本研究將台灣期貨與選擇權市場進行綜合比較，透過這兩種市場都擁有用來衡量衍生性商品價格對標的價格敏感程度的風險參數─Delta來研究分析交易者的資訊內涵。探討各類型交易人市場取得Delta時點(Market timing)的優劣以及應用Chang, Hsieh and Wang (2010)延用Ni et al., (2008)的方法，來計算當天台指期貨與台指選擇權的淨Delta，了解投資人對未來報酬的預測能力來觀察其是否為資訊交易者。
由於選擇權市場有造市者提供市場流動性，故特別把造市者下單情況做為討論之一，觀察其交易行為是否有別於其他投資人，結果發現選擇權造市者主要為市場提供流動性，其預測能力不顯著，表示造市者的交易行為對於未來報酬並無預測能力。
     本研究顯示開倉較具有資訊性，由開倉部位來分析，發現只交易期貨以及期選皆交易的外資為方向性資訊交易者。自營商若操作當沖交易獲利機會極大，但在留倉判斷的錯誤訊息導致其預測能力不佳。在散戶方面，只交易期貨、只交易選擇權以及期選皆交易的散戶對未來報酬預測皆不顯著，且不論是大額散戶或是小額散戶皆無對方向性的預測能力。而只交易選擇權市場部分的各類型交易人所持有之淨Delta對未來股市報酬的預測能力皆不顯著，原因在於只在擇權市場交易的投資人較不在意市場的方向性，其交易的目的關注於市場波動度的變化。
    此外，資料期間適逢金融海嘯之際，因此進一步探討各類型交易人在正常市場與市場恐慌時的交易行為是否有差異，結果發現在金融海嘯期間，大部分投資人都有受到衝擊，包含國內法人、小額散戶與造市者，外資除外。且小額散戶受到的金融海嘯的影響顯著大於大額散戶，故本文將散戶歸納為雜訊交易者。

n this paper, we apply the method of Chang, Hsieh and Wang (2010) to investigate the information content of Delta to examine the market timing and the predictive power of different types of traders in the TAIEX futures and options markets on stock market return. We also discuss the impact of financial crisis how to affect the traders.
   After the market timing and regression analysis about predictability, this paper finds that foreign institutional investors who trade in only futures market and in both futures and options markets (FF and CF) are the informed traders on the stock market return. Dealers (CS) have wrong information about future return in our result. Market makers’ (OM) major purpose is providing liquidity, so their predictability is not significant. Besides, we also find that individual investors have no the predictive power of the future return. For this reason, we define individual investors as noise traders. 
   In the period of financial crisis, most of investors had been influenced, including domestic institutional investors, small individual investors and market makers. And we find foreign investors could not be impacted in this period. Our empirical results show that foreign institutional investors who trade in only futures market and in both futures and options markets (FF and CF) possess the strongest and most direct information.

目錄
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	5
第二章 文獻探討	7
第一節 不同市場之投資行為訊息反應	7
第二節 不同類型投資人之資訊性	11
第三節 資訊交易者之投資策略	14
第四節 金融危機對投資人之影響	16
第三章 研究方法	18
第一節 衍生性商品市場結構簡介	18
第二節 資料來源與介紹	21
第三節 市場取得Delta時點的優劣比較	29
第四節 迴歸分析方法	32
第四章 實證結果與分析	36
第一節 資料敘述統計分析	36
第二節 各類型投資人市場取得Delta時點優劣之分析	40
第三節 基本迴歸模型分析	45
第四節 金融海嘯的影響	58
第伍章 結論	67
參考文獻	69

 
表目錄
【表3-1】  2010年全球與我國期貨商品交易量統計	19
【表3-2】  台灣期貨市場外資投資比重	20
【表3-3】  期貨商品內容簡介	22
【表3-4】  期貨成交檔資料格式	23
【表3-5】  選擇權成交檔資料格式	24
【表4-1】  市場敘述統計表	36
【表4-2】  交易人分類敘述統計表(不分帳號)	37
【表4-3】  交易人分類敘述統計表(分帳號)	38
【表4-4】  各類型交易人每日淨Delta之平均數	39
【表4-5】  各類型交易人當日交易可能獲得報酬之帳戶比率平均以及帳戶內未實現損益之平均	41
【表4-6】  各類型交易人當日交易可能獲得報酬之帳戶比率異同之檢定	41
【表4-7】  兩不同類型交易人當日從事交易可能獲得報酬帳戶比之平均數t檢定表	43
【表4-8】  兩不同類型交易人帳戶裡未實現損益之平均數t檢定表	44
【表4-9】  對未來報酬預測分析(不分開平倉)	48
【表4-10】 交易人於現貨市場與衍生性商品市場所持有部位之相關係數	49
【表4-11】 對未來報酬預測分析(開倉)	52
【表4-12】 對未來報酬預測分析(平倉)	53
【表4-13】 對未來報酬預測分析(各類型投資人綜合分析)	56
【表4-14】 對未來報酬預測分析之金融海嘯影響(不分開平倉)	60
【表4-15】 對未來報酬預測分析之金融海嘯影響(開倉)	62
【表4-16】 對未來報酬預測分析之金融海嘯影響(平倉)	63
【表4-17】 對未來報酬預測分析之金融海嘯影響(各類型投資人綜合分析)	65
 
圖目錄
【圖1-1】 研究流程圖	6
【圖3-1】 期貨市場機構投資人與一般投資人參與比重變化說明圖	20
【圖3-2】 台灣加權股價指數走勢圖	22
【圖3-3】 期貨價格配對說明圖	27

參考文獻
1.	黃敏助，(2009)，「當前資本市場改革之我見」，證券公會季刊，第2季，頁4~9。
2.	陳志娟、馬長峰、林蒼祥，(2012)，「機構投資者的交易行為研究：來自台灣股市的證據」，商業經濟與管理，第3期 總第245期，頁52~64。
3.	Ashby, W. R., (1956), An Introduction to Cybernetics, London: Chapman & Hall Press.
4.	Bakshi, G., C. Cao, and Z. Chen, (1997), “Empirical Performance of Alternative Option Pricing Models,” Journal of Finance, Vol.52, pp.2003-2049.
5.	Barber, B. M., Y. T. Lee, Y. J. Liu, and T. Odean, (2009), “Just How Much Do Individual Investors Lose by Trading?” Review of Financial Studies, Vol.22, pp.609-632. 
6.	Barclay, M. J. and J. B. Warner, (1993), “Stealth and Volatility: Which Trades Move Prices?” Journal of Financial Economics, Vol.34, pp.281-306.
7.	Black, F. and M. Scholes, (1973), “The Pricing of Options and Corporate Liabilities,” Journal of political economy, Vol.81, pp.637-654. 
8.	Bollen, N. B. P., and R. Whaley, (2004), “Does Net Buying Pressure Affect the Shape of Implied Volatility Function?” Journal of Finance, Vol.59, pp.711-753.
9.	Booth, G. G., R. W. So, and Y. Tse, (1999), “Price Discovery in the German Equity Index Derivatives Markets,” Journal of Futures Markets, Vol.19, pp.619-643.
10.	Calcagno, R. and S. Lovo, (2006), “Bid-Ask Price Competition with Asymmetric Information between Market Makers,” Review of Economic Studies, Vol.73, pp.329-355.
11.	Chan, K., (1992), “A Further Analysis of the Lead-lag Relationship between the Cash Market and Stock Index Futures Market,” Review of Financial Studies, Vol.5, pp.123-152.
12.	Chan, K. C., L. T. W. Cheng, and P. P. Lung, (2004), “Net Buying Pressure, Volatility Smile, and Abnormal Profit of Hang Seng Index Options,” The Journal of Futures Markets, Vol.24, pp.1165-1194.
13.	Chan, K., Y. P. Chung, and W. M. Fong, (2002), “The Informational Role of Stock and Option Volume,” The Review of Financial Studies, Vol.15, pp.1049-1075. 
14.	Chang, C. C., P. F. Hsieh, and H. N. Lai, (2009), “Do Informed Option Investors Predict Stock Returns? Evidence from the Taiwan Stock Exchange,” Journal of Banking and Finance, Vol.33, pp.757-764. 
15.	Chang, C. C., P. F. Hsieh, and Y. H. Wang, (2010), “Information Content of Options Trading Volume for Future Volatility: Evidence from the Taiwan Options Market,” Journal of Banking and Finance, Vol.34, pp.174-183. 
16.	Chakravarty, S., H. Gulen, and S. Mayhew, (2004), “Informed Trading in Stock and Option Markets,” Journal of Finance, Vol.59, pp.1235-1257.
17.	Chen, A. C., H. G. Fung, and E. C. Kao, (2008), “The Dynamic Relations among Return Volatility, Trading Imbalance, and Trading Volume in Futures Markets,” Mathematics and Computers in Simulation, Vol.79, pp.429-436.
18.	Chen, C. R., P. P. Lung, and N. S. P. Tay, (2005), “Information Flow between the Stock and Option Markets: Where Do Informed Traders Trade?” Review of Financial Economics, Vol.14, pp.1-23.
19.	Chu, Q. C., G. W-L. Hsieh, and Y. Tse, (1999), “Price Discovery on the S&P 500 Index Markets: An Analysis of Spot Index, Index Futures, and SPDRs,” International Review of Financial-Analysis, Vol.8, pp.21-34.
20.	Close, N., (1975), “Price Reaction to Large Transaction in the Canadian Equity Market,” Financial Analyst Journal, Vol.31, pp.50-57.
21.	Cox, C. C., (1976), “Futures Trading and Market Information,” Journal of Political Economy, Vol.84, pp.1215-1237.
22.	Dennis, P. J. and J. P. Weston, (2001), “Who’s Informed? An Analysis of Stock Ownership and Informed Trading,” Working paper, University of Virginia.
23.	Easley, D. and M. O’Hara, (1987), “Price, Trade Size, and Information in Securities Markets,” Journal of Financial Economics, Vol.19, pp.69-90.
24.	Engle, R. F., (2000), “The Econometrics of Ultra‐high‐frequency Data,” Econometrica, Vol.68, pp.1-22. 
25.	Fahlenbrach, R. and P. Sandas, (2010), “Does Information Drive Trading in Option Strategies?” Journal of Banking and Finance, Vol.34, pp.2370-2385.
26.	Ghosh, A., (1993), “Cointegration and Error Correction Models: Intertemporal Causality between Index and Futures Prices,” Journal of Futures Markets, Vol.13, pp.193-198.
27.	Glosten, L. R., and P. R. Milgrom, (1985), “Bid, Ask, and Transaction Prices in a Specialist Market with Heterogeneously Informed Traders,” Journal of Financial Economics, Vol.14, pp.71-100.
28.	Hasbrouck, J., (1995), “One Security, Many Markets: Determining the Contributions to Price Discovery,” Journal of Finance, Vol.50, pp.1175-1199.
29.	Herbst, A., J. McCormack, and E. West, (1987), “Investigation of a Lead-lag Relationship between Spot Stock Indices and Their Futures Contracts,” Journal of Futures Markets, Vol.7, pp.373-381.
30.	Kang, J. and H. J. Park, (2008), “The Information Content of Net Buying Pressure: Evidence from the KOSPI 200 Index Option Market,” Journal of Financial Markets, Vol.11, pp.36-56.
31.	Kaul, G., Nimalendran, M., and D. Zhang, (2004), “Informed Trading and Option Spreads,” Working paper, University of Michigan.
32.	Kawaller, I., P. Koch, and T. Koch, (1987), “The Temporal Price Relationship between S&P 500 Futures and S&P 500 Index,” Journal of Finance, Vol.42, pp.1309-1329.
33.	Keynes, J. M., (1936), The General Theory of Employment Interest and Money, London: Macmillan.
34.	Kyle, A., 1985, “Continuous auctions and insider trading,” Econometrica, 53, 1315-1335. 
35.	Lee, J., and C. H. Yi, (2001), “Trade Size and Information-motivated Trading in the Options and Stock Market,” Journal of Financial and Quantitative Analysis, Vol.36, pp.485-501.
36.	Lee, Y. T., J. C. Lin, and Y. J. Liu, (1999), “Trading Patterns of Big versus Small Players in an Emerging Market: An Empirical Analysis,” Journal of Banking and Finance, Vol.23, pp.701-725. 
37.	Lee, Y. T., Y. J. Liu, R. Roll, and A. Subrahmanyam, (2004), “Order Imbalances and Market Efficiency: Evidence from the Taiwan Stock Exchange,”Journal of Financial and Quantitative Analysis, Vol.39, pp.327-341. 
38.	Le, V. and R. Zurbruegg, (2010), “The Role of Trading Volume in Volatility Forecasting,” Journal of International Financial Markets, Institutions and Money, Vol.20, pp.533-555.
39.	Liu, S., (2009), “The Impacts of Index Options on the Underlying Stocks: The Case of the S&P100,” The Quarterly Review of Economics and Finance, Vol.49, pp.1034-1046.
40.	Merton, R. C., (1995), “Financial Innovation and the Management and Regulation of Financial Institutions,” Journal of Banking and Finance, Vol.19, pp.461-481.
41.	Ni, S. X., J. Pan, and A. M. Poteshman, (2008), “Volatility Information Trading in the Option Market,” Journal of Finance, Vol.63, pp.1059-1091. 
42.	Pan, J. and A. M. Poteshman, (2006), “The Information in Option Volume for Future Stock Prices,” The Review of Financial Studies, Vol.19, pp.871-908
43.	Rappoport, P. W. and E. N. White, (1994), “The New York Market in the 1920s and 1930s: Did Stock Prices Move together Too Much?” Working Paper, No.4627. NBER(National Bureau of Economic Research Inc.).
44.	Pavabutr, P. and H. Yan, (2004), “Foreign Portfolio Flows and Emerging Market Return: Evidence from Thailand,” Working Paper.
45.	Schlag, C. and H. Stoll, (2005), “Price Impacts of Options Volume,” Journal of Financial Markets, Vol.8, pp.69-87.
46.	Shapira, Z. and I. Venezia, (2001), “Patterns of Behavior of Professionally Managed and Independent Investors,” Journal of Banking and Finance, Vol.25, pp.1573-1587. 
47.	Shleifer, A., (2000), “Inefficient Markets: An Introduction to Behavioral Finance,” Oxford, New York: Oxford University Press.
48.	Sprecher, C. R., and M. A. Pertl, (1983), “Large Losses, Risk Management and Stock Prices,” Journal of Risk and Insurance, Vol.50, pp.107–117.
49.	Stoll, H. and R. Whaley, (1990), “The Dynamics of Stock Index and Stock Index Futures Returns,” Journal of Financial and Quantitative Analysis, Vol.25, pp.441-468.
50.	Wahab, M. and M. Lashgari, (1993), “Price Dynamics and Error Correction in Stock Index and Stock Index Futures Markets: A Cointegration Approach,” Journal of Futures Markets, Vol.13, pp.11-742.
51.	Wrolstad, M. and T. Krueger, (2003), “The Impact of September 11 on Investors’ Risk aversion,” Journal of Investing, Vol.12, pp.72–77.
52.	Zhong, M., A. F. Darrat, and R. Otero, (2004), “Price Discovery and Volatility Spillovers in Index Futures Markets: Some Evidence from Mexico,” Journal of Banking and Finance, Vol.28, pp.3030-3054.