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System No. U0002-2806202211561700
DOI 10.6846/TKU.2022.00803
Title (in Chinese) 臺指選擇權波動率偏差對臺股期貨報酬率之預測能力
Title (in English) The Predictive Power of Options Implied Volatility Skewness on TAIEX Futures Return
Other Title
Institution 淡江大學
Department (in Chinese) 財務金融學系碩士班
Department (in English) Department of Banking and Finance
Other Division
Other Division Name
Other Department/Institution
Academic Year 110
Semester 2
PublicationYear 111
Author's name (in Chinese) 邱孟杰
Author's name(in English) Meng-Chieh Chiu
Student ID 609530067
Degree 碩士
Language Traditional Chinese
Other Language
Date of Oral Defense 2022-06-10
Pagination 41page
Committee Member advisor - William T. Lin(103705@mail.tku.edu.tw)
co-advisor - 蔡蒔銓(chuant@ntnu.edu.tw)
co-chair - 李文柱
co-chair - William T. Lin
co-chair - 邱文昌
Keyword (inChinese) 隱含波動率
期貨報酬預測
波動率偏差
價性
Keyword (in English) Implied Volatility
Futures return
Skewness
Other Keywords
Subject
Abstract (in Chinese)
本研究主要為探討臺指選擇權波動率偏差對臺股期貨報酬之預測能力。依循Doran, Peterson, and Tattant (2007) 與 Xing, Zhang, & Zhao (2010) 所提出的價外選擇權隱含波動率偏差,並加入流動性代理變數來觀察價外選擇權隱含波動率偏差對臺股期貨報酬是否有預測能力。
  研究中,參照Xing et al. (2010) 的價性定義,根據篩選出流動性最佳且最適當的價外賣權與價外買權。對於各市場的不同的搓合機制,本研究以重建揭示檔的方式來避免資料時間不同的問題。最後本研究採用穩健性檢定,檢驗在不同時間區間的情況下,價外選擇權波動率偏差對臺股期貨報酬率是否尚有預測之能力。
  實證結果發現,價外賣權波動率偏差對臺股期貨報酬之預測能力有顯著相關,且符合 Xing et al. (2010) 的研究結果呈現負向的顯著關係;而價外買權波動率偏差對臺股期貨報酬率之預測能力有正向顯著相關,且在穩健性檢定結果中也再次證實。於高波動期間時,價外賣權波動率偏差對臺股期貨報酬具預測能力;價外買權則無。顯示在散戶為主之臺灣期貨市場,交易人通常會交易價外股指賣權作為空頭市場的交易策略。最後,本研究透過回測來證實波動率偏差的可預測性,價外賣權波動率偏差進行交易所獲得的平均日報酬(0.4729%)遠高於價外買權波動率偏差(0.0193%)且穩定。
Abstract (in English)
This study mainly explores the ability of out-of-the-money option volatility skewness to predict Taiwan stock futures return. Follow the implied volatility skewness of out-of-the-money options proposed by Doran, Peterson, and Tattant (2007) and Xing, Zhang, & Zhao (2010), and add liquidity proxy variables to discuss the out-of-the-money options implied volatility skewness whether it has the ability to predict on TAIEX futures return. 
In the study, referring to the definition of moneyness by Xing et al. (2010), the best liquidity and the most appropriate out-of-the-money call options and out-of-the-money put options are screened out. Finally, this study uses robustness test to test whether the implied volatility skewness of out-of-the-money options has the ability to predict the TAIEX futures return in different time intervals.
The empirical results show that the implied volatility skewness of out-of-the-money put options has a significant correlation with the forecasting ability of TAIEX futures returns, which is in line with the research results of Xing et al. The implied volatility skewness of out-of-the-money call options has a positive and significant correlation with the predictive power of TAIEX futures return, which is also confirmed in the robustness test results. Based on the above research results, it can be concluded that the implied volatility skewness of out-of-the-money options has a certain predictive power for TAIEX futures return.
Other Abstract
Table of Content (with Page Number)
第一章	緒論	1
第一節	研究背景與動機	1
第二節	研究目的	3
第三節	研究架構	4
第四節	研究流程	5
第二章	文獻探討	6
第一節	預測報酬率之相關文獻	6
第二節	選擇權資訊內涵之相關文獻	7
第三章	研究方法	9
第一節	選擇權市場結構概述	9
第二節	樣本資料篩選	11
第三節	理論實證與分析	16
第四節	變數設定	21
第五節	迴歸模型設定	24
第四章	實證結果與分析	27
第一節	敘述統計分析	27
第二節	迴歸統計分析	30
第五章	結論	38
第六章	參考文獻	40
 
表目錄
【表3-1】 2010 年至 2012 年臺灣選擇權市場年成交量統計表	10
【表3-2】臺指選擇權各月份合約每日平均成交量占比	14
【表3-3】委託至成交所需時間統計表--買權	14
【表3-4】委託至成交所需時間統計表—賣權	14
【表3-5】TXO_VIX恐慌指數敘述統計表	26
【表4-1】ADF單根檢定結果	28
【表4-2】價外賣權隱含波動率偏差主要變數敘述統計表	28
【表4-3】價外買權隱含波動率偏差主要變數敘述統計表	29
【表4-4】價外賣權隱含波動率偏差對臺股期貨報酬之影響	30
【表4-5】價外買權隱含波動率偏差對臺股期貨報酬之影響	31
【表4-6】高波動區間對一般區間CHOW檢定統計表	32
【表4-7】高波動區間波動率偏差對臺股期貨報酬之影響	33
【表4-8】不同時間區間賣權波動率偏差之穩健性檢定	34
【表4-9】不同時間區間買權波動率偏差之穩健性檢定	34
【表4-10】不同價性篩選下波動率偏差對臺股期貨報酬之影響	35
 
圖目錄
【圖1-1】研究流程	5
【圖3-1】價外賣權價性最大成交量次數	12
【圖3-2】價外買權價性最大成交量次數	12
【圖3-3】時間序列之檢定分析流程	16
【圖3-4】TXO_VIX恐慌指數分布圖	26
【圖4-1】價外賣權波動率偏差之日報酬率	36
【圖4-2】價外買權波動率偏差之日報酬率	36
【圖4-3】價外賣權波動率偏差之總報酬率	36
【圖4-4】價外買權波動率偏差之總報酬率	37
References
1.	詹錦宏, & 施介人. (2005). 台股指數現貨, 期貨與選擇權價格發現之研究. 台灣金融財務季刊, 6(1), 31-51.
2.	Back, K. (1993). Asymmetric information and options. The Review of Financial Studies, 6(3), 435-472.
3.	Biais, B., & Hillion, P. (1994). Insider and liquidity trading in stock and options markets. The Review of Financial Studies, 7(4), 743-780.
4.	Black, F., & Scholes, M. (1973). The pricing of options and corporate liabilities. Journal of political economy, 81(3), 637-654.
5.	Cao, M., & Wei, J. (2010). Option market liquidity: Commonality and other characteristics. Journal of Financial Markets, 13(1), 20-48.
6.	Chen, W. P., Chung, H., & Lien, D. (2016). Price discovery in the S&P 500 index derivatives markets. International Review of Economics & Finance, 45, 438-452.
7.	Diebold, F. X., & Strasser, G. (2013). On the correlation structure of microstructure noise: A financial economic approach. Review of Economic Studies, 80(4), 1304-1337.
8.	Doran, J. S., Peterson, D. R., & Tarrant, B. C. (2007). Is there information in the volatility skew?. Journal of Futures Markets: Futures, Options, and Other Derivative Products, 27(10), 921-959.
9.	Fernandez‐Perez, A., Frijns, B., Gafiatullina, I., & Tourani‐Rad, A. (2018). Determinants of intraday price discovery in VIX exchange traded notes. Journal of Futures Markets, 38(5), 535-548.
10.	Ge, L., Lin, T. C., & Pearson, N. D. (2016). Why does the option to stock volume ratio predict stock returns?. Journal of Financial Economics, 120(3), 601-622. 
11.	Lin, W. T., Tsai, S. C., & Chiu, P. (2016). Do foreign institutions outperform in the Taiwan options market?. The North American Journal of Economics and Finance, 35, 101-115.
12.	Lin, W. T., Tsai, S. C., Zheng, Z., & Qiao, S. (2017). Does options trading convey information on futures prices?. The North American Journal of Economics and Finance, 39, 182-196
13.	Pan, J., & Poteshman, A. M. (2006). The information in option volume for future stock prices. The Review of Financial Studies, 19(3), 871-908.
14.	Xing, Y., Zhang, X., & Zhao, R. (2010). What does the individual option volatility smirk tell us about future equity returns?. Journal of Financial and Quantitative Analysis, 45(3), 641-662.
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