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博碩士論文 etd-0826111-011537 詳細資訊
Title page for etd-0826111-011537
論文名稱
Title
市場與行為因素對股票報酬之影響-馬可夫轉換模型之應用
Market and Behavioral Factors on Stock Returns-The Application of Markov Regime-Switching Models
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
74
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2011-07-11
繳交日期
Date of Submission
2011-08-26
關鍵字
Keywords
馬可夫轉換模型、股票報酬、風險因素、投資者情緒、集群分析
Markov Regime-switching, Stock returns, Investors sentiment, Risk factors, Cluster analysis
統計
Statistics
本論文已被瀏覽 5832 次,被下載 764
The thesis/dissertation has been browsed 5832 times, has been downloaded 764 times.
中文摘要
本研究主要目的為利用Fama-French五因子模型與馬可夫狀態轉換模型分析美國股票報酬的變動,探討市場面及行為面風險因素對股價行為的影響力,並利用集群分析瞭解不同特性的樣本公司對不同風險因子與股票報酬的關係是否有所差異。本文實證結果顯示,股票報酬在低波動狀態有相對較高之超額報酬和存續期間,高波動狀態則有相對較低之超額報酬及存續期間;本文亦發現各種風險因子對股票報酬影響並非對稱,在低波動狀態下市場面因子和動能效應對股價報酬具有顯著的影響力,而在高波動狀態下除了規模效應外,市場面因子和行為面因子同時顯著影響了股票報酬率,但影響程度與低波動狀態呈現很大的差異。同時本文進一步驗證馬可夫轉換模型較Fama-French因子模型適切地描述股票報酬行為,透過模型轉換的設定能瞭解到各種因子在不同狀態下對股票市場的解釋力及影響力,更確實捕捉到不同狀態間所傳遞的樣本資訊。
最後利用馬可夫轉換模型之估計結果以集群分析來做分群討論,結果顯示考慮集群分析的多因子模型是可行的研究方式。本文發現具有成熟型公司特性之股票報酬主要受到市場風險溢酬的影響,而具有成長型公司特性之股票報酬主要影響因子為投資者情緒;此外發現具有小型公司特性之股票報酬在容易受到投資者情緒影響的情況下,投資者會以股票過去的表現做為投資行為的參考依據,使動能效應明顯影響股票報酬。最後我們也瞭解除了市場面因子為影響股價報酬的基本因素外,行為面因子亦是探討股價行為的重要因素之一。
Abstract
In this paper, we use a Fama-French model and Markov regime-switching model to capture time series behavior of many financial variable. Alternatively, classification by cluster analysis help to learn the different characteristics of the sample between stock returns and risk factors. This empirical result shows that the excess return in the low volatility state tends to be greater than that in the high volatility state. The stock returns in each regime have a higher probability of remaining in their original state, especilly in low volatility state. This article also found the influence of risk factors affecting the stock returns is not symmetrical. In the state of low volatility, market factors and momentum effect have a significant influence in stock returns, and in the high volatility state, except the size effect, market and behavior factors have a significant influence in stock returns. Markov-switching models have proved to be useful for modeling a range of economic time series in the stock market. The regime-switching model has a superior performance in capturing the risk sensitivities of the stock return beyond the findings based on the Fama-French models.
At last, we find the cluster analysis is feasible for the multi-factor model. The returns of mature companies have a primarily impact of market risk premium, while the major factor affecting returns with characteristics of growth companies is a investor sentiment. In addition, it is found that small companies’ returns are vulnerable to investors sentiment. In this case, investors will invest based on stock's past performance, so the momentum effect significantly affect the stock returns.
目次 Table of Contents
目 錄
中文摘要 …………………………………………… I
英文摘要 …………………………………………… II
圖目錄 ……………………………………………… VI
表目錄 ………………………………………………  VII
第一章 緒論 1
第一節 研究動機 1
第二節 研究目的 4
第三節 研究流程 5
第二章 文獻探討 6
第一節 影響股票報酬因素之文獻 6
第二節 投資者情緒對股票報酬影響之文獻 8
第三節 馬可夫轉換模型相關文獻 10
第三章 模型與研究方法 12
第一節 馬可夫狀態轉換模型 12
第二節 集群分析 16
第三節 實證研究模型 18
第四節 模型之檢定與估計 20
第四章 實證研究分析 23
第一節 資料說明與處理 23
第二節 基本資料分析 27
第三節 模型檢定 29
第四節 模型估計結果分析 30
第五節 集群分析 36
第五章 結論與建議 40
第一節 研究結論 40
第二節 後續研究建議 42
參考文獻 43
參考文獻 References
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