跳到主要內容

臺灣博碩士論文加值系統

(44.201.99.222) 您好!臺灣時間:2022/12/10 09:54
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

我願授權國圖
: 
twitterline
研究生:廖國洋
研究生(外文):Liao, Guo-Yang
論文名稱:低波動策略與近因偏誤:台灣股票市場的實證
論文名稱(外文):Low-Volatility Anomaly and Recency Biases: Evidence from the Taiwan Stock Market
指導教授:柯冠成柯冠成引用關係
指導教授(外文):KO, KUAN-CHENG
口試委員:楊念慈何曉緯柯冠成朱香蕙張眾卓
口試委員(外文):YANG,NIEN-TZUHO, HSIAO-WEIKO, KUAN-CHENGCHU, HSIANG-HUICHANG, CHONG-CHUO
口試日期:2020-05-16
學位類別:碩士
校院名稱:國立暨南國際大學
系所名稱:財務金融學系
學門:商業及管理學門
學類:財務金融學類
論文種類:學術論文
論文出版年:2020
畢業學年度:108
語文別:中文
論文頁數:50
中文關鍵詞:台灣股票市場低波動策略近因偏誤
外文關鍵詞:Taiwan stock marketLow-volatility anomalyRecency bias
DOI:doi:10.6837/ncnu202000090
相關次數:
  • 被引用被引用:1
  • 點閱點閱:92
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
本文以1982年7月至2018年12月的台股普通股作為研究樣本,探討買入低波動並賣出高波動組合的低波動策略投資組合,在台灣股票市場受近因偏誤影響之分析。首先,我們發現低波動策略在台灣市場並不具獲利性,在考慮近因偏誤下,我們分別建構高近因偏誤與低近因偏誤的低波動策略,並發現高
近因偏誤之低波動策略具有顯著獲利性,同時其獲利性較市場報酬來得穩健。此結果顯示投資人之交易行為的確受近因心理之影響。
在穩健性測試中,我們發現高近因偏誤的低波動策略在高流動性的公司中仍顯著為正,而以低流動性、高市值及高成交量的公司尤其顯著。在總風險和獨特性風險衡量下,各以高及低法人持股公司顯著,說明散戶相對法人無法完全分散獨特性風險,故高近因策略之獲利性會受此影響。在市場景氣擴張時,投資人情緒加深近因偏誤之影響,進而強化低波動策略之獲利性。整體而言,我們發現台灣市場的低波動度效果的確受到投資人的近因偏誤影響,在考量此因素後,可建構較佳之低波動交易策略。

In this paper, we use common stock listed in the Taiwan stock market for the period from July 1982 to December 2018 to examine the low-volatility strategy, which involves buying the low-volatility portfolio and short selling the high-volatility portfolio. We first show that the low-volatility strategie is not profitable. Considering the impact of recency biases, we construct two low-volatility strategies, namely high-recency and low-recency low-volatility strategies, and show that the low-recency low-volatility strategy generates significantly positive profits, which is more robust and resilient than the market portfolio. The result indicates that investors' trading behavior is widely affected by recency bias.
The robustness tests reveal that the profitability of the high-recency low-volatility strategy is particularly stronger among stocks with low liquidity, high market capitalization, and high trading volumes. Further, investors’ behavioral bias is strengthened when investor sentiment is high, resulting in higher profitability of the high-recency low-volatility strategy. Overall, we document supportive evidence for the recency bias in explaining the low-volatility anomaly in the Taiwan stock market. By taking recency bias into considertaion, we are able to come up with a better low-volatility strategy to enhance its profitability.

目次
摘要 i
Abstract ii
目次 iii
表目次 v
圖目次 vii
第一章 緒論 1
第一節 為何考慮投資人交易行為心理(近因心理)? 2
第二節 三個層面—市場環境、投資組合建構方式、投資人行為心理 4
第二章 資料及投資組合建構方法 11
第一節 資料及變數定義 11
第二節 投資組合建構方法 12
第三章 實證分析—總風險衡量的投資策略 15
第一節 敘述統計比較(總風險) 15
第二節 波動度效果分析(總風險) 16
第三節 近因波動度效果分析(總風險) 17
第四節 收益成長比較(總風險) 18
第四章 實證分析—獨特性風險衡量的投資策略 20
第一節 敘述統計比較(獨特性風險) 20
第二節 波動度效果分析(獨特性風險) 20
第三節 近因波動度效果分析(獨特性風險) 21
第四節 收益成長比較(獨特性風險) 22
第五章 波動度效果之穩健性分析(流動性、市值、法人持股、景氣、成交量) 24
第一節 總風險衡量的波動度效果 24
第二節 獨特性風險衡量的波動度效果 34
第六章 結論 41
參考文獻 43
一、中文部分 43
二、英文部分 43
三、網路部分 45
附錄 46
附錄一 外資持股之波動度效果分析 46
附錄二 投信持股之波動度效果分析 48
附錄三 自營商持股之波動度效果分析 48


參考文獻
一、中文部分
張琬喻、楊弘章與陳佳吟,2014。新聞媒體報導對公司財務績效與股價之影響,證券市場發展季刊。第26卷第1期:113-146。
許菁旂、黃文聰與黃振聰,2015。投資人情緒對低波動異常現象的預測力:市場狀態的影響。管理學報。第32卷第4期:399-424。
二、英文部分
Avery, C., & Peter, Z., 1998. Multidimensional uncertainty and herd behavior in financial markets. The American Economic Review, 88(4): 724-748.
Baker, M., Brendan, B., & Jeffrey, W., 2011. Benchmarks as limits to arbitrage: understanding the low-volatility anomaly. Financial Analysts Journal, 67(1): 40-54.
Baker, M., & Jeffrey, W., 2015. Do strict capital requirements raise the cost of capital? Bank regulation, capital structure, and the low-risk anomaly. American Economic Review, 105(5): 315-20.
Benartzi, S., 2002. Excessive extrapolation and the allocation of 401(k) accounts to company stock. The Journal of Finance, 56(5): 1747-1764.
Baker, N. L., & Haugen, R. A., 2012. Low risk stocks outperform within all observable markets of the world. SSRN Electronic Journal.
Block, R. A., & David, R. H., 1991. Overconfidence in estimation: testing the anchoring-and-adjustment hypothesis. Organizational Behavior and Human Decision Processes, 49(2): 188-207.
Boyer, B. H., & Keith, V., 2014. Stock Options as Lotteries. The Journal of Finance, 69(4): 1485-1527.
Baker, M., Hoeyer, M. F., & Jeffrey, W., 2016. The risk anomaly tradeoff of leverage. SSRN Electronic Journal
Blitz, D., & Milan, V., 2017. The profitability of low-volatility. Journal of Empirical Finance, 43: 33-42
Chow, T., Jason, C. H., Li-lan, K., & Feifei, L., 2014. A study of low-volatility portfolio construction methods. The Journal of Portfolio Management, 40(4): 89-105.
De Bondt, W. P. M., 1993. Betting on trends: Intuitive forecasts of financial risk and return. International Journal of forecasting– Elsevier, 9(3): 355-371.
De Bondt, W. F. M., & Richard, T., 1985. Does the stock market overreact? The Journal of Finance, 40(3): 793-805.
Dutt, T., & Mark, H., 2013. Stock return volatility, operating performance and stock returns: international evidence on drivers of the ‘low volatility’ anomaly. Journal of Banking & Finance, 37(3): 999-1017.
French, K. R., G. William, S., & Robert, F. S., 1987. Expected stock returns and volatility. Journal of financial Economics, 19(1): 3-29.
Garcia-Feijóo, L., Lawrence, E. K., Rodney, N. S., & Peng, W., 2015. Low-volatility cycles: the influence of valuation and momentum on low-volatility portfolios. Financial Analysts Journal, 71(3): 47-60.
Giot, P., 2005. Relationships between implied volatility indexes and stock index returns. The Journal of Portfolio Management, 31 (3): 92-100.
Hibbert, A. M., Robert, T. D., & Brice, D., 2008. A behavioral explanation for the negative asymmetric return–volatility relation. Journal of Banking & Finance, 32(10): 2254-2266.
Hsu, J., & Feifei, L., 2013. Low-volatility investing. The Journal of Index Investing, 4(2): 67-72.
Hamilton, J. D., & Gang, L., 1996. Stock market volatility and the business cycle. Journal of Applied Econometrics, 11(5): 573-593.
Hsu, J., Hideaki, K., & Toru, Y., 2013. When sell-side analysts meet high-volatility stocks: an alternative explanation for the low-volatility puzzle. Journal of Investment Management, 11(2): 28–46.
Kumar, A., 2009. Who Gambles in the Stock Market? Journal of Finance, 64(4): 1889–1933.
Kahneman, D., & Amos, T., 1979. Prospect theory: an analysis of decision under risk. Econometrica, 47(2): 263–291.
Li, X., Rodney, N. S., & Luis, G., 2016. The low-volatility anomaly: market evidence on systematic risk vs. mispricing. Financial Analysts Journal, 72(1): 36-47.
Li, X., Rodney, N. S., & Luis G., 2014. The limits to arbitrage and the low-volatility anomaly. Financial Analysts Journal, 70(1): 52-64.
Nofsinger, J. R., 2005. Social mood and financial economics. Journal of Behavioral Finance, 6(3): 144-160.
Shefrin, H., & Mario, L. B., 2007. Behavioral finance: biases, mean-variance returns, and risk premiums. CFA Institute Conference, 24(2): 4-12.
三、網路部分
Ramos, E., & J. C., Hans, 2013. Finding opportunities through the low-volatility anomaly. BMO Asset Management - bmogam.com.

電子全文 電子全文(網際網路公開日期:20250606)
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top