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研究生:柯政宏
研究生(外文):Jang-Hung Ke
論文名稱:CBOE新編VIX指數於台指選擇權及實現波動度預測上之應用
論文名稱(外文):作者未提供
指導教授:盧陽正盧陽正引用關係吳靖東吳靖東引用關係
指導教授(外文):作者未提供作者未提供
學位類別:碩士
校院名稱:銘傳大學
系所名稱:財務金融學系碩士在職專班
學門:商業及管理學門
學類:財務金融學類
論文種類:學術論文
論文出版年:2004
畢業學年度:92
語文別:中文
論文頁數:92
中文關鍵詞:波動度指數波動度交換隱含波動度波動度預測台指選擇權
外文關鍵詞:Volatility swapsVolatility ForecastTAIEX OptionsVIXImplied Volatility
相關次數:
  • 被引用被引用:62
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  • 下載下載:232
  • 收藏至我的研究室書目清單書目收藏:7
波動度的變化是金融資產的風險來源之一,對於衍生性金融商品的定價、避險、交易策略擬定以及風險控管,扮演一個相當重要的角色。芝加哥選擇權交易所 (CBOE) 於1993年推出由S&P100選擇權隱含波動度計算之波動度指數 (VIX Index),因其標準化的特性而廣為市場所接受。然隨著財務理論的發展及為了更貼近市場,CBOE 於2003年9月以Volatility & Variance swaps 的觀念,重新編制以S&P500選擇權為標的之VIX指數。而後更進一步成立期貨交易所 (CFE),於2004年3月26日推出第一個波動度期貨商品(VIX futures),於2004年5月18日推出第二個波動度相關期貨商品(Variance futures)。
國內已於2001年12月推出台指選擇權,市場規模正逐步擴大之中,然至目前尚無廣為接受的波動度指標,本文以CBOE新編制VIX指數之公式應用臺指選擇權市場,同時與歷史波動度、隱含波動度、GARCH 模型比較對台指期貨未來真實波動度之預測能力。此外,再加入交易量為解釋變數,以及使用日內資料為樣本,檢視是否能提高對真實波動度的預測績效。最後並檢測應用於台指選擇權之VIX指數與台指期貨之關係。所得結論如下:
1. 在市場不成熟的階段,隱含波動度模型與VIX模型可能因交易量偏低,導致不合理之價格跳動,而無法獲得有效之預測能力。
2. 於交易量穩定之市場成熟期,各種波動度模型之預測績效均大幅提升。預測績效最佳的是VIX指數,VIX指數是以所有價外合約之買、賣權計算,更能反應整體選擇權市場對於真實波動度的預期。
3. 加入期貨交易量為解釋變數後,僅在市場不成熟階段能提高預測能力,於市場成熟期則無有效提升模型的解釋能力。在改以選擇權交易量為新增解釋變數的話,於市場成熟期則可以小幅提升預測模型之解釋能力。
4. 使用日內資料預測未來之真實波動度,在流動性不佳的情況下,將會擷取到更多不合理的選擇權價格,使VIX模型與隱含波動度模型之解釋能力降低•而於交易量穩定之市場成熟期,使用日內資料可使隱含波動度模型及VIX模型提高對未來真實波動度之預測能力。
5. 台指期貨報酬與VIX指數之變動呈現反向關係,但兩者之關係並非對稱,台指期貨下跌導致VIX指數產生的變動大於因台指期貨上漲使VIX指數產生的變動。
Since the uncertainty of volatility is part of financial assets risk, it becomes an important role for derivatives pricing, hedging, and risk management. In 1993, the Chicago Board Options Exchange (CBOE) introduced the Volatility Index (VIX) of S&P 100, and it quickly became the benchmark for stock market volatility. After ten years later, theorists and practitioners alike have changed the way they think about volatility. CBOE update the VIX methodology from volatility and variance swaps. The Chicago Board Options Exchange (CBOE) newly created CBOE Futures Exchange (CFE) opened for trading on March 26, 2004. The first product listed on CFE is VIX futures. Then, variance futures based on the realized variance of the S&P 500 index over a three-month period were following on May 18, 2004.
On December 24, 2001, the first options contract based on Taiwan stock index was listed on the TAIFEX; moreover, the market scale is growing until now. However, Taiwan options market is still lack of a standard volatility index. In this research, we applied the new formula of VIX index to calculate a specific volatility scale of Taiwan index options, and tested the forecasting power of VIX index with historical volatility, implied volatility and GARCH model. Besides, the study added trading volume and used intraday data in the volatility models to examine forecasting power. The major empirical results are shown as follows.
1. During the initial developing of Taiwan options market, the irrational price movement, caused by the low trading volume, maybe downgrades the forecasting power of implied volatility and VIX index.
2. In the developed stage of options market, the forecasting power of all volatility models is upgraded. VIX is the best estimator, since the VIX estimates expected volatility from the prices of stock index options in a wide range of strike prices, not just at-the-money strikes as in the implied volatility.
3. Futures trading volume could not increase the forecasting power, except the developing stage. By contrast, when options trading volume were added in the models, the forecasting performance increases.
4. In the low liquidity stage, intra-day data would acquire more irrational options price; therefore, implied volatility model and VIX have a lower forecasting power of realized volatility. In the developed stage, however, with intra-day data the implied volatility and VIX have a better forecasting power of realized volatility.
5. The VIX of Taiwan index options and the return of FITX (Taiwan stock index futures) have negative relationship. However, negative returns for the stock index yield much larger relative changes in the implied volatility index than do positive returns.
目 錄


第一章 緒論
第二節 研究背景 ………………………………….…..……….…… 1
第三節 研究動機 ………………………………….…..……….…… 3
第四節 研究目的 …………………………………………………….4

第二章 文獻探討
第一節 波動度之相關文獻.………………………..…..……..……… 5
第二節 波動度指標之相關研究.…….…………….…..……..……… 9
第三節 波動度模型預測能力………………………………..………11
第四節 波動度與交易量……………………………………..………13

第三章 研究方法
第一節 波動度的估計.…………………………….…..….…….…....15
第二節 波動度模型預測能力之比較……….…………….…………23

第四章 實證分析
第一節 資料來源與選取.…………..…………….……….………….25
第二節 波動度模型預測能力之比較分析..…………….…..……….28
第三節 加入交易量之波動度預測…………………………………..49
第四節 使用日內資料之檢定……………….…………..…….……..55
第五節 台指期貨與VIX指數之關係……………………….………59

第五章 結論與建議
第一節 結論.……………………..……………………..…….………66
第二節 建議………………………………………………….……….68

附錄一………………………………………………………………………….70
附錄二……………………………………………………………………….…72
附錄三……………………………………………………………………….…79
附錄四……………………………………………………………………….…80
參考文獻……………………………………………………………………….82
表 目 錄

表4-1:國內選擇權市場成交量比較表……………………..…….………….27
表4-2:不同期間真實波動度之基本統計量……………………..…………..29
表4-3:不同波動度預測模型之基本統計量…………………………………29
表4-4:預測5日真實波動度之迴歸分析……………………………………40
表4-5:預測10日真實波動度之迴歸分析………………………..…………41
表4-6:預測20日真實波動度之迴歸分析………………….……………….42
表4-7:預測30日真實波動度之迴歸分析………………………….……….43
表4-8:預測至選擇權到期日為止真實波動度(E RV)之迴歸分析………….44
表4-9:不同樣本期間各波動度預測模型之 比較表……………………..45
表4-10:各模型預測波動度之MAE比較表 (日資料)………..……………47
表4-11:各模型預測波動度之RMSE比較表 (日資料)……..…….….……48
表4-12:加入前一期之期貨交易量成長率後之迴歸係數表………………..51
表4-13:加入前一期之期貨交易量成長率後之 成長率…………………52
表4-14:加入前一期之選擇權交易量成長率後之迴歸係數………………..53
表4-15:加入前一期之選擇權交易量成長率後之 成長率………………54
表4-16:使用日內資料作波動度預測之迴歸分析………………….….…….57
表4-17:使用日內資料估計20RV之MAE……………………...…………..58
表4-18:使用日內資料估計20日RV之RMSE…………………….………58
表4-19:台指期貨極端值與所對應之VIX波動度指數…………………….62
表4-20:VIX波動度指數極端值時與所對應之台指期貨………….……….62
表4-21:指數報酬與波動度指數變動之迴歸分析………………..……...….63
表4-22:台指期貨、S&P500、NASDAQ100波動度指數之各百分位數….64
表5-1:S&P500、NASDAQ100、FITX波動度指數之相關係數表………..69
表A-1:CBOE波動度指數 (VXO) 選擇權序列選取表……………………70
表A-2:CBOE 波動度指數(VIX)期貨契約規格…………….……………….79
表A-3:CBOE S&P500三個月期變異數期貨契約規格…………………….80
圖 目 錄

圖1-1:台灣選擇權市場月成交量成長圖…………………………….……..…2
圖3-1:未來固定期間真實波動度之預測期間….…………..………….…….15
圖3-2:至選擇權到期日為止之真實波動度預測期間……………….………16
圖4-1:不同波度模型之預測值與未來5日真實波動度之走勢圖……….…30
圖4-2:不同波度模型之預測值與未來10日真實波動度之走勢圖…………31
圖4-3:不同波度模型之預測值與未來20日真實波動度之走勢圖…………32
圖4-4:不同波度模型之預測值與未來30日真實波動度之走勢圖………...33
圖4-5:不同波度模型預測值與至選擇權到期之真實波動度之走勢圖…….34
圖4-6:買權之隱含波動度變化圖…………………………………………….38
圖4-7:賣權之隱含波動度變化圖…………………………………….………38
圖4-8:S&P500指數及其波動度指數(VIX)走勢圖…………..………………59
圖4-9:S&P500指數及其波動度指數(VIX)分佈圖……………….…………59
圖4-10:S&P500指數報酬及其波動度指數變動分佈圖…………………….59
圖4-11:NASDAQ100指數及其波動度指數(VXN)走勢圖………………….60
圖4-12:NASDAQ100指數及其波動度指數(VXN)分佈圖…………………60
圖4-13:NASDAQ100指數報酬及其波動度變動分佈圖……………………60
圖4-14:台指期貨及其波動度指數走勢圖……………...……………………61
圖4-15:台指期貨及其波動度指數分佈圖………………...………………....61
圖4-16:台指期貨報酬及其波動度變動分佈圖…………………….………..61
圖5-1:S&P500、NASDAQ100、台指期貨之波動度指數走勢圖……….....69
李進生、鍾惠民、吳壽山 (1999),現階段台灣權證發行之問題解析與與避險策略之形成:檢討與因應,證券金融,第62期,1-28頁。
林佩蓉 (2000),Black-Scholes模型在不同波動性衡量下之表現-股價指數選擇權,東華大學企業管理研究所碩士論文。
莊益源、張鐘霖、王祝三(2003),波動率模型預測能力的比較-以台指選擇權為例,台灣金融季刊,第四輯第二期,41-63頁。
雪邧n、詹世煌、謝宗祐 (2000),選擇權波動性與標的資產歷史波動性及選擇權參數之關聯性, 亞太管理評論,第5期,385~401頁。
陳煒朋 (1999),GARCH模型與隱含波動性模型預測能力之比較,淡江大學財務金融所碩士論文。
薛吉廷 (1999),隱含波動性預測品質之解析:台灣及美國市場之實證,淡江大學財務金融研究所碩士論文。
曹金泉 (1999),隨機波動度下選擇權評價理論的應用-以台灣認購權證為例,政治大學金融研究所碩士論文。

Andersen, T. G. and T. Bollerslev, (1999), "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecast", International Economic Review, 39, 885-905.
Anthony, J., (1988), "The interrelation of stock and options market trading volume data", Journal of Finance, vol 43, pp949~964.
Barberis, N., Shleifer, A. and Vishny, R., (1998), "A Model of Investor Sentiment", Journal of Financial Economics, 49, pp. 307-343.
Black, F. and. M. Scholes, (1973), "The Pricing of Options and Corporate Liabilities", Journal of Political Economy ,81:3,637-54.
Black, F, (1976), "Studies of Stock Price Volatility Changes, Proceedings from the American Statistical Association", Business and Economics Statistics Section. 177-181.
Bollerslev, T., (1986), "Generalized Autoregressive Conditional Heteroscedasticity", Journal of Econometrics , 31, 307-327.
Brooks, C., (1998), "Prediciting Stock Index Volatility: Can Market Volume Help?", Journal of Forecasting , 17, 59-80.
Canina, L. and S. Figlewski, (1993), "The Informational Content of Implied Volatility", The Review of Financial Studies ,6:3, 659-681.
Chang, R., Chou, Y. E. & Nelling, F. E. (2000), "Market Volatility and the Demand for Hedging in Stock Index Futures", The Journal of Futures Market, Vol. 20, pp.105-125.
Chen, N. F., Cuny, J. C. & Haugen, A. R. (1995), "Stock Volatility and the Levels of the Basis and Open Interest in Futures Contracts", The Journal of Finance, Vol.12, No.1, pp.281-300.
Chiras, D. P. and S. Manaster, (1978), "The Information Content of Option Prices and a Test of Market Efficiency", Journal of Financial Economics, pp213-234.
Christensen B.J. and N. R. Prabhala (1998), "The Relation between Implied and Realized Volatility", Journal of Financial Economics, vol..50, 125-150.
Claessen, H. and Mittnik, S., (2002), "Forecasting stock market volatility and the informational efficiency of the DAX-index options market", The European Journal of Finance, vol 8, pp302~321.
Copeland, Maggie. and Thomas Copeland, (1999), "Market Timing: Style and Size Rotation Using the VIX", Financial Analysts Journal, Vol.55, Mar/Apr 1999, pp. 73-81.
Cox, J., S. Ross, and M. Rubinstein, (1979), "Option Pricing: A New Approach", Journal of Financial Economics, Vol. 7, pp.229-264, October.
Day, T. E. and C. M. Lewis (1993), "Forecasting Futures Market Volatility", Journal of Derivatives, 1, 33-50.
Derman, E., M. Kamal, I. Kani, J. McClure, and J. Zou (1998), "Investing in Volatility", Journal of Derivatives 7-11.
Duan, J., (1995), "The GARCH Option Pricing Model", Mathematical Finance, 5, 13- 32.
Ederington, Louis H. and Jae Ha Lee, (1996), "The creation and resolution of market uncertainty: The impact of information releases on implied volatility", Journal of Financial and Quantitative Analysis 31, 513-539.
Ederington, Louis H. and Jae Ha Lee, (1993), "How markets process information: News releases and volatility", Journal of Finance 48, 1161-1191.
Engle, R.,(1982), "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of UK Inflation", Econometrica 50, pp.987-1108.
Engle, R. and V. Ng, (1993), "Measuring and Testing of the Impact of News on Volatility", Journal of Finance, 48, 1749-1778.
Epps, T.W. (1975), "Security Price Changes and Transaction Volumes: Theory and Evidence", American Economic Review 65:586-597.
Figlewski, S., and X. Wang (2000), "Is the “Leverage Effect” a Leverage Effect? ", Working Paper S-00-37, New York University, Stern School of Business.
Fitzgerald, D. (1999), "Trading Volatility", Risk Mangement and Analysis. Vol.2: New Market and Products, Edited by C. Alexander, 261-291.
Finnerty, J. E., (1978), "The CBOE and Market Efficiency", Journal of Financial and Quantitative Analysis, March 1978, pp29-38.
Fleming, J., B., Ostdiek, and R., E., Whaley, (1995), "Predicting Stock Market Volatility: A New Measure", Journal of Futures Markets, 15, 265-302.
Fleming, J. (1998), "The Quality of Market Volatility Forecasts Implied by S&P100 Index Options Prices", Journal of Empirical Finance , 5,317-345.
Gemmill, G., (1986), "The forecasting performance of stock options on the London Traded Options Marker", Journal of Business Finance and Accounting, vol 13, pp535~546.
Gemmill, G. (1996), "Did Option Traders Anticipate the Crash? Evidence from Volatility Smiles in the U.K. with U.S. Comparisons", Journal of Futures Markets, 16, 881-897.
Giot, P. (2002a), "Implied Volatility Indices as Leading Indicators of Stock Index Returns? ", Working Paper, CORE, University of Leuvain.
Giot, P. (2002b), "The Information Content of Implied Volatility Indexes for forecasting Volatility and Market Risk", Working Paper, CORE, University of Leuvain.
Gwilym, O. A. and Buckle, M., (1999), "Volatility forecasting in the framework of the option expiry circle", European Journal of Finance, vol 5, pp73~94.
Gwilym, O. A., (2001), "Forecasting volatility for options pricing for the U.K stock market", Journal of Financial Management and Analysis, vol 14, pp55~62.
Harvey, C.R.; and R. E. Whaley (1991), "S&P100 Index Option Volatility", The Journal of Finance , 46:4,1551-1561.
Hull, John and Alan White, (1987), "The Pricing of Options on Assets with Stochastic Volatilities", Journal of Finance, Vol. 42, pp.281-300.
Jorion, P. (1995), "Predicting Volatility in Foreign Exchange Market", Journal of Finance Vol.50, 507-528.
Karpoff, J., (1987), "The relation between price changes and trading volume: a survey", Journal of Financial and Quantitative Analysis, vol 22, pp109~123.
Kawaller, I.G.; Koch, P.D.; and Peterson, J.E. (1994), "Assessing the Intraday Relationship between Implied & Historical Volatility", The Journal of Futures Markets 14(3):323-346.
Kim, O. and R. Verrecchia, (1994), "Market Liquidity and Volume Around Earnings Announcements", Journal of Accounting and Economics, Vol. 17, pg. 41-67.
Lamoureux, C. G. and W. D. Lastrapes (1990), "Heteroscedasticity in Stock Return Data: Volume versus GARCH Effects", The Journal of Finance ,45:1, 221-229.
Lamoureux, C. G. and W. D. Lastrapes (1993), "Forecasting Stock-Return Variance: Toward an Understanding of Stochastic Implied Volatility", The Review of Financial Studies, 6:2, 293-326.
Latane, Henry A., and Richard J. Rendleman, Jr., (1976), "Standard deviations of stock price ratios implied in options price", Journal of Finance, 31, 361-381.
Mandelbrot, B., (1963), “The Variation of Certain Speculative Prices", Journal of Business, 36, pp. 394-419.
Macbeth, J., L. Mervile(1979), "An Empirical Examination of the Black-Scholes Call Option Pricing Model", Journal of Finance,Vol.34, No.5, pp.1173-1186.
Nofsinger, John R. and Brian Prucyk, (2003), "Option Volume and Volatility Response to Scheduled Economic News Releases", Journal of Futures Markets, vol. 23, no. 4 (April 2003):315–345.
Rubinstein, M.(1985), "Nonparametric Tests of Alternative Option Pricing Models Using All Reported Trades and Quotes on the 30 Most Active CBOE Option Classes from August 23,1976 through August 31,1978", Journal of Finance, Vol. 40, pp.455-480.
Rubinstein, M., (1994), " Implied Binomial Trees", Journal of Finance, 49, 771-818.
Simon, David P. (2003), "The Nasdaq Volatility Index during and after the Bubble", Journal of Derivatives vol. 11, no. 2 (Winter 2003):9–24.
Schmalense, R. and R. R. Trippi (1978), "Common Stock Volatility Expectation by Option Premia", Journal of Finance, Mar 1978, pp. 129-147.
Szakmary Andrew, Evren Ors, Jin Kyoung Kim, Wallace N. Davidson (2002), "The predictive power of implied volatility : Evidence from 35 futures market", Journal of Banking & Finance , 27, 2151-2175.
Tom Holland (2003), "Risk Appetite", Far Eastern Economic Review, Issue cover-dated October 09, 2003.
Traub, Heydon, Luis Ferreira, Maria McArdle and Mauro Antognelli,(2000), "Fear and Greed in Global Asset Allocation", The Journal of Investing, Vol.9, No. 1, Spring 2000 pp.21-37.
Veronesi, Pietro (1999), "Stock Market Overreaction to Bad News in Good Times: A Rational Expectations Equilibrium Model", Review of Financial Studies, Vol. 12, 975-1007.
Whaley, Robert E., (1981), "On the valuation of American futures options: Theory and empirical tests", Journal of Financial Economics, 9, 127-150.
Whaley, R., E., (1993), "Derivatives on Market Volatility: Hedging Tools Long Overdue", Journal of Derivatives, 1, 71-84.
Whaley, R., E. (2000), "The Investor Fear Gauge", Journal of Portfolio Management, 26, 12-17
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