自1980年代初期全球金融市場開始發生大變革，全球各國先後解除利率與匯率的管制，進而強化了不同金融市場間的連動性。資訊與通訊科技的快速發展，也加速金融市場的變化與改革。隨著金融市場的不斷推陳出新，衍生出各式金融商品，使得金融體系結構相繼調整。此外，國際金融制度持續演化，無論是匯率、利率、股價、指數期貨，時時刻刻在波動。基此，本文希冀分別針對金融商品創新、政府調節與制度變革對金融市場的衝擊加以討論。
由於金融動態的日新月異與金融市場的蓬勃發展，人們對處理數據、訊息的能力大為提高，若想隨時掌握金融動態，更深入分析金融情勢波動原因，必須擁有處理大量數據的能力與技術。財務計量領域自二十世紀末期迅速發展，藉由財務計量模型，有助於提供基金管理者與投資者之投資評估決策、資產配置與風險管理之參考。財務計量模型是建立在某些先決假設條件的基礎上，利用計量方法，對金融管理當局採用金融政策、交易機制與引進新金融商品之影響進行實證研究，能對於各種金融議題提供深入探索。在金融理論與實證中已有許多研究應用計量經濟模型，來分析金融市場之變化。然本文的整體價值在於能夠效率且精確地運用財金計量模型之建構方法（包括自我迴歸遞延落差模型、日內跨期迴歸模型以及資訊分享模型）來剖析財金資訊。本文實證研究發現貨幣供給增加、期交稅調降、國安基金進場調節以及迷你期貨契約加入等因素發生變化時，分別對於金融市場之匯率、定價效率與資訊傳遞過程，產生顯著的影響與衝擊。研究更進一步發現，當貨幣供給增加時，台幣匯率不易發生短期的泡沫投機現象；此外，調降期交稅可增進市場效率、國安基金進場調節導致金融市場定價無效率；最後，研究亦發現迷你型期貨契約會主導羅素期貨市場資訊分享過程。綜言之，本論文結合財務金融理論與計量經濟模型，利用財經實際案例分析來貫穿理念；並以效率、簡單、具體步驟來分別探討外匯市場台幣匯率過度反應之情形與期貨市場之定價效率和資訊傳遞過程。
本論文包括三篇子題：第一部分為ARDL方法在外匯市場之運用，利用臨界區間法來檢測匯率與總體經濟變數是否存在長期均衡關係，並探討台灣貨幣供給的增加，對於匯率過度反應的情形。該子題之研究克服了變數間同時存在I(1)及I(0)整合級次不一致的問題，並提供證據讓進出口商瞭解台灣外匯市場非理性行為之特性以及台灣外匯市場在短期間之匯率過度波動的泡沫投機現象不易發生，進而有助於企業評估避險策略，以降低營運風險。第二部分應用虛擬變數之日內跨期迴歸模型來探討市場變革對台灣期貨市場的影響，實證研究發現政府採取期交稅調降政策能增進市場效率，國安基金進場調節導致妨礙市場效率。該子題之研究結果可提供新興衍生性市場之金融管理當局選擇施政措施與制度變革之參考，惟有採取適度的調節與公平合理的稅制，才能使市場價格機能充分運作。第三部分自電子化交易之迷你羅素2000推出後，尚未有研究探討羅素2000指數之傳統期貨與迷你期貨兩者間的價格動態關連性。本文利用資訊分享模型，發掘公開喊價之正規型指數期貨與電子化交易之迷你型指數期貨的資訊傳遞過程，主要貢獻在於發現迷你羅素2000期貨主導市場資訊傳遞能力，顯示電子化交易系統具資訊效率與運作效率的優勢。該子題之研究提供交易機制（公開喊價交易、電子化交易）與契約設計（傳統期貨、迷你期貨）一項有利的證據。對投資人而言，有助於投資羅素2000指數期貨之參考。對全球交易所而言，本文的例證支持政府當局將交易機制與契約規格設計做調整，的確有助於達到健全市場發展的目標。

Major changes in the global financial market began in the early 1980s. The lifting of restrictions on interest rates and exchange rates strengthened the interconnectedness of cross-markets. The rapid development of information and communication technologies accelerated changes in the financial markets. Following the renewal of financial markets, a variety of new financial derivative products was generated, causing successive adjustments in the structures financial systems. In addition, international finance was subjected to unrelenting assaults, with exchange rates, interest rates, stock prices and index futures not only changing daily, but fluctuating by the minute and even by the second. In view of this, the aim of this paper is to discuss the impact of policy and system reform on financial markets.
Our data processing capabilities have increased greatly along with the ever-changing financial dynamics and the vigorous development of the financial markets. If we wish to understand the financial dynamics at each point in time and analyze the causes of changes in financial conditions, there is an urgent need for econometric techniques that can instantly process large volumes of data. If we can conduct suitable econometric analyses on financial markets data, that would be important indeed. The field of financial econometrics developed rapidly at the end of the 20th century, and it goes without saying that we can benefit from the broad range of applications of financial econometric models, which can be helpful in evaluating investment strategies, asset allocation and risk management, and can also be adjusted according to users’ needs. Financial econometrics is built upon a hypothetical basis, and making use of econometric methods and conducting research into phenomena such as the course of development of financial systems and tools can provide deep insight into numerous financial areas. For this reason, this paper applies modern financial econometrics separately to different financial markets.  In financial theory and empirical studies, there is a growing number of applied econometric analysis techniques. The overall value of this paper is in the ability to quickly and accurately apply these new econometric models (including ARDL model, intertemporal regression model and information share model) to analyze financial data, unearthing the effects that these change factors have on financial phenomena through empirical studies, thereby fleshing out new research findings and developments in the field of exchange rate and index futures, and substantiating a financial theory system. To sum up, this paper combines financial theory and econometrics, illustrating concepts through real-life economic and financial examples, introducing relevant documentation and financial theories on foreign exchange and futures markets in clear, concrete steps, and introducing different econometric models that can be applied to the field of finance. 
This dissertation consists of three essays: In the first part, we apply the ARDL methods in foreign exchange markets, enabling the reader to understand the characteristics of the irrational behavior of Taiwan's foreign exchange market through examples of the overreaction of NT dollar exchange rates to increases in money supply. Research has found that bubble speculative phenomena regarding excessive fluctuation in short-term exchange rates in Taiwan's foreign exchange market do not easily occur. In the second part, we add dummy variables into intertemporal regression models to explore the effects of market changes on Taiwan’s futures market. The results of empirical studies support the hypothesis that lowering the futures transaction tax will increase market efficiency, and we found that the intervention of the National Stabilization Fund in the market leads to a dampening of market efficiency, and only by reducing unnecessary government intervention can the market pricing mechanism be fully utilized. In the third part: after the introduction of electronically traded and small-sized (E-mini) index futures there was a lack of research into the correlation of price dynamics between Russell 2000 futures and E-mini Russell 2000. This paper explores the information transmission processes of open outcry for Russell 2000 futures and E-mini Russell 2000 through information share model. We found that E-mini Russell 2000 index futures contracts possess the ability to guide price discovery in financial markets, showing that E-trading systems have a superiority in information efficiency and operational efficiency, which will help us understand the characteristics of open outcry trading and E-trading, and can serve as a reference for investing in Russell index futures. In sum, we provide useful evidence for trading mechanism (open outcry trading vs. E-trading) and contract design (regular futures vs. mini futures). To investors, it provides a reference beneficial for investing in Russell 2000 index futures. As for the world's exchanges, this paper's examples can help financial management authorities make adjustments in trading mechanism and contract specification design, which will certainly be advantageous in attaining the goal of robust market development.

Table of Contents
Acknowledgment……………………………………………………………………Ⅰ
Abstract in Chinese………………………………………………………………... Ⅱ
Abstract in English…………………...………………………………………………Ⅳ

Introduction of the dissertation…………..………………………………………….1

Part 1: ARDL Approach to the Exchange Rate Overshooting in Taiwan……...7
1. Introduction…………………………………………...………………………8
2. Theoretical models…………………….……………..………………………14
3. Methodology and empirical results…………………..…………………….16
3.1 Stationary test………………………..…………………………………..16
3.2 Johansen’s cointegration test………………………..……………………17
3.3 ARDL bound test…………………………………..…………………….19
4. Conclusion……………….……………………..………………………...…25
References……………….………………………….…….….…………………27

 
Part 2: The Effect on Market Efficiency of a Futures Transaction Tax Reduction and the   Intervention of the National Financial Stabilization Fund……………………………….37
1. Introduction………………………………………………………………….38
2. Data and institutional environment…………………………………………42
2.1 Trading mechanism………………………………….…………………42
2.2 Data…………………………………………………………………….42
3. Econometric specifications…………………………..…………………...…..44
3.1 Cost of carry model……………………………………………..………44
3.2 Mispricing analysis……………………………………………………..45
3.3 Market depth…………………………….….……….…………………..45
3.4 Liquidity analysis…………………….…………………………………47
4. Empirical results………………………………………………………….48
4.1 Descriptive statistics...……………….………………………………….49
4.2 Inter-temporal analysis…………………………………………………..50
4.2.1 Analysis of mispricing…………..…………………………………50
4.2.2 Market depth………………………………………………………51
4.2.3 Liquidity analysis…………………………………………………53
4.3 Regression analysis results……………………………………………….54
4.3.1 Mispricing analysis………………………………………………..54
4.3.2 Market depth……………………………………………………...57
4.3.3 Liquidity analysis………………………………………………….60
5. Conclusion…………………………………………………………………..62
References…………………………………………………………………….65
 
Part 3: Information shares between Russell 2000 futures and E-mini Russell 2000...85
1. Introduction…………………………………………………………………86
2. Institutional detail and literature review……..…….…………………89
2.1 Russell 2000 index instruments…………………………………………89
2.2 The difference of regular futures and E-mini futures ……………………92
2.3 Compare open outcry with automated trading system…………....……..95
2.4 Literature review of open outcry vs. automated trading system…..….100
3. Methodology and empirical results………………………………………103
3.1 Data and descriptive statistics………………………………………..…103
3.2 Stationary test…………………………………………………………105
3.3 Johansen’s cointegration test ………………..……………………….106
3.4 Vector error correction model…………………………………………109
3.5 Information share………………………………………………………111
4. Conclusion and discussion…………………………………………………116
References……………………………………………………………………119
 
List of Figures
Essay 1: ARDL Approach to the Exchange Rate Overshooting in Taiwan
Figure 1 The trend of the NTD/USD exchange rate.….………….……….………….32
Figure 2 Comparison of the percentage changes with the relative price……………32
Figure 3 The interest rates and their interest rate differentiation…………….………33

Essay 2: The Effect on Market Efficiency of a Futures Transaction Tax Reduction and the Intervention of the National Financial Stabilization Fund
Figure 1 Market depth (Futures Transaction Tax reduction)……….….……………70
Figure 2 Market depth (National Financial Stabilization Fund)…………………….70
Figure 3 Market liquidity (Futures Transaction Tax reduction)………..……………71
Figure 4 Market liquidity (National Financial Stabilization Fund)…………………71

Essay 3: Information shares between Russell 2000 futures and E-mini Russell 2000
Figure 1 Price trend of the Russell 2000 instruments……………………………125
 
List of Tables
Essay 1: ARDL Approach to the Exchange Rate Overshooting in Taiwan
Table 1 Comparison of exchange rate determination models.………..……………..33
Table 2 The results of various unit root tests….…………..…………………………34
Table 3 Determination of cointegration rank…………….………………………….35
Table 4 ARDL bound testing…………………………….…………..………………35
Table 5 Full information estimate of the ARDL model……………….…………….36
Essay 2: The Effect on Market Efficiency of a Futures Transaction Tax Reduction and the Intervention of the National Financial Stabilization Fund
Table 1 Descriptive statistics.…………..…………………………………….………67
Table 2 ANOVA table………..……………………………………………….………68
Table 3 ANOVA table………..……………………………………………………….69
Table 4 Estimates for the regression analysis coefficients ………………………….72
Table 5 Regression analysis of market depth (Futures Transaction Tax)…………....73
Table 6 Regression analysis of market depth (National Financial Stabilization Fund)..….76
Table 7 Regression analysis of market liquidity (Futures Transaction Tax )………..79
Table 8 Regression analysis of market liquidity (National Financial Stabilization Fund)…82
Essay 3: Information shares between Russell 2000 futures and E-mini Russell 2000
Table 1 Recent products of E-minis futures of CME and CBOT………..…………125
Table 2 Contractual Specifications of the Russell 2000 futures…………..…...……126
Table 3 Summary statistics and correlation coefficient………….………………....127
Table 4 The results of various unit root tests…………………….…………………128
Table 5 Determination of cointegration rank…………………….………………....129
Table 6 Results of vector error correction model………………..………………...130
Table 7 Information share………………………………………………………….130

References
[Part 1]
Abbot, A., A. Darnell, and L. Evans (2001), “The Influence of Exchange Rate Variability on UK Exports,” Applied Economics Letters, 8, 47-49.
Akiba, H. (1996), “Exchange-rate Sensitive Demand for Money and Overshooting,” International Economic Journal, 10(2), 119-129.
Atkins, F.J. and P.J. Coe (2002), “An ARDL Bounds Test of the Long-run Fisher Effect in the United States and Canada,” Journal of Macroeconomics, 24(2), 255-266.
Bahmani-Oskooee, M. and O. Kara (2000), “Exchange Rate Overshooting in Turkey,” Economics Letters, 68, 89-93.
Bahmani-Oskooee, M. and G.G. Goswami (2003), “A Disaggregated Approach to Test the J-curve Phenomenon: Taiwan versus her Major Trading Partners,” Journal of economics and finance, 27(1), 102-113.
Bahmani-Oskooee, M. and R. Ng (2002), “Long-run Demand for Money in Hong Kong: An Application of the ARDL Model,” International Journal of Business and Economics, 1(2), 147-155.
Bentzen, J. and T. Engsted (2001), “A Revival of the Autoregressive Distributed Lag Model in Estimating Energy Demand Relationships,” Energy, 26, 45-55.
Bhandari, J.S. (1985),“A Look at ‘Overshooting’ in a Two-tier Float Exchange Rate System,” Economics Letters, 19, 57–61.
Bilson, J. (1978), “The Monetary Approach to the Exchange Rate: Some Empirical Evidence,” IMF Staff Paper, 25, 48-75.
Branson, W.H. (1980), "Asset Markets and Relative Prices in Exchange Rate Dtermination," Sozialwissenschaftliche Annalen des Instituts fur Hohere Studien, Reihe A, 1, 1977, 69-89 (reprinted in Princeton University International Finance, 20, June 1980.)  
Dickey, D.A. and W.A. Fuller (1981), “Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root,” Econometrica, 49, 1057-1072.
Dolado, J.J., T. Jenkinson and S. Sosvilla-Rivero (1990), “Cointegration and Unit Roots,” Journal of Economic Surveys, 4, 249-73.
Dornbusch, R. (1976), “Expectations and Exchange Rate Dynamics,” Journal of Political Economy, 84, 1161-1175.
Dornbusch, R. and S. Fisher (1980), “Exchange Rates and the Current Account,” American Economic Review, 70, 960-971.
Dornbusch, R. (2004), “Monetary Policy Under Exchange Rate Flexibility,” Massachusetts Institute of Technology (MIT), Working Paper.
Driskill, R. (1981), “Exchange Rate Overshooting, the Trade Balance, and Rational Expectations,” Journal of International Economics, 361-377.
Dutt, S.D. and D. Ghosh (2000), “An Empirical Note on the Monetary Exchange Rate Model,” Applied Economics Letters, 7(10), 669–671.
Elliott, G., T.J. Rothenberg, and J.H. Stock (1996), “Efficient Tests for an Autoregressive Unit Root,” Econometrica, 64, 813-836.
Engle, R.F. and C.W.J. Granger (1987), “Co-integration and Error Correction Representation, Estimation and Testing,” Econometrica, 55, 251-267.
Fedderke, J.W. and W. Liu (2002), “Modeling the Determinants of Capital Flows and Capital Flight: With an Application to South African Data from 1960 to 1995,” Economic modeling, 19, 419-444.
Frankel, J.A. (1979), “On the Mark:  A Theory of Floating Exchange Rate Based on Real Interest Differentials,” American Economic Review, 69, 610-627.
Frenkel, J. (1976), “Monetary Approach to the Exchange Rate:  Doctrinal Aspects and Empirical Evidence,” Scandinavian Journal of Economics, 78(2), 220-224.
Ghatak, S. and J. Siddiki (2001), “The Use of the ARDL Approach in Estimating Virtual Exchange Rates in India,” Journal of Applied Statistics, 28(5), 573-583.
Goldfajn, I. and P. Gupta (2001), “Overshootings and Reversals: The Role of Monetary Policy,” Central Bank of Chile, Working Paper, No. 126, 279-302.
Hooper, P. and J.E. Morton (1982), “Fluctuations in the Dollar: A Model and Real Exchange Rate Determination,” Journal of International Money and Finance, 1, 39-56.
Jimoh, A. (2004), “The Monetary Approach To Exchange Rate Determination: Evidence From Nigeria,” Journal of Economic Cooperation, 25(2), 109-130. 
Johansen, S. (1988),“Statistical Analysis of Cointegration Vectors,” Journal of Economic Dynamics and Control, 12, 231-254.
Johansen, S. (1994), “The Role of the Constant and Linear Terms in Cointegration Analysis of Nonstationary Variables,” Econometric Reviews, 13, 205-229.
Johansen, S. and K. Juselius (1990), “Maximum Likelihood Estimation and Inference on Cointegration with Applications to the Demand for Money,” Oxford Bulletin of Economics and Statistics, 52, 169-210.
Karfakis, C. (2003), “Exchange Rate Determination during Hyperinflation:  The Case of the Romanian lei,” Applied Financial Economics, 13(6), 473-476.
Kilian, L. and M.P. Taylor (2003), “Why is it So Difficult to Beat the Random Walk Forecast of Exchange Rates?” Journal of International Economics, 60, 85-107.
Kwiatkowski, D., P. Phillips, P. Schmidt, and Y. Shin (1992), “Testing the Null Hypothesis of Stationary against the Alternative of a Unit Root,” Journal of Econometrics, 54, 159-178.
Levin, J.H. (1999), “Exchange Rate Undershooting,” International Journal of Finance and Economics, 4(4), 325-333.
Meese, R.A. and K. Rogoff (1983), “Empirical Exchange Rate Models of the Seventies: Are any Fit to Survive?” Journal of International Economics, 14, 3-24.
Miyakoshi, T. (2000), “The Monetary Approach to the Exchange Rate:  Empirical Observations from Korea,” Applied Economics Letters, 7(12), 791–794.
Newey, W. and K. West (1994), “Automatic Lag Selection in Covariance Matrix Estimation,” Review of Economic Studies, 61, 631-653.
Ng, S. and P. Perron (2001), “Lag Length Selection and the Construction of Unit Root Tests with Good Size and Power,” Econometrica, 69, 1519-1554.
Nieh, C.C. and C.F. Lee (2001), “Dynamic Relationship between Stock Prices and Exchange Rates for G-7 Countries,” Quarterly Review of Economics and Finance, 41(4), 477-490.
Papell, D.H. (2004), “Activist Monetary Policy and Exchange Rate Overshooting: The Deutsche Mark/Dollar Rate,” University of Houston, Department of Economics, Working Paper. 
Pattichis, C. and M. Kanaan (2004), “The Balassa-Samuelson Hypothesis and Oil Price Shocks in a Small Open Economy: Evidence from Cyprus,” Open economies review, 15, 45–56.
Pesaran, M.H. and Y. Shin (1995a), “Long Run Structural Modelling,” DAE Working Paper, Department of Applied Economics, University of Cambridge.
Pesaran, M.H. and Y. Shin (1995b), “An Autoregressive Distributed Lag Modelling Approach to Cointegration Analysis,” DAE Working Paper, No. 9514, Department of Applied Economics, University of Cambridge.
Pesaran, M.H., Y. Shin and R.J. Smith (1996), “Testing for the Existence of a Long-run Relationship,” DAE Working Paper, No. 9622, Department of Applied Economics, University of Cambridge.
Pesaran, M.H., Y. Shin, and R.J. Smith (2001), “Bounds Testing Approaches to the Analysis of Long-run Relationship,” Journal of Applied Econometrics, 16, 289-326.
Phillips, P.C.B. and P. Perron (1988), “Testing for a Unit Root in Time Series Regression,” Biometrika, 75, 335-346.
Rogoff, K. (2002), “Dornbusch's Overshooting Model after Twenty-five Years,” Washington: IMF Working Paper.
Rapach, D.E. and M.E. Wohar (2002), “Testing the Monetary Model of Exchange Rate Determination: New Evidence From a Century of Data,” Journal of International Economics, 58(2), 359-385.
Rapach, D.E. and M.E Wohar (2004), “Testing the Monetary Model of Exchange Rate Determination: a Closer Look at Panels,” Journal of International Money and Finance, 23(6), 841-865. 
Simwaka, K. (2004), “Monetary Model of Exchange Rate:  Empirical Evidence from Malawi,” Working Paper, Reserve Bank of Malawi.
Tang, T.C. and M. Nair (2002), “A Cointegration Analysis of Malaysian Import Demand Function:  Rassessment from the Bounds Test,” Applied Economics Letters, 9(5), 293-296.
Taylor, M. and D. Peel (2000), “Nonlinear Adjustment, Long Run Equilibrium and Exchange Rate Fundamentals,” Journal of International Money and Finance, 19, 33–53.
Veronese, P.R. (2003), “Exchange Rate Overshooting,” Working paper, Department of Economics, Queen’s University Kindston, Ontario, Canada, 1-6, 
Vita, G. D. and A. Abbott (2002), “Are Saving and Investment Cointegratd?  An ARDL Bounds Testing Approach,” Economics Letters, 77(2), 293-299.
West, K.D. (2004), “A Standard Monetary Model and the Variability of the Deutschemark-Dollar Exchange Rate,” Working Paper, Department of Economics, University of Wisconsin-Madison. 
[Part 2]
 
References
Aitken, M. and C. Comerton-Forde (2003), “How Should Liquidity be Measured?” Pacific-Basin Finance Journal, 11, 45-59. 
Brockman, P. and D.Y. Chung (1999), “An Analysis of Depth Behavior in an Electronic Order-driven Environment,” Journal of Banking & Finance, 23, 1861-1886.
Chaboud, A. and B. LeBaron (2001), “Foreign-Exchange Trading Volume and Federal Reserves Intervention,” The Journal of Future Markets, 21(9), 851–860. 
Chou, R.K. and J. Lee (2002), “The Relative Efficiencies of Price Execution between the Singapore Exchange and the Taiwan Futures Exchange,” Journal of Futures Markets, 22, 174-196. 
Coppejans, M., I. Domowitz, and A. Madhavan (2001), “Liquidity in an Automated Auction,” available from URL: http://www.ebrc.psu.edu/publications/papers/pdf/2001_09.pdf.
Cornell, B. and K. French (1983), “The Pricing of Stock Index Futures,” Journal of Futures Markets, 3, 1-14.
Draper, P. and J.K.W. Fung (2003), “Discretionary Government Intervention and the Mispricing of Index Futures,” The Journal of Futures Markets, 23, 1159–1189.
Feldstein, M. (1995), “Behavioral Response to Tax Rate:  Evidence from TRA86,” NBER Working Paper, No. 5000, 1-14.
Fleming, J., B. Ostdiek and R.E. Whaley (1996), “Trading Costs and the Relative Rates of Price Discovery in Stock, Futures and Options Markets,” Journal of Futures Markets, 16, 353-387. 
Harris, L. (2003), “Trading and Exchanges,” Oxford University Press, NY.
Kim, M., A.C. Szakmary and T.V. Schwarz (1999), “Trading Costs and Price Discovery across Stock Index Futures and Cash Markets,” The Journal of Futures Markets, 19(4), 475–498.
Kyle, A.S. (1985), “Continuous Auctions and Insider Trading,” Economica, 53, 1315-1335.
Lee, C.M., C.B. Mucklow, and M.J. Ready (1993), “Spreads Depths, and the Impact of Earnings Information:  An Intraday Analysis,” Review of Financial Studies, 6, 345-374.
McInish, T.H. and R.A. Wood (1992) “An Analysis of Intraday Patterns in Bid/Ask Spreads for NYSE Stocks,” Journal of Finance, 47, 753-764. 
Naranjo, A. and M. Nimaledran (2000), “Government Intervention and Adverse Selection Costs in Foreign Exchange Markets,” The Review of Financial Studies, 13(2), 453-477.
Pirrong, C. (1996), “Market Liquidity and Depth on Computerized and Open Outcry Trading Systems: A Comparison of DTB and LIFFE Bund Contracts,” Journal of Futures Markets, 16, 519-43. 
Switzer, L.N., P.L. Varson and S. Zghidi (2000), “Standard and Poor’s Depository Receipts and the Performance of the S&P 500 Index Futures Market,” Journal of Futures Market, 20(8), 705-716.
[Part 3]
Ates, A. and G.H.K. Wang (2004), “When Size Matters:  The Case of Equity Index Futures,” European Financial Management Association Annual Meeting, Basel, Switzerland. 
Baillie, R.T., G.G. Booth, Y. Tse, and T. Zabotina (2002), “Price Discovery and Common Factor Models,” Journal of Financial Markets, 5, 309-321. 
Booth, G.G., R.W. So, and Y. Tse (1999), “Price Discovery in the German Equity Index Derivatives Markets,” The Journal of Futures Markets, 19, 619-643.
Breedon, F.J. and A. Holland (1998), “Electronic Versus Open Outcry Markets: The Case of the Bund Futures Contract,” Working Paper, Bank of England, No. 76.
Chan, K. (1992), “A Further Analysis of the Lead-lag Relationship between the Cash Market and Stock Index Futures Market,” Review of Financial Studies, 123-152.
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, 8, 21-34.
Dickey, D.A. and W.A. Fuller (1981), “Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root,” Econometrica, 49, 1057-1072.
Dolado, J.J., T. Jenkinson, and S. Sosvilla-Rivero (1990), “Cointegration and Unit Roots,” Journal of Economic Surveys, 4, 249-73.
Domowitz, I. (1993), “Equally Open and Competitive: Regulatory Approval of Automated Trade Execution in the Futures Markets,” Journal of Futures Markets, 13, 93-113.
Elliott, G., T.J. Rothenberg, and J.H. Stock (1996), “Efficient Tests for an Autoregressive Unit Root,” Econometrica, 64, 813-836.
Engle, R.F. and C.W.J. Granger (1987), “Cointegration and Error Correction Representation, Estimation and Testing,” Econometrica, 55, 251-267.
Gonzalo, J. (1994), “Five Alternative Methods of Estimating Long-run Equilibrium Relationships,” Journal of Econometrics, 60, 203-233.
Gonzalo, J., and C.W.J. Granger (1995), “Estimation of Common Long - Memory Components in Cointegrated Systems,” Journal of Business & Economic Statistics, 13, 27-36.
Granger, C.W.J. (1969), “Investigating Causal Relations by Econometric Models and Cross-spectral Methods,” Econometrica, 37, 424-436.
Granger, C.W.J. (1981), “Some Properties of Time Series Data and their Use in Econometric Model Specification,” Journal of Econometrics, 16, 121-130.
Granger, C.W.J. (1988), “Some Recent Developments in a Concept of Causality,” Journal of Econometrics, 39, 199-211.
Hall, A.R. (1994), “Testing for a Unit Root in Time Series with Pretest Data-Based Model Selection,” Journal of Business and Economics Statistics, 12, 461-470. 
Hasbrouck, J. (1995), “One Security, Many Markets: Determining the Contributions to Price Discovery,” Journal of Finance, 50, 1175-1199.
Hasbrouck, J. (2003), “Intraday Price Formation in US Equity Index Markets,” Journal of Finance, 58(6), 2375-2400. 
Hayashi, F. (2000), “Econometrics,” Princeton University Press.
Hung, M.W., and H. Zhang (1995), “Price Movements and Price Discovery in the Municipal Bond Index Futures Markets,” The Journal of Futures Markets, 15, 489-506. 
Hsieh, W.G. (2002), “Market Integration, Price Discovery, and Information Transmission in Taiwan Index Futures Market,” Journal of Financial Studies, 10(3), 1-31.
Johansen, S. (1988), “Statistical Analysis of Cointegration Vectors,” Journal of Economic Dynamics and Control, 12, 231-254.
Johansen, S. (1994), “The Role of the Constant and Linear Terms in Cointegration Analysis of Nonstationary Variables,” Econometric Reviews, 13, 205-229.
Johansen, S. and K. Juselius (1990), “Maximum Likelihood Estimation and Inference on Cointegration with Applications to the Demand for Money,” Oxford Bulletin of Economics and Statistics, 52, 169-210.
Kawaller, I.G., P.D. Koch, and T.W. Koch (1987), “The Temporal Relationship between S&P 500 Futures and the S&P 500 Index,” Journal of Finance, 42, 1309-1329.
Kurov, A. and D. Lasser (2002), “Price Discovery in the E-mini Futures Market: Is the Tail Wagging the Dog?” Working Paper, School of Management, Binghamton.
Kurov, A., and T. Zabotina (2003), “Is it Time to Reduce the Minimum Tick Sizes of the E-mini Futures?” Working paper, 1-41. 
Kwiatkowski, D., P. Phillips, P. Schmidt and Y. Shin (1992), “Testing the Null Hypothesis of Stationary against the Alternative of a Unit Toot,” Journal of Econometrics, 54, 159-178.
Mackinnon, J.G. (1996), “Numerical Distribution Functions for Unit-Root and Cointegration Tests,” Journal of Applied Econometrics, 601-618.
Martikainen, T. and V. Puttonen (1994), “International Price Discovery in Finnish Stock Index Futures and Cash Markets,” Journal of Banking and Finance, 18, 809-822.
Massimb, M.N. and B. Phelps (1994). “Electronic Trading, Market Structure and Liquidity,” Financial Analyst Journal, January-February, 39-50.
Masulis R. and L. Shivakumar (2002), “The Speed of Price Adjustment to Stock Offering Announcements: A NYSE/AMEX and NASDAQ Comparison,” Journal of Financial and Quantitative Analysis, 73(4), 617-648.
Melamed, L. (1997), “The Mechanics of a Commodity Futures Exchange: A Critique of Automation of the Transaction Process,” Hofstra Law Review, 6, 149-72.
Newey, W. and K. West (1994), “Automatic Lag Selection in Covariance Matrix Estimation,” Review of Economic Studies, 61, 631-653.
Ng, S. and P. Perron (1995), “Unit Root Tests in ARMA Models with Data-Dependent Methods for the Selection of the Truncation Lag,” Journal of the American Statistical Association, 90, 268-281.
Ng, S. and P. Perron (2001), “Lag Length Selection and the Construction of Unit Root tests with goof size and power,” Econometrica, 69, 1519-1554.
Nieh, C.C. and C.F. Lee (2001), “Dynamic Relationship Between Stock Prices and Exchange Rates for G-7 Countries,” Quarterly Review of Economics and Finance, 41(4), 477-490.
O’Connor, S.M. (1993). “The Development of Financial Derivatives Markets: The Canadian Experience,” Technical Report No. 62, Ottawa: Bank of Canada.
Osterwald-Lenum, M. (1992), “Practitioner's Corner A Note with Quantiles of the Asymptotic Distribution of the Maximum Likelihood Cointegration Rank Test Statistics,” Oxford Bulletin of Economics and Statistics, 54, 461-472.
Phillips, P.C.B. and P. Perron (1988), “Testing for a Unit Root in Time Series Regression,” Biometrika, 75, 335-346.
Pieptea, D.R. (1992), “Electronic Trading and Futures Market Efficiency,” International Journal of Technology Management, 7, 471-77.
Pirrong, C. (1996), “Market Liquidity and Depth on Computerized and Open Outcry Trading Systems: A Comparison of DTB and LIFFE Bund Contracts,” Journal of Futures Markets, 16, 519-43.  
Pizzi A.M., A. J. Economopoulos, and H.M. O’Neill (1998), “An Examination of the Relationship Between Stock Index Cash and Futures Markets: a Cointegration Approach,” The Journal of Futures Markets, 18, 297-305.
Reimers, H.E. (1992), “Comparions of Tests for Multivariate Cointegration,” Statistics Paper, 33, 335-346.
Schwartz, G. (1978), “Estimating the Dimension of a Model,” Ann. Statistics, 6, 461-464.
Soydemir, G.A. and A.G. Petrie (2003), “Intraday Information Transmission between DJIA Spot and Futures Markets,” Applied Financial Economics, 13, 817-827.
Stoll, H.R. and R.E. Whaley (1990), “The Dynamics of Stock Index and Stock Index Futures Returns,” Journal of Financial and Quantitative Analysis, 25(4), 441-467.
Tse, Y. (1998), “International Linkages in Euromark Futures Markets: Information Transmission and Market Integration,” The Journal of Futures Markets, 18, 128-149.
Tse, Y. (1999), “Price Discovery and Volatility Spillovers in the DJIA Index and Futures Markets,” The Journal of Futures Markets, 19(8), 911-930.
Tse, Y. and G. Erenburg (2003), “Competition for Order Flow, Market Quality, and Price Discovery in the NASDAQ 100 Index Tracking Stock,” Journal of Financial Research, 26(3), 301-318.
Wahab, M. and M. Lashgari (1993) “Price Dynamics and Error Correction in Stock Index and Stock Index Futures Markets: A Cointegration Approach,” The Journal of Futures Markets, 13, 711-742.
Wang, G.H.K., and A. Ates (2001), “Information Transmission and Electronic Versus Open Outcry Trading Systems: An Intraday Analysis of E-Mini S&P 500 Futures, S&P 500 Index Futures and S&P 500 Cash Index,” Working Paper, University of Maryland, College Park, 1-67.  
White, H. (1980), “A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity,” Econometrica, 48, 817-838.