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  1. NTU Theses and Dissertations Repository
  2. 管理學院
  3. 財務金融學系
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/64972
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor石百達
dc.contributor.authorMin-Syuan Tsaien
dc.contributor.author蔡旻軒zh_TW
dc.date.accessioned2021-06-16T23:11:12Z-
dc.date.available2025-03-13
dc.date.copyright2020-03-13
dc.date.issued2020
dc.date.submitted2020-02-24
dc.identifier.citationBakshi G., Kapadia N., and Madan D. (2003). Stock Return Characteristics, Skew Laws, and the Differential Pricing of Individual Equity Options. The Review of Financial Studies, 16(1), 101-143.
Black, F. (1972). Capital Market Equilibrium with Restricted Borrowing. The Journal of Business, 45(3), 444-455.
Buss A. and Vilkov G. (2012). Measuring Equity Risk with Option-implied Correlations. The Review of Financial Studies, 25(10), 3113-3140.
Campbell R., Koedijk K., and Kofman P. (2002). Increasing correlation in bear markets. Financial Analysts Journal, 58(1), 87-94.
Chang B.-Y., Christoffersen P., Jacobs K., and Vainberg G. (2012). Option-Implied Measures of Equity Risk. Review of Finance, 16(2), 385-428.
Chesnay F. and Jondeau E. (2001), Does Correlation Between Stock Returns Really Increase During Turbulent Periods?. Economic Notes, 30, 53-80.
Christoffersen, Peter F., Jacobs K., and Vaniberg G. (2007). Forward-looking betas. Working paper, McGill University.
Delen D., Kuzey C., and Uyar A. (2013). Measuring firm performance using fincancial ratios: A decision tree approach. Expert Systems with Applications, 40(10), 3970-3983.
Heiberger R. H. (2014). Stock network stability in times of crisis. Physica A, 393, 376-381.
Huang W., Nakamori Y., and Wang, S.-Y (2005). Forecasting stock market movement direction with support vector machine. Computers & Operations Research, 32, 2513-2522.
Sun J. and Li H. (2008). Data mining method for listed companies’ financial distress prediction. Knowledge-Based Systems, 21(1), 1-5.
Sun J., Li H., Huang Q.-H., and He K.-Y. (2014). Predicting financial distress and corporate failure: A review from the state-of-the-art definitions, modeling, sampling, and featuring approaches. Knowledge-Based Systems, 57, 41-56.
Leung M. T., Daouk H., and Chen A. S. (2000). Forecasting stock indices: a comparison of classification and level estimation models. International Journal of Forecasting, 16, 173-190.
Lintner, J. (1965). SECURITY PRICES, RISK, AND MAXIMAL GAINS FROM DIVERSIFICATION. The Journal of Finance, 20(4), 587-615.
Longin F. and B. Solnik (2001). Extreme Correlatin of International Equity Markets. The Journal of Finance, 56(2), 649-676.
Patel J., Shah S., Thakkar P., and Kotecha K. (2015). Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques. Expert Systems with Applications, 42(4), 2162-2172.
Pesaran M. H. and Timmermann A. (1994). Forecasting stock returns an examination of stock market trading in the presence of transaction costs. Journal of Forecasting. 13(4), 335-367.
Sharpe W. F. (1964). CAPITAL ASSET PRICES: A THEORY OF MARKET EQUILIBRIUM UNDER CONDITIONS OF RISK*. The Journal of Finance, 19(3), 425-442.
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/64972-
dc.description.abstract本研究運用選擇權隱含之 Beta 值,探討市場危機是否具可預測性。本研究 搜集了 1996 年至 2016 年 S&P 500 股價指數與其成分股週資料,以 S&P 500 股 價指數月報酬率之風險值定義市場危機,並由選擇權隱含之 Beta 值定義三項代 理變數,使用決策樹模型對市場危機進行預測。實證結果發現,在相對寬鬆之 風險值下,決策樹模型較能夠正確預測市場危機以及 S&P 500 股價指數下跌之 趨勢。zh_TW
dc.description.abstractThis study investigates whether market crashes can be predicted using option- implied betas. Three proxy variables of option-implied betas as features are used to predict market crisis event which is defined using Value at Risk(VaR). The thesis empirical results based upon 1996-2016 S&P 500 data show that market crisis event and S&P 500 index movement could be predicted more accurately when using VaR with a lower confidence level.en
dc.description.provenanceMade available in DSpace on 2021-06-16T23:11:12Z (GMT). No. of bitstreams: 1
ntu-109-R06723056-1.pdf: 1770488 bytes, checksum: 1081f8b1b8f69b760956b39a88b693cc (MD5)
Previous issue date: 2020
en
dc.description.tableofcontents口試委員會審定書 .......................... #
摘要 .......................... ii
Abstract .......................... iii
第一章 緒論 .......................... 7
1.1 研究動機與目的 .......................... 7
1.2 研究流程 .......................... 7
第二章 文獻探討 .......................... 9
第三章 研究樣本與研究方法 .......................... 11
3.1 變數介紹 .......................... 11
3.1.1 特徵 .......................... 11
3.1.2 目標變數 .......................... 13
3.2 資料來源與樣本處理 .......................... 13
3.3 敘述性統計 .......................... 14
3.4 研究方法 .......................... 15
第四章 實證結果與分析 .......................... 18
第五章 結論. .......................... 22
參考文獻 .......................... 23
dc.language.isozh-TW
dc.title以選擇權隱含之 Beta 值預測市場危機zh_TW
dc.titleForecasting Market Crashes Using Option-implied Betasen
dc.typeThesis
dc.date.schoolyear108-1
dc.description.degree碩士
dc.contributor.coadvisor莊文議
dc.contributor.oralexamcommittee盧佳琪
dc.subject.keyword市場危機,決策樹,選擇權隱含貝它值,zh_TW
dc.subject.keywordStock Market Crashes,Decision Tree,Option-implied Beta,en
dc.relation.page24
dc.identifier.doi10.6342/NTU202000574
dc.rights.note有償授權
dc.date.accepted2020-02-24
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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