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博碩士論文 etd-0621112-163923 詳細資訊
Title page for etd-0621112-163923
The application of Multifactor model and VaR model in predicting market meltdown
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Advisory Committee
Date of Exam
Date of Submission
VaR, Risk factors, Cluster analysis, financial market meltdown, Stock returns
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本研究主要過程為利用 Fama-French 五因子模型以及 VaR 模型,配合集群分析方法,針對台灣五十成分股進行分群,依照個別股票之五因子特性,將性質相近之股票分為同一群,建立投資組合,使用投資組合日報酬計算其 VaR,並觀察VaR spread 在崩盤前走勢如何,是否具有某種特性。比較各集群群對於崩盤事件的預測能力,以及風險因子與預測能力之關係。
結果發現,對於大崩盤發生之前,VaR spread 走勢往往波動度會明顯上升。除了 2000 年崩盤事件以外。而預測能力較好之集群,往往其成分股與崩盤原因有較密切之關係。金融股對金融海嘯敏感;電子出口廠商股對匯率影響反應較強烈。整體而言,較具有預測能力之集群個股,其對於動能因子、投資人情緒有較強之敏感度,而對於淨值市價比之敏感度極小。若要以 VaR spread 走勢作為預測參考,可以選擇符合前述條件之個股來組成投資組合
With the progress of the times, the international financial market link is becoming more and more closely, while the probability of extreme events more and more high, if there are some indicators can be used as a prediction of the crash, as whether to sell the stocks, it can be very useful.
The study process for the use of the Fama-French five-factor model, as well as the VaR model, with the cluster analysis method, and clustering for Taiwan 50
constituent stocks in accordance with the five-factor characteristics of the individual stocks, the similar nature of stock into the same group, the establishment of portfolio, the use of portfolio daily returns to calculate the the VaR, and observe the VaR spread before the crash, how the trend, and whether certain characteristics. Comparison of the cluster group for the predictive ability of the collapse events, as well as the
relationship between risk factors and predictive ability.
The results of VaR spread movements are often subject to fluctuations significantly change the situation before the crash occurs. By intense will be stable or
from stable will be severe. Good predictive ability of the cluster, often its constituent stocks and the collapse of the reasons more closely the relationship. Financial stocks sensitive to the financial tsunami; Electronic stocks are subject to exchange rate affect.Overall, the group with the best predictive ability is more sensitive to momentum effects and investor sentiment indicators ,but non-sensitive to book-to-market factor.To use the Var spread as a predictor of reference,choosing to meet the aforementioned conditions of stocks to the portfolio is a nice way.
目次 Table of Contents
摘 要 I
Abstract II
圖 次 V
表 次 VI
第一章 緒論 1
第一節 研究動機與背景 1
第二節 研究目的 4
第二章 文獻探討 6
第一節 個股報酬影響因素之文獻 6
第二節 VaR模型之相關文獻 8
第三章 模型與研究方法 10
第一節 多因子模型 10
第三節 投資組合報酬之計算與單根檢定 12
第四節 EGARCH(1,1)模型 13
第五節 VaR之簡介與VaR Spread之定義 13
第六節 崩盤之定義 15
第七節 具有預測能力之條件 16
第八節 資料處理 17
第九節 研究流程圖 20
第四章 實證研究結果 21
第一節 基本資料分析 21
第二節 集群分析 22
第三節 單根檢定 24
第四節 預測能力比較 24
第五節 集群預測能力與風險因子之關聯 28
第五章 結論與建議 30
第一節 研究結論 30
第二節 後續研究建議 31
參考文獻 32
參考文獻 References
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