請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/80289完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 石百達(Pai-Ta Shih) | |
| dc.contributor.author | Rui-Chi Chang | en |
| dc.contributor.author | 張芮綺 | zh_TW |
| dc.date.accessioned | 2022-11-24T03:03:53Z | - |
| dc.date.available | 2021-07-08 | |
| dc.date.available | 2022-11-24T03:03:53Z | - |
| dc.date.copyright | 2021-07-08 | |
| dc.date.issued | 2021 | |
| dc.date.submitted | 2021-06-29 | |
| dc.identifier.citation | An, B., A. Ang, T.G. Bali, and N. Cakici. 2014. The joint cross section of stocks and options. Journal of Finance 69, 2279-2337. Chakravarty, S., H. Gulen, and S. Mayhew. 2004. Informed trading in stock and option markets. Journal of Finance 59, 1235-1257. Cremers, M. and D. Weinbaum. 2010. Deviations from put–call parity and stock return predictability. Journal of Financial and Quantitative Analysis 45, 335–367. Johnson, T.L. and E.C. So. 2012. The option to stock volume ratio and future returns. Journal of Financial Economics 106, 262–286. McLean, R.D. and J. Pontiff. 2016. Does academic research destroy stock return predictability? Journal of Finance 71, 5-32. Pan, J. and A. Poteshman. 2006. The information in option volume for future stock prices. Review of Financial Studies 19, 871-908. Roll, R., E. Schwartz, and A. Subrahmanyam. 2010. O/S: The relative trading activity in options and stock. Journal of Financial Economics 96, 1-17. Stambaugh, R.F., J. Yu, and Y. Yuan. 2012. The short of it: Investor sentiment and anomalies. Journal of Financial Economics 104, 288–302. Xing, Y., X. Zhang, and R. Zhao. 2010. What does the individual option volatility smirk tell us about future equity returns? Journal of Financial and Quantitative Analysis 45, 641–662. Lee, S.W. 2020. The joint information in option price and the volume ratio of option and stock for future stock returns. (Unpublished doctoral dissertation). National Taiwan University, Taipei. IC Insights. 2020, November 23. Intel to Keep Its Number One Semiconductor Supplier Ranking in 2020. Cambridge Spark. 2017, September 11. Getting started with XGBoost. Retrieved from https://blog.cambridgespark.com/getting-started-with-xgboost-3ba1488bb7d4 | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/80289 | - |
| dc.description.abstract | 本文透過由下而上累積個股選擇權的資訊來判斷美國半導體產業未來4週的股票趨勢，將微笑曲線和P/(C+S)比率的十年相對排名、以及四個月的排名差作為模型變數，並以Random Forest和XGBoost兩種演算法預測股價指數的空頭訊號。研究結果發現模型在預測跌幅超過6.37%時有不錯的表現；此外短期內微笑曲線排名的變化可以提升模型預測空頭的能力，而短期內P/(C+S)比率的排名變化則需要搭配其他變數方能區分有用的資訊抑或雜訊。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2022-11-24T03:03:53Z (GMT). No. of bitstreams: 1 U0001-2906202115413200.pdf: 2519845 bytes, checksum: d7c4e6a55fd2d5949d486d071d4a1fdc (MD5) Previous issue date: 2021 | en |
| dc.description.tableofcontents | 口試委員會審定書……………………………………………………………………..i 誌謝………………………………………………………………………………….....ii 摘要…………………………………………………………………………………iii Abstract...……………………………………………………………………………...iv 目錄…………………………………………………………………………………….v 圖目錄………………………………………………………………………………vii 表目錄……………………………………………………………………………….viii 第一章 緒論…………………………………………………………………………...1 1.1 研究動機與目的…………………………………………………………..….1 1.2 研究架構…....…………………………………………………………….…..4 第二章 文獻回顧……………………………………………………………………...5 第三章 研究流程……………………………………………………………………...7 3.1 資料來源和篩選……………………………………………………………...7 3.2 選擇權價量資訊和半導體股價指數………………………………………...8 3.2.1 選擇權價格…………………………………………………………......8 3.2.2 選擇權交易量………………………......................................................9 3.2.3 半導體股價指數………………………..................................................9 3.3 變數處理.....…………………………………………………………………10 3.3.1 訊號發布日期……………………………………….………………...10 3.3.2 價量資訊的排名………………………….…………………………...10 3.3.3 標記空頭…………………………………………………….………11 第四章 研究結果…………………………………………………………………….14 4.1 Random Forest……………………………………………………………….14 4.1.1 報酬率左尾10%.........……………………………….………………...14 4.1.2 報酬率左尾15%………………………….…………………………...17 4.2 XGBoost……………………………………………………………………..19 4.2.1 報酬率左尾10%.........………………………….………………...…....19 4.2.2 報酬率左尾15%…………………….………………………………....22 4.3 分析結果…………………………………………………………………….24 第五章 結論………………………………………………………………………….26 參考文獻…………………………………………………………………….…..…....27 附錄一 異常指標(anomaly)………..………………………………………………..28 | |
| dc.language.iso | zh-TW | |
| dc.subject | 極限梯度提升 | zh_TW |
| dc.subject | 半導體 | zh_TW |
| dc.subject | 隱含波動度 | zh_TW |
| dc.subject | 微笑曲線 | zh_TW |
| dc.subject | 選擇權交易量 | zh_TW |
| dc.subject | 危機預測 | zh_TW |
| dc.subject | 隨機森林 | zh_TW |
| dc.subject | Semiconductor | en |
| dc.subject | XGBoost | en |
| dc.subject | Random Forest | en |
| dc.subject | Crisis Forecasting | en |
| dc.subject | Crash Signal | en |
| dc.subject | Option Trading Volume | en |
| dc.subject | Volatility Skew | en |
| dc.subject | Volatility Smirk | en |
| dc.subject | Implied Volatility | en |
| dc.title | 以個股選擇權價量資訊預測美國半導體股票市場景氣 | zh_TW |
| dc.title | The Predictability of US Semiconductor Stock Market Using the Information of Individual Option Price and Volume | en |
| dc.date.schoolyear | 109-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 洪偉峰(Hsin-Tsai Liu),盧佳琪(Chih-Yang Tseng) | |
| dc.subject.keyword | 半導體,隱含波動度,微笑曲線,選擇權交易量,危機預測,隨機森林,極限梯度提升, | zh_TW |
| dc.subject.keyword | Semiconductor,Implied Volatility,Volatility Smirk,Volatility Skew,Option Trading Volume,Crash Signal,Crisis Forecasting,Random Forest,XGBoost, | en |
| dc.relation.page | 28 | |
| dc.identifier.doi | 10.6342/NTU202101189 | |
| dc.rights.note | 同意授權(限校園內公開) | |
| dc.date.accepted | 2021-06-30 | |
| dc.contributor.author-college | 管理學院 | zh_TW |
| dc.contributor.author-dept | 財務金融學研究所 | zh_TW |
| 顯示於系所單位： | 財務金融學系 | |
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|---|---|---|---|
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