manager sentiment and stock returns. Journal of Financial Economics, 132(1), 126-149.
Kelly, B., & Pruitt, S. (2013). Market expectations in the cross‐section of present values. Journal of Finance, 68(5), 1721-1756.
Kelly, B., & Pruitt, S. (2015). The three-pass regression filter: A new approach to forecasting using many predictors. Journal of Econometrics, 186(2), 294-316.
Lettau, M., & Ludvigson, S. (2001). Resurrecting the (C) CAPM: A cross-sectional test when risk premia are time-varying. Journal of political economy, 109(6), 1238-1287.
Lettau, M., & Ludvigson, S. C. (2005). Expected returns and expected dividend growth. Journal of Financial Economics, 76(3), 583-626.
Maheu, J. M., & McCurdy, T. H. (2000). Identifying bull and bear markets in stock returns. Journal of Business & Economic Statistics, 18(1), 100-112.
Merton, R. C. (1973). An intertemporal capital asset pricing model. Econometrica, 41(5), 867-887.
Neuhierl, A., & Schlusche, B. (2010). Data snooping and market-timing rule performance. Journal of Financial Econometrics, 9(3), 550-587.
Pontiff, J., & Schall, L. D. (1998). Book-to-market ratios as predictors of market returns. Journal of Financial Economics, 49(2), 141-160.
Rapach, D. E., Wohar, M. E., & Rangvid, J. (2005). Macro variables and international stock return predictability. International Journal of Forecasting, 21(1), 137-166.
Ross, S., 1976.The arbitrage theory of capital asset pricing. Journal of Economic Theory 13, 341–360.
Shen, J., Yu, J., & Zhao, S. (2017). Investor sentiment and economic forces. Journal of Monetary Economics, 86, 1-21.
Shen, P. (2003). Market timing strategies that worked. The Journal of Portfolio Management, 29(2), 57-68.
Welch, I., & Goyal, A. (2007). A comprehensive look at the empirical performance of equity premium prediction. Review of Financial Studies, 21(4), 1455-1508.
Wold, H. (1966). Estimation of principal components and related models by iterative least squares. Multivariate Analysis, 391-420.
Wold, H. (1975). Path models with latent variables: The NIPALS approach. In Quantitative sociology (pp. 307-357). Academic Press.
指導教授 高櫻芬(Yin-Feng Gau) 審核日期 2019-7-25
推文 facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu   
網路書籤 Google bookmarks   del.icio.us   hemidemi   myshare   

若有論文相關問題,請聯絡國立中央大學圖書館推廣服務組 TEL:(03)422-7151轉57407,或E-mail聯絡  - 隱私權政策聲明