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姓名 邢志祥(Chih-Hsiang Hsing) 查詢紙本館藏 畢業系所 財務金融學系 論文名稱 產業低波動投組之市場預警效果
(Market Warning Effect of Industrial Low Volatility Portfolio)相關論文 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]
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摘要(中) 從財務理論中我們知道報酬與風險具有正向的抵換關係,簡單來說就是「高風險,高報酬」,但過去一些研究發現在某些市場中,低波動投資組合報酬高於高波動投資組合報酬,此違反傳統財務理論的現象稱為低波動異常現象。後續也有研究發現透過低波動異常現象建構的低波動投資組合報酬有市場預警的效果。
本研究分別以總風險、系統風險和獨有風險當作衡量風險的變數,根據風險變數分類產業,產業風險的計算方式分別採簡單平均加權和市值加權,發現台灣產業間有低波動異常現象,低風險產業的報酬高於高風險產業的報酬,再使用一個月觀察期與一個月持有期建構產業低波動投資組合,發現產業低波動投組報酬的標準差有市場預警的能力,並且使用簡單平均加權計算產業風險的市場預警能力優於使用市值加權計算產業風險的市場預警能力,最後使用此指標建構市場擇時策略,策略報酬優於買進持有大盤。摘要(英) In the financial theory, we know that there is a positive trade-off relationship between return and risk, which is called "high risk, high return". But some researches have found that return of low-volatility portfolio are higher than return of high-volatility portfolio in some markets. This phenomenon is called low volatility anomaly. Subsequent researches also found that return of low-volatility portfolio constructed by low-volatility anomalies have market warning effects.
This thesis uses total risk, system risk and idiosyncratic risk as risk variables, and sorts industries by risk variables. The calculation method of industrial risk are equal weighted and capitalization weighted. The result shows that there is industrial low volatility abnormal phenomenon in Taiwan. The return of low-risk industries is higher than return of high-risk industries. This thesis uses one-month formation period and holding period to construct industrial low volatility portfolio. The result shows that the standard deviation of portfolio return have market warning effect. The market warning effect of using equal weighted to calculate industrial risk is better than using capitalization weighted to calculate industrial risk. Finally, this thesis uses the indicator to construct a market timing strategy. The return of timing strategy is better buy and hold index.關鍵字(中) ★ 低波動異常現象
★ 避風港效應
★ 總風險
★ 系統風險
★ 獨有風險關鍵字(英) ★ Low volatility anomaly
★ Safe haven effect
★ Total risk
★ Systematic risk
★ Idiosyncratic risk論文目次 摘要 ……………..…………………………………………………………………… i
Abstract ……………………………………………………………………………… ii
誌謝 ………………………………………………………………………………… iii
目錄 ………………………………………………………………………………… iv
圖目錄 …………………………………………………………………………...…. vi
表目錄 …………………………………………………………..………………… viii
一、 緒論 …..………...……………………………………………………….. 1
1-1 研究動機 …..………………………………………………………….. 1
1-2 研究架構 …..………………………………………………………….. 3
二、 研究方法 …….………………………………………………………….. 4
2-1 資料選取 …..………………………………………………………….. 4
2-2 研究方法 …..………………………………………………………….. 4
三、 研究結果 …..…...……………………………………………………….. 8
3-1 檢驗產業低波動異常現象 …..……………………………………….. 8
3-1-1 簡單平均加權 …………………………………………………….... 8
3-1-2 市值加權 ..………..……………………………..……………….... 10
3-2 產業低波動投組指標與股市大盤的關係 …………………..……... 12
3-2-1 簡單平均加權 …………………………………………..……….... 12
3-2-2 市值加權 ..………..…………………………..………..……….... 13
3-3 產業低波動投組指標市場預警的能力 ……………...……………... 20
3-3-1 簡單平均加權 …………………………………..……………….... 20
3-3-2 市值加權 …………………………………………………..……… 24
3-4 以產業低波動投組指標建構市場擇時策略…………...…….……... 28
3-4-1 簡單平均加權 …………………………………………..……….... 28
3-4-2 市值加權 …………………………………………………..……… 30
四、 結論與建議 …………………………………………………………..…. 32
參考文獻 ……………………………………………………………………..……. 34參考文獻 [1] Ang, A., Hodrick, R. J., Xing, Y., & Zhang, X. (2006). The cross-section of volatility and expected returns. The Journal of Finance, 61(1), 259-299.
[2] Ang, A., Hodrick, R. J., Xing, Y., & Zhang, X. (2009). High idiosyncratic volatility and low returns: International and further U.S. evidence. Journal of Financial Economics, 91(1), 1-23.
[3] Fama, E. F., & French, K. R. (1992). The cross‐section of expected stock returns. The Journal of Finance, 47(2), 427-465.
[4] Fama, E. F., & French, K. R. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33(1), 3-56.
[5] Frazzini, A., & Pedersen, L. H. (2014). Betting against beta. Journal of Financial Economics, 111(1), 1-25.
[6] Guo, H., & Savickas, R. (2010). Relation between time-series and cross-sectional effects of idiosyncratic variance on stock returns. Journal of Banking & Finance, 34(7), 1637-1649.
[7] Garcia-Feijóo, L., Kochard, L., Sullivan, R. N., & Wang, P. (2015). Low-Volatility Cycles: The Influence of Valuation and Momentum on Low-Volatility Portfolios. Financial Analysts Journal, 71(3), 47-60.
[8] Kaul, A., & Sapp, S. (2006). Y2K fears and safe haven trading of the US dollar. Journal of international money and finance, 25(5), 760-779.
[9] 吳冠緯, 「低波動異常現象及其預測能力」, 國立中央大學,碩士論文,民國105年。
[10] 許博淳, 「低波動效果與市場預警之指標」, 國立中央大學,碩士論文,民國106年。指導教授 吳庭斌(Ting-Pin Wu) 審核日期 2020-6-29 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