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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 石百達(Pai-Ta Shih) | |
| dc.contributor.author | Meng-Chun Hsieh | en |
| dc.contributor.author | 謝孟均 | zh_TW |
| dc.date.accessioned | 2021-06-08T03:36:59Z | - |
| dc.date.copyright | 2019-07-31 | |
| dc.date.issued | 2019 | |
| dc.date.submitted | 2019-07-24 | |
| dc.identifier.citation | [1] Black, F., and M. Sholes, 1973. “The pricing of options and corporate liabilities.” Journal of Political Economy, 81: 637-654.
[2] Bakshi, G., N. Kapadia and D. Madan, 2003. “Stock return characteristics, skew laws, and the differential pricing of individual equity options.” The Review of Financial Studies, 16: 101-143. [3] Poon, S.-H. and C.W.J. Granger, 2003. “Forecasting volatility in financial markets: A review.” Journal of Economic Literature, 41: 478-539. [4] Christensen, B.J. and N.R. Prabhala, 1998. “The relation between implied and realized volatility.” Journal of Financial Economics, 50: 125-150. [5] Koopman, S.J., B. Jungbacker and E. Hol, 2005. “Forecasting daily variability of the S&P 100 stock index using historical, realised and implied volatility measurements.” Journal of Empirical Finance, 12: 445– 475. [6] Corrado, C.J. and T.W. Miller, 2005. “The forecast quality of CBOE implied volatility indexes.” Journal of Futures Markets, 25: 339–373. [7] Yang, M.J. and M.Y. Liu, 2012. “The forecasting power of the volatility index in emerging markets: Evidence from the Taiwan stock market.” International Journal of Economics and Finance, 4: 217-231. [8] Jiang, G.J., and Y.S. Tian, 2005. “The model-free implied volatility and its information content.” The Review of Financial Studies, 18: 1305–1342. [9] Britten‐Jones, M. and A. Neuberger, 2000. “Option prices, implied price processes, and stochastic volatility.” The Journal of Finance, 55:839-866. [10] Andersen, T.G., P. Frederiksen, and A.D. Staal, 2007. “The information content of realized volatility forecasts.” Working paper. [11] Tsiaras, L., 2009. “The forecast performance of competing implied volatility measures: The case of individual stocks.” Working paper. [12] Diavatopoulos, D., J.S. Doran, and D.R. Peterson, 2008. “The information content in implied idiosyncratic volatility and the cross‐section of stock returns: Evidence from the option markets.” Journal of Futures Markets, 28: 1013–1039. [13] Taylor, S.J., P.K. Yadav, and Y. Zhang, 2010. “The information content of implied volatilities and model-free volatility expectations: Evidence from options written on individual stocks.” Journal of Banking & Finance, 34: 871-881. [14] Carr, P. and D. Madan, 1998. “Towards a theory of volatility trading.” in R. Jarrow (ed.), Volatility: New Estimation Techniques for Pricing Derivatives. Risk Books, London, 417-427. [15] Yu, W.W., E.C.K. Lui, and J.W. Wang, 2010. “The predictive power of the implied volatility of options traded OTC and on exchanges.” Journal of Banking & Finance, 34: 1–11. [16] Bali, T.G., J. Hu, and S. Murray, 2019. “Option implied volatility, skewness, and kurtosis and the cross-section of expected stock returns.” Working paper. [17] Hollstein F., and M. Prokopczuk. 2016. “Estimating beta.” Journal of Financial and Quantitative Analysis, 51: 1437-1466. [18] Buss, A. and G. Vilkov, 2012. “Measuring equity risk with option-implied correlations.” The Review of Financial Studies, 25: 3113-3140. [19] Fama, E.F. and J.D. MacBeth, 1973. “Risk, return, and equilibrium: Empirical tests.” Journal of Political Economy, 81: 607-636. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/21531 | - |
| dc.description.abstract | 本篇研究首先檢驗了無模型假設波動度的預測能力,接著我們將研究重點延伸到高階動差資訊的探討。我們的實證結果指出,三階動差含有部分無模型假設波動度所沒有的資訊,但四階動差則不能有效預測未來波動度。另外,本篇研究也將無模型假設動差進行拆解,並比較系統性和非系統部分的預測表現。我們的研究結果顯示,非系統性部分波動度之個別預測能力優於系統性部分,不過另一方面,系統性及非系統性部分波動度具有不同的資訊含量,兩者都可以用於預測未來波動度。 | zh_TW |
| dc.description.abstract | In this paper, we first examine the forecasting power of the model-free volatility, and then we extend our study by investigating the information content of the higher moments. Our results suggest that skewness contains some information other than the model-free volatility while kurtosis seems to be an inefficient forecast for the realized volatility. This paper also decomposes the model-free moments and compares the predicting performance of the systematic and the unsystematic parts. Our findings suggest that unsystematic volatility generally outperforms the systematic part of the volatility. However, the results also show that both parts of the volatility contain useful information that can be used to predict the realized volatility. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-08T03:36:59Z (GMT). No. of bitstreams: 1 ntu-108-R06723024-1.pdf: 928559 bytes, checksum: bbb4927a583b4b49794e4ae64975fdfe (MD5) Previous issue date: 2019 | en |
| dc.description.tableofcontents | 第一章 緒論 1
1.1 研究動機 1 1.2 研究流程與架構 2 第二章 文獻回顧 3 2.1 選擇權隱含波動度之預測能力 3 2.2 無模型假設波動度 5 第三章 研究樣本與資料來源 6 第四章 研究方法 7 4.1 建構波動度指標 7 4.1.1 真實波動度與歷史波動度 7 4.1.2 OptionMetrics隱含波動度 8 4.1.3 無模型假設動差之計算 8 4.1.4 無模型假設動差之拆解 10 4.2 真實波動度之預測 12 4.2.1 迴歸方法與樣本選擇 12 4.2.2 波動度指標之預測能力比較 13 4.2.3 無模型假設波動度之系統性與非系統性部分預測能力比較 14 4.2.4 無模型假設高階動差之預測能力 15 第五章 實證結果與分析 17 5.1 敘述性統性量 17 5.2 以波動度指標預測之迴歸結果 19 5.3 以高階動差預測之迴歸結果 22 5.4 以系統性與非系統性動差預測之迴歸結果 23 第六章 結論 27 參考文獻 28 附錄-BKM隱含波動度公式 30 | |
| dc.language.iso | zh-TW | |
| dc.title | 無模型假設波動度之預測能力 | zh_TW |
| dc.title | The Predictive Power of the Model-Free Volatility | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 107-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 盧佳琪(Chia?Chi Lu),蔡芸琤(Yun-Cheng Tsai) | |
| dc.subject.keyword | 波動度預測,隱含波動度,無模型假設波動度,高階動差,系統性波動度, | zh_TW |
| dc.subject.keyword | Volatility forecasting,Implied volatility,Model-free volatility,Higher moments,Systematic volatility, | en |
| dc.relation.page | 31 | |
| dc.identifier.doi | 10.6342/NTU201901744 | |
| dc.rights.note | 未授權 | |
| dc.date.accepted | 2019-07-24 | |
| 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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