政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/101084

政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/101084

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政大機構典藏 > 商學院 > 金融學系 > 學位論文 > Item 140.119/101084

請使用永久網址來引用或連結此文件: https://nccur.lib.nccu.edu.tw/handle/140.119/101084

題名:	CBOE SKEW指數資訊內涵研究-應用馬可夫狀態轉換模型建構交易策略 The Information Content of CBOE SKEW Index - Trading Strategy Under Markov Regime Switching Model
作者:	簡育昰 Jian, Yu Shi
貢獻者:	陳威光林靖庭 Chen, Wei Kuang Lin, Ching Ting 簡育昰 Jian, Yu Shi
關鍵詞:	SKEW指數 VIX指數馬可夫狀態轉換模型交易策略 SKEW Index VIX Index Markov Switching Model Trading Strategy
日期:	2016
上傳時間:	2016-09-01 23:47:21 (UTC+8)
摘要:	被市場稱作黑天鵝指數的CBOE SKEW指數在2015年10月12日來到了歷史新高148.92，這比2006年房地產泡沫破滅前及1998年長期資本管理公司倒閉時觸及的水準還要高，亦同時加劇了市場恐慌的心理。實際觀察股市後續發展，並未發生崩跌的現象，這引起我們的好奇心究竟SKEW指數該如何解讀。 CBOE於2011年推出SKEW指數，本文針對SKEW指數探究其資訊內含並建構交易策略。首先透過一系列的時間序列分析對SKEW指數有基本的認識。透過時間序列分析加以驗證SKEW指數與VIX指數是兩個捕捉不同資訊內涵的指數。VIX指數捕捉的是報酬的標準差，而標準差僅描述平均數附近的報酬分布。但S&P500指數報酬並非常態分配，SKEW指數能額外捕捉VIX指數捕捉不到的尾端風險。SKEW指數還能用來預測未來大盤走勢，在不同資料頻率比較下以預測大盤週報酬的效果最好。本文進一步採用SKEW指數建構交易策略。以採用固定轉換機率馬可夫轉換模型下VIX指數所偵測的狀態轉換為比較基準，比較增加SKEW指數作為訊息因子後所採用的時序變動型馬可夫轉換模型是否能提升模型偵測狀態轉換的能力。樣本期間為2002年4月15日至2013年3月29日，透過模型偵測到狀態轉換的時點，於隔日以開盤價在市場上建立相應部位。當再次偵測到狀態轉換時，隔日以開盤價做反向部位，如此反覆操作。實證結果發現以VIX指數作為應變數並搭配SKEW指數作為訊息因子下的時序變動型馬可夫轉換模型偵測狀態轉換的能力最佳，其中多頭部位表現又都較空頭部位表現好。以SKEW指數作為訊息因子的TVTP模型在不考慮稅、手續費及股利下年化報酬有13.61%，考慮稅、手續費及股利後年化報酬仍有12.47%。 This paper divided into two parts to investigate on the information content of CBOE SKEW Index. For the first part, we do time series analysis to observe the relationship between SKEW Index and other variables. First, we found that SKEW index is totally different from VIX index. VIX index is a proxy for the standard deviation of the returns. The standard deviation describes the average spread of the distribution of returns around its mean. This is not a sufficient measure of risk because the distribution of S&P 500 log returns is not normal. SKEW Index captures the tail risk of the distribution. Next, SKEW Index is good at predict future S&P500 ETF returns especially weekly speaking. Also, we found that the correlation between SKEW index & S&P500 index is too unstable to interpret. We argue that it’s not easy to interpret SKEW Index directly but we can combine SKEW Index with VIX Index. Regarding the above reason, in second part, we combined SKEW Index with VIX Index to construct trading strategy under Markov Switching Model. By comparing with FTP Model, which included VIX index only, we found that TVTP model, which encompassed VIX Index and SKEW Index together, significantly outperform others. When the model detected regime switching, we buy/short SPY ETF in the market separately. We did the simulation test from 2002.4.15 to 2013.3.29. Without considering tax, fee and dividend, we earned yearly average rate of return 13.61%. After considering tax, fee and dividend, we earned yearly average rate of return 9.51%.
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描述:	碩士國立政治大學金融研究所 103352005
資料來源:	http://thesis.lib.nccu.edu.tw/record/#G1033520052
資料類型:	thesis
顯示於類別:	[金融學系] 學位論文

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