波动、相关与最优套期保值
|
摘要
期现货市场的波动与相关使套期保值理论与实践发展成为必然与可能,正是期货价格与现货价格的波动与相依,使得期货市场简单对冲不但不能规避投资者现货市场风险,反而会增加期货头寸暴露的风险。理论上,投资者的最优套期保值还是其效用函数最大化的过程,本文应用最小方差和最小下偏风险矩两种效用标准,分别对中国铜期货市场最优套期保值率进行理论与实证研究。
由于国内期货市场处于初级阶段,市场波动机制频繁变化。本文在借鉴国外研究基础上,率先运用马尔可夫机制转换模型和随机自回归机制转换模型实证计算中国铜期货市场的最小方差套期保值率,并与OLS模型、ECM模型和多元GARCH模型进行实证比较,一般情况下,动态模型优于静态模型,但具体模型的适用要依样本状况确定。本研究增加了最优套期保值率模型选择范围,为套期保值者在市场多变的情况下提供了更多的选择依据。
目前国内期货市场尾部相关性研究多集中于描述国内外市场间的尾部相依结构,对期、现货收益序列的尾部相依结构研究的还比较鲜见。本文采用极值理论拟合期、现货市场尾部边缘分布,然后通过Copula函数构建期、现货市场尾部的相依结构。实证分析了中国铜期、现货市场的边缘相依特征。实证分析表明:期、现货市场上下侧表现出非对称相关性特征,下侧相关性明显强于上侧。
当投资者的效用函数为损失规避时,下偏风险矩能够刻画此类投资者的效用特征。本文在研究最小下偏风险矩套期保值理论基础上,实证分析了多头和空头套期保值策略。分析表明:由于期、现货市场非对称相关性的影响,在目标收益的下侧,套期保值者可以运用更小的期货合约规避下侧风险,且多头套期保值者能够比空头套期保值者更好的利用期货市场规避下侧风险。
本文的研究意义在于:处于初级阶段的中国期货市场将较为频繁的出现极端情况,通过极端相关性研究,为投资者在市场极端情况提供决策支持;另一方面,通过对套期保值率全面系统的比较分析,便于投资者根据自身效用倾向和当前市场状况,选择适宜的套期保值率估计模型。
It is the volatility and correlation of spot and future market that result in the development of hedge theory. Just because of the volatility and correlation of spot and future price, the traditional naive hedge cannot reduce the risk but even increase it. In theory, an optimal hedge strategy is based on the expected-utility maximization paradigm. This paper engages academic and practical researches on the optimal hedge ratio of Chinese copper future market with the minimum-variance and minimum-LPM criterion.
At the beginning of domestic future market, the market volatility regime changes frequently. In use of aboard MRS model and RCARRS model, the paper experimentally calculates the minimum-variance hedge ratio in Chinese copper future market, and compare with the OLS, ECM and dynamic-Garch models. In general, dynamic model is better than static model, whereas applicability of idiographic model depends on the state of market. Therefore, this paper adds the choice area of the optimal hedge ratio estimated model.
At present, the domestic research on the tail correlation is fastened on the tail correlation of domestic and foreign market. It is rare that the research on the tail correlation of spot and future market is. The paper models the tail dependence between spot and futures returns with extreme value theory in Chinese copper market. The above-mentioned analyses indicate that the spot and futures returns on both up and down side show the asymmetric correlations character, and the correlations on the downside are much greater than on the upside.
Furthermore, under the notion of loss aversion, as a measure of risk, the low partial moment is feasible to delineate the risk preference. Based on the theory of the mini-LPM hedging, the paper experimentally analyses the optimal hedge strategy of short and long position. The analytic results indicate that the hedgers who hold long positions may be more favorable than that who hold short positions in reducing downside risk.
In a word, the research of this paper has following signification. On one hand, since the extreme scenarios may happen frequently in Chinese future market, the extreme correlation researches can help investor to make a decision. On the other hand, a comparative research on hedge ratio can provide some useful information for investors to choose an optimal hedge ratio estimated model.
由于国内期货市场处于初级阶段,市场波动机制频繁变化。本文在借鉴国外研究基础上,率先运用马尔可夫机制转换模型和随机自回归机制转换模型实证计算中国铜期货市场的最小方差套期保值率,并与OLS模型、ECM模型和多元GARCH模型进行实证比较,一般情况下,动态模型优于静态模型,但具体模型的适用要依样本状况确定。本研究增加了最优套期保值率模型选择范围,为套期保值者在市场多变的情况下提供了更多的选择依据。
目前国内期货市场尾部相关性研究多集中于描述国内外市场间的尾部相依结构,对期、现货收益序列的尾部相依结构研究的还比较鲜见。本文采用极值理论拟合期、现货市场尾部边缘分布,然后通过Copula函数构建期、现货市场尾部的相依结构。实证分析了中国铜期、现货市场的边缘相依特征。实证分析表明:期、现货市场上下侧表现出非对称相关性特征,下侧相关性明显强于上侧。
当投资者的效用函数为损失规避时,下偏风险矩能够刻画此类投资者的效用特征。本文在研究最小下偏风险矩套期保值理论基础上,实证分析了多头和空头套期保值策略。分析表明:由于期、现货市场非对称相关性的影响,在目标收益的下侧,套期保值者可以运用更小的期货合约规避下侧风险,且多头套期保值者能够比空头套期保值者更好的利用期货市场规避下侧风险。
本文的研究意义在于:处于初级阶段的中国期货市场将较为频繁的出现极端情况,通过极端相关性研究,为投资者在市场极端情况提供决策支持;另一方面,通过对套期保值率全面系统的比较分析,便于投资者根据自身效用倾向和当前市场状况,选择适宜的套期保值率估计模型。
It is the volatility and correlation of spot and future market that result in the development of hedge theory. Just because of the volatility and correlation of spot and future price, the traditional naive hedge cannot reduce the risk but even increase it. In theory, an optimal hedge strategy is based on the expected-utility maximization paradigm. This paper engages academic and practical researches on the optimal hedge ratio of Chinese copper future market with the minimum-variance and minimum-LPM criterion.
At the beginning of domestic future market, the market volatility regime changes frequently. In use of aboard MRS model and RCARRS model, the paper experimentally calculates the minimum-variance hedge ratio in Chinese copper future market, and compare with the OLS, ECM and dynamic-Garch models. In general, dynamic model is better than static model, whereas applicability of idiographic model depends on the state of market. Therefore, this paper adds the choice area of the optimal hedge ratio estimated model.
At present, the domestic research on the tail correlation is fastened on the tail correlation of domestic and foreign market. It is rare that the research on the tail correlation of spot and future market is. The paper models the tail dependence between spot and futures returns with extreme value theory in Chinese copper market. The above-mentioned analyses indicate that the spot and futures returns on both up and down side show the asymmetric correlations character, and the correlations on the downside are much greater than on the upside.
Furthermore, under the notion of loss aversion, as a measure of risk, the low partial moment is feasible to delineate the risk preference. Based on the theory of the mini-LPM hedging, the paper experimentally analyses the optimal hedge strategy of short and long position. The analytic results indicate that the hedgers who hold long positions may be more favorable than that who hold short positions in reducing downside risk.
In a word, the research of this paper has following signification. On one hand, since the extreme scenarios may happen frequently in Chinese future market, the extreme correlation researches can help investor to make a decision. On the other hand, a comparative research on hedge ratio can provide some useful information for investors to choose an optimal hedge ratio estimated model.
引文
[1] Adams, J. and Montesi, C. J., Major Issues Related to Hedge Accounts, Newark, Connecticut: Financial Accounting Standard Board, 1995.
[2] Alizadeh, A. and Nomikos, N., A Markov Regime Switching Approach for Hedging Stock Indices, The Journal of Futures Markets, 2004, 24 (7): 649-674.
[3] Amihud, Y. and Mendelson, H., The effect of computer base trading on volatility and liquidity, H.C. Lucas, 1989.
[4] Anderson, R.W. and Danthine, J.P., The time pattern of hedging and the volatility of futures prices, Review of Economic Studies, 1983, 50: 249-266.
[5] Ang, A. and G. Bekaert, International asset allocation with time-varying correlations, Working paper, Columbia University, 2000.
[6] Ang, A., J. Chen and Y. Xing, Downside risk and the momentum effect, Working paper, Columbia University, 2001.
[7] Ang, A. and J. Chen, Asymmetric correlations of equity portfolios, Journal of Financial Economics, 2002, 63, No. 3 (March 2002): 637–654.
[8] Baillie, R. T. and R. Myers, Bivariate GARCH estimation of the optimal commodity futures hedge, Journal of Applied Econometrics, 1991, 6: 109-124.
[9] Balke, N. S. and Fomby, T. B., Threshold Cointegration, International Economic Review, 1997, 38: 627 - 645.
[10] Balkema, A. and L. de Haan, Residual life time at great age, Annals of Probability, 1974, 55: 792–804.
[11] Bawa, V.S., Safely-first, stochastic dominance and optimal portfolio choice, Journal of Financial and Quantitative Analysis, 1978, 33: 25- 71.
[12] Bekaert, G. and C. R. Harve, Emerging equity market volatility, Journal of Financial Economics 1997, 43: 29–77.
[13] Bekaert, G. and C. R. Harvey, Foreign speculators and emerging equity markets, Journal of Finance, 2000, 55 (2): 565–613.
[14] Bekaert, G. and G. Wu, Asymmetric volatility and risk in equity markets, Review of Financial Studies, 2000, 13 (1): 1–42.
[15] Bell, D.E. and Krasker, W.S., Estimating Hedge Ratios, Financial Management, 1986, 15:34-39.
[16] Bollerslev, T., Generalized autoregressive conditional heteroscedasticity, Journal of Economics, 1986, 31: 307-327.
[17] Bollerslev, T., Chou, R.Y. and Kroner, K.F., ARCH modeling in finance: A review of the theory and empirical literature, Journal of Econometrics, 1992, 52 (1): 5-59.
[18] Bookstaber, R., Global risk management: Are we missing the point? Journal of Portfolio Management, 1997: 102-107.
[19] Boyer, B. H., M. S. Gibson and M. Loretan, Pitfalls in tests for changes in correlations, International Finance Discussion Papers, No. 597R, Board of Governors of the Federal Reserve System, March 1999.
[20] Broll, U., Chow, K.W. and Wong, K.P., Hedging and Nonlinear Risk Exposure, Oxford economic papers, 2000, Forthcoming.
[21] Brooks, C., O. T. Henry, and G. Persand, The effect of asymmetries on optimal hedge ratios, Journal of Business, 2002, 75 (2, April 2002): 333-352.
[22] Campbell, J. Y., M. Lettau, B. G. Malkiel, and Y. Xu, Have individual stocks become more volatile? An empirical exploration of idiosyncratic risk, Journal of Finance, 2001,56 (1): 1-43.
[23] Campbell, R., K. Koedjik, and P. Kofman, Increased correlations in bear markets, Financial Analysts Journal, 2002, 24(January/February 2002): 87-94.
[24] Cecchetti, Stephen G., Cumby, Robert E. and Figlewski, Stephen, Estimation of the Optimal Futures Hedge, The Review of Economics and Statistics, 1988, 70 (4): 623-630.
[25] Charles J. Jacklin, Allan W. Kleidon, and Paul Pfleiderer, Underestimation of Portfolio Insurance and the Crash of October 1987, Review of Financial Studies, 1992, 1:35-63.
[26] Charnes M. John, Asymmetric Correlation of Future Markets and Optimal Hedging, working paper, Kansas University, 2003.
[27] Chou, W. L., Fan, K. K., & Lee, C. F., Hedging with the Nikkei index futures: The conventional model versus the error correction model, Quarterly Review of Economics and Finance, 1996, 36: 495–505.
[28] Chow, G., E. Jacquier, M. Kritzman, and K. Lowry, Optimal portfolios in good times and bad, Financial Analysts Journal, 1999 (May/June): 65-73.
[29] Cornew, R., Crowson, L., and Town, D., Stable Distributions and Commodity Price and Performance Measurements, The Journal of Futures Markets, 1984, 4: 531-557.
[30] Das, S. and R. Uppa, Systemic risk and portfolio choice, Working paper, London Business School, 2001.
[31] Davison, A. C. and R. L. Smith, Models for exceedances over high thresholds (with Discussion), Journal of the Royal Statistical Society, 1990,B 53, 377–392.
[32] De Santis, G., B. Gerard, and P. Hillion, The relevance of currency risk in the EMU, Working paper, UCLA, 1999
[33] Dickey, D.A. and Fuller, W.A., Distribution of Estimators for Time Series Regressions with a Unit Root, Journal of the American Statistical Association, 1979, 74,427-431.
[34] Duffee, G. R, Stock returns and volatility: A firm-level analysis, Journal of Financial Economics, 1995, 37, 399–420.
[35] Ederington, L. H., The Hedging Performance of the New Futures Markets, The Journal of Finance, 1979, XXXIV (1), 157-170.
[36] Embrechets, P., Mcneil, A. and Traumann, U. S., Correlation and dependency in risk management: properties and pitfalls, http:// www.math.ethz.ch/~mcneil/ftp/pitfalls.pdf, 2000-12-26.
[37] Engle, R.F., Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation, Econometrica, 1982, 50: 987-1007.
[38] Engle, R.F. and Bollerslev, T., Modeling the persistence of conditional variances, Econometric Reviews, 1986, 5: 1-50, 81-87.
[39] Engle R.F. and Kroner K.F., Multivariate simultaneous generalized Arch Econometric Theory, 1995, 11:122-150.
[40] Fama, Eugene. F., Portfolio Analysis in a Stable Paretian Market, Management Science, 1965, 11(3, Series A, Sciences): 404-419.
[41] Fama, E.F. and French, K., Commodity futures prices: Some evidence on forecast power, premiums and the theory of storage, The Journal of Business, 1987, 60: 55-73.
[42] Fishburn, P.J., Mean-risk analysis with risk associated with below-target retures, American Economic review, 1977, 67: 116-126.
[43] Fong, W.M. and See, K.H., A Markov switching model of the conditional volatility of crude oil prices, Energy Economics, 2002, 35: 71-95.
[44] Garbade, K. D. and Silber, W. L. , Price Movements and Price Discovery in Futures and Cash Markets, Review of Economics and Statistics, 1983, 65: 289-297.
[45] Ghosh, A., Hedging with stock index futures: estimation and forecasting with error correction model, Journal of Futures Markets, 1993, 13: 743-752.
[46] Glen R., Components of The Bid-ask Spread and The statistical properties of Transaction prices, Journal of Finance, 1994, 42: 1293-1308.
[47] Granger, C. W. J., Developments in the Study of Cointegrated Economic Variables, Oxford Bulletin of Economics and Statistics, 1986, 48: 213-228.
[48] Gray, R.W. and Rutledge, D.J.S., The economics of commodity futures markets: A survey, Review of Marketing and Agricultural Economics, 1971.
[49] Gray, S. F., Modeling the conditional distribution of interest rates as a regime switching process, Journal of Financial Economics, 1996, 42: 27–62.
[50] Haigh, M.S. and Holt, M.T., Hedging multiple price uncertainty in international grain trade, American Journal of Agricultural Economics, 2000, 82: 881-896.
[51] Hamilton, James D., A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle, Econometrica, 1989, 57 (2): 357-384.
[52] Hardle, W., Applied nonparametric regression, Cambridge England: Cambridge University Press, 1990.
[53] Harlow W V., Asset allocation in a downside risk framework, Financial Analysts Journal, 1991, Sep-Oct: 28-40.
[54] Hasbrouck, Joel and Seppi, Duane J., Common factors in prices, order flows, and liquidity, Journal of Financial Economics, 2001, 59: (383-411).
[55] Helms, B., and Martell, T., An Examination of the Distribution of Commodity Price Changes, Journal of Futures Markets, 1985, 5: 259-272.
[56] Herbst, A. F., Kare, D. D., and Marshall, J. F., A Time Varying, Convergence Adjusted, Minimum Risk Futures Hedge Ratio, Advances in Futures and Options Research. 1993, 6: 137-155.
[57] Hogan, William W. and Warren, James M., Computation of the Efficient Boundary in the E-S Portfolio Selection Model, The Journal of Financial and Quantitative Analysis, 1972, VII (4): 1881.
[58] Hogan, William W. and Warren, James M., Toward the development of an equilibrium capita-market model based on semivariance, Journal of Financial and Quantitative Analysis, January 1974: 1.
[59] Howard C T, D’Antonio L J., A risk-return measure of hedging effectiveness, Journal of Financial and Quantitative Analysis, 1984,19: 101-112.
[60] Hsiang-Tai Lee, Jonathan Yoder, R.C. Mittelhammer and Jill J. McCluskey, A Random Coefficient Autoregressive Markov Regime Switching Model of Dynamic Futures Hedging, Journal of Futures Markets, 2006, 26 (2): 103-129.
[61] Hull, J. C., Introduction to Futures and Options Markets, 3rd Edition, New Jersey: Prentice Hall, 1998.
[62] Jansen, D. W., and C. G. Devries, On the frequency of large stock returns: Putting booms and busts into perspectives, Review of Economics and Statistics, 1991, 73: 18–24.
[63] Jenkinson, A. F., The frequency distribution of the annual maximum (or minimum) values of meteorological elements, Quarterly Journal of the Royal Meteorological Society, 1955, 81: 145–158.
[64] John C. Hull, Options, Futures, and Other Derivative Securities, New York: Prentice-Hall, 1993.
[65] Johnson, L. L., The Theory of Hedging and Speculation in Commodity Futures, Review of Economic Studies, 1960, 27: 139-151.
[66] J.R.Hicks,Value and capital, London:Oxford University Press, 1946(2nd edition)
[67] Kahl, K.H., Determination of the recommended hedging ratio, American Journal of Agricultural Economics, 1983, 65: 603-605.
[68] Kahneman, D., and Tversky, A., Prospect Theory: An Analysis of Decision under Uncertainty, Econometrica, 1979, 47: 263-291.
[69] Keynes,J.M.,A Treatiseon Money, Vol,Ⅱ,London:Macmillan, 1930.
[70] Kim, C.J., source of monetary growth uncertainty and economic activity: The time-varying-parameter model with heteroskedastic disturbances, The review of economics and statistic, 1993b, 75: 483-492.
[71] Kolb, R. W. and Okunev, J., Utility Maximizing Hedge Ratios in the Extended Mean-Gini Framework, Journal of Futures Markets, 1993,13: 597-609.
[72] Krolzig, H.M., statistical analysis of cointegrated VAR processes with Markovian regime shifts, Unpublished manuscript, Department of Economics, University of Oxford, 1993.
[73] Kyle, Albert S., Continuous auctions and insider trading [J], Econometrica, 1985, 53:1315-1335.
[74] Lamoureux, C.G. and Lastrapes, W.D., Persistence in variance, structural change, and the GARCH model, Journal of Business and Economic Statistics, 1990, 8: 225-234.
[75] Ledford, A. W., and J. A. Tawn, Statistics for near independence in multivariate extreme values, Biometrika, 1996, 83 (1): 169-187.
[76] Lee, W. Y., and R. Rao, Mean lower partial moment valuation and log normally distributed returns, Management Science, 1988, 34, 446–453.
[77] Lence, S. H. and Hayes, D.J., The Empirical Minimum-Variance Hedge, American Journal of Agricultural Economics, 1994a, 76: 94 -104.
[78] Lence, S. H. and Hayes, D.J., Parameter-Based Decision Making Under Estimation Risks: An Application in Futures Trading, Journal of Finance, 1994b, 49: 345 - 357.
[79] Lien, D., The Effect of the Cointegrating Relationship on Futures Hedging: A Note, The Journal of Futures Markets, 1996, 16 (7): 773-780.
[80] Lien, D., A Note on Loss Aversion and Futures Hedging, Journal of Futures Markets, 2000, forthcoming.
[81] Lien, D. and Luo, X., Estimating multiperiod hedge ratios in cointegrated markets, Journal of Futures Markets, 1993, 13: 909–920.
[82] Lien, D. and Shaffer, D., A Note on Estimating the Minimum Extended Gini Hedge Ratio, Journal of Futures Markets, 1999, 19: 101-113.
[83] Lien, D. and Tse, Y. K., Hedging Time-Varying Downside Risk, Journal of Futures Markets, 1998, 18: 705-722.
[84] Lien, D., & Tse, T. K., Fractional Cointegration and Futures Hedging, The Journal of Futures Hedging, 1999, 19(4): 457-474.
[85] Lien, D. and Tse, Y. K., Hedging Downside Risk with Futures Contracts, Applied Financial Economics, 2000a, 10: 163-170.
[86] Lien, D. and Tse, Y. K., A Note on the Length Effect of Futures Hedging, Advances in Investment Analysis and Portfolio Management, 2001, 7: 131-143.
[87] Lien, D. and Tse, Y.K., Some recent developments in futures hedging, Journal of Economic Survey, 2002, 16 (3): 357-396.
[88] Longin, F. M., The asymptotic distribution of extreme stock market returns, Journal of Business, 1996, 69 (3): 383–408.
[89] Longin, F. M., and B. Solnik, Extreme correlation of international equity markets, Journal of Finance 2001, 56, (2, April 2001): 649–676.
[90] Loretan, M. and W. English, Evaluating correlation breakdowns during periods of market volatility, Working paper, Federal Reserve Board, Washington D.C., 2000.
[91] Malevergne, Y., and D. Sornette, Investigating extreme dependences: Concepts and tools, Working Paper, Institute of Geophysics and Planetary Physics and Department of Earth and Space Sciences, UCLA, 2002.
[92] Mandelbrot, B., The variation of certain speculative prices, Journal of Business, 1963, 36: 394-419.
[93] Mao, J., Models of capital budgeting, E-V vs E-S, Journal of Financial and Quantitative Analysis, 1970, 4: 657–675.
[94] Markowitz, Harry, Portfolio Selection, The Journal of Finance, 1952, 7(1): 77-91
[95] Mathews, K.H. and Holthausen, Jr., D. M., A simple multi period minimum risk hedge model, American Journal of Agricultural Economics, 1991, 73: 1020-1026.
[96] Michael S. Haigh and Matthew T. Holt, Combining Time-Varying and Dynamic Multi-Period Optimal Hedging Models, European Review of Agricultural Economics, 2002.
[97] Myers, R. J., & Thompson, S. R., Generalized Optimal Hedge Ratio Estimation, American Journal of Agricultural Economics, 1989: 858-867.
[98] Nelsen, R. B., An introduction to copulas, New York: Springer, 1998.
[99] O'Hara, Maureen, Market Microstructure Theory, Cambridge, MA: Blackwell Publishers Inc., 1995.
[100] Park, H. Y., and Bera, A. K., Interest-Rate Volatility, Basis Risk and Het-eroskedasticity in Hedging Mortgages, Journal of American Real Estate and Urban Economic Analysis, 1987, 15:79–97.
[101] Patton, A. and Skewness, J., Asymmetric Dependence, and Portfolios, Working paper, London School of Economics & Political Science, 2002.
[102] Pennings, J.M.E. and Leuthold, R.M., Commodity futures contract viability: a multidisciplinary approach, OFOR Paper, 1999: 99-102.
[103] Perez-Quiros, G. and Timmerman, A., Firm size and cyclical variations in stock returns, The Journal of Finance, 2000, 55: 1229-1262.
[104] Petty, J. W. and D. F. Scott, Capital budgeting practices in large American firms: A retrospective analysis and update in Derkinderen, G. J. and R. L. Crum (eds), Readings in Strategies for Corporate Investment, Boston: Pitman Publishing, 1981.
[105] Pickands, J., Statistical inference using extreme order statistics, Annals of Statistic, 1975, 3: 119–131.
[106] Robert F. Engle, Autoregressive Conditional Heteroskedasticity with Estimates of the Variance of U.K. Inflation,Econometrics,1982, Vol.50:987-1008.
[107] Robert F. Engle and T. Bollersler, Modeling the Persistence of Conditional Variances,Econometric Reviews, 1986, Vol.5: 1-50.
[108] Robert R. Trippi and Richard B. Harriff, Dynamic Asset Allocation Rules: Survey and Synthesis, Journal of Portfolio Management, 1991, 4: 19-26.
[109] Sarno, L. and Valente, G., The cost of carry model and regime shifts in stock index futures markets: An empirical investigation, The Journal of Futures Markets, 2002, 20: 603-624.
[110] Sayantani Ghose, Downside Risk in the DJ-AIG Commodity Index Futures Market, working paper, University of Rochester, 2005.
[111] Sephton, Peter S., Optimal Hedge Ratios at the Winnipeg Commodity Exchange, The Canadian Journal of Economics, 1993, 26 (1): 175-193.
[112] Shalit, H. and Yitzhaki, S., Mean-Gini, Portfolio Theory and the Pricing of Risky Assets, Journal of Finance, 1984, 38: 1449-1468.
[113] Silvapulle, P. and C. W. Granger, Large returns, conditional correlation and portfolio diversification: A value-at-risk approach, Quantitative Finance, 2001, 1: 542–551.
[114] Silverman, B.W., density Estimation for statistics and Data Analysis, NY: Chap-man and Hall, 1986.
[115] Stein, J. L., The Simultaneous Determination of Spot and Futures Prices, American Economic Review, 1961, 51: 1012-1025.
[116] Tawn, J. A., Bivariate extreme value theory, Models and estimation, Biometrika, 1988, 75: 397-415.
[117] Tehranian, Hassan, Empirical Studies in Portfolio Performance Using Higher Degrees of Stochastic Dominance, The Journal of Finance, 1980, 35(1): 159-171.
[118] Tim Bollerslev,Ray Y. Chou and Kenneth F. Kroner, ARCH Modeling in Finance:A Review of the Theory and Empirical Evidence,Econometrics, 1992, Vol.52:5-59
[119] Tse, Y.K., Lead—Lag Relationship between Spot and Futures Prices of the Nikkei Stock Average. Journal of Forecasting. 1995, 14: 553-563.
[120] Uhlig, H., Bayesian Vector Autoregressions with Stochastic Volatility, Econometrica, 1997, 65: 59-73.
[121] Wahab, M. and Lashgari, M., Price Dynamics and Error Correction in Stock Index and Stock Index Futures Markets: A Cointegration Approach, Journal of Futures Markets, 1993, 13: 711 -742.
[122] Wei, G., Hu, T. Z., Supermodular dependence ordering on a class of multivariate copulas, Statistics and Probability Letters, 2002, 57(4): 375-385.
[123] Working H., New concepts concerning futures markers and prices, American Economic Reviews, 1952, 52:431-459.
[124] Yeh, S.C. and Gannon, G.L., Comparing trading performance of the constant and dynamic hedge models: a note, Review of Quantitative Finance and Accounting, 2000, 14:155-160.
[125] Yitzhaki, S, On an Extension of the Gini Inequality Index, International Economic Review, 1983, 24: 617-628.
[126] 曹瑞庆,何晓彬,我国期货市场套期保值比率的估计方法, 统计与决策,2005(7 下):98-100。
[127] 崔援民,杨春鹏,限定亏损概率下期货交易中的套期保值比率研究,预测,1999(2):63-70。
[128] 陈晓红,林孝贵,套期保值交易时机分析,中南工业大学学报,2000(6):213-315。
[129] 冯春山,吴家春,蒋馥,石油期货套期保值时变套期比研究,上海理工大学学报,2004(26):328-332。
[130] 管炎彬,童宛生,期货市场流动性研究,中国期货业协会 2001 年重点课题,北京工商大学证券期货研究所,深圳金牛期货经纪有限公司,2002。
[131] 郭峰,动态套期保值策略的模拟检验及在我国的应用,浙江大学硕士论文,2002。
[132] 韩高峰,鲍建平,商品期货市场尾部相关性初探,证卷市场导报,2005(2):45-49。
[133] 何晓彬,周恒,对我国期货市场套期保值有效性的测度,统计与决策,2006(7 下):56-59。
[134] 花俊洲,吴冲峰, 期铜套期保值有效性实证研究[J]. 系统工程理论方法应用, 2003,(9):204-208。
[135] 华仁海,仲伟俊,上海期货交易所期货价格有效性的实证检验,数量经济技术经济研究,2003,(1):133-136。
[136] 华仁海,陈百助,我国期货市场期货价格收益及波动方差的长记忆性研究,金融研究,2004(2):52-61。
[137] 华仁海,上海期货交易所铜、铝套期保值问题研究,中国金融学,2004(5):169-183。
[138] 华仁海,仲伟俊, 我国期货市场期货价格波动与成交量和空盘量动态关系的实证分析[J]. 数量经济与技术经济研究, 2004,(7):123-132。
[139] 华仁海,我国期货市场期货价格收益及条件波动方差的周日历效应研究,统计研究,2004(8):33-37。
[140] 华仁海,现货价格和期货价格之间的动态关系:基于上海期货交易所的经验研究,世界经济,2005(8):32-39。
[141] 黄长征,期货套期保值决策模型研究,数量经济技术经济研究,2004(7):96-102。
[142] 蒋涛. 中国沪深股票市场流动性研究, [C]深交所研究报告,2002。
[143] 李国荣,吴大为,余方平,基于差异系数 σ / μ的期货套期保值优化策略,系统工程,2005(8):78-81。
[144] 李萌,余思勤,袁象,计算股指期货套期保值比率的新方法——LPM 法,当代经济,2005(4):35-36。
[145] 李暮春,张国元,期货市场流动性研究,大连商品交易所课题,2002。
[146] 梁朝晖,张维,套期保值计算模型在中国市场的有效性,天津大学学报(博士后专刊),2006,283-287。
[147] 林孝贵,陈晓红,套期保值率的最小二乘估计,中南工业大学学报,2000(6):128-129
[148] 林孝贵,期货套期保值的最小二阶矩方法,应用概率统计,2002(8):239-243。
[149] 林孝贵,期货市场逐步组合套期保值的理论与方法,系统工程理论与实践,2002(11):100-103。
[150] 林孝贵,基于收益与风险比率的期货套期保值策略,系统工程,2004(1):74-77。
[151] 林孝贵,期货套期保值最大概率于最小风险分析,数学的实践与认识,2004(5):24-29
[152] 林孝贵,二重期货套期保值模型及其代数解法,广西工学院学报,2004,(9):22-26。
[153] 刘卉,李晔,王远志,中国期货市场波动性交易量市场深度动态关系的日内特征分析,长春理工大学学报,2005(12):44-48。
[154] 罗俊鹏,史道济,徐付霞,SHFE 和 LME 期铜相关模式的研究,西北农林科技大学学报,2006(9):69-74。
[155] 欧阳资生,极值估计在金融保险中的应用,北京:中国经济出版社,2006,16-34,168-186。
[156] 齐明亮,套期保值比率与套期保值的绩效——上海期铜合约的套期保值实证分析,华中科技大学学报,2004(2):51-54。
[157] 司继文,蒙坚玲,龚朴,国内外期货市场相关性研究,华中科技大学学报,2004(12):16-19。
[158] 申唯正,上海期货市场流动性实证研究,期货日报,2004.03.04。
[159] 唐小我,马永开,组合套期保值策略及其理论研究[EJ].预测,1999,(4):48—51.
[160] 汪贵浦,王明涛,Harlow 下偏矩证券组合优化模型的求解方法研究,系统工程理论与实践,2003(6):42-47。
[161] 汪炜,杜利辉,基于协整关系的中国大豆期货合约套期保值策略,粮食经济研究, 2005(1):25-29。
[162] 王骏,张宗成,赵昌旭,中国硬麦和大豆期货市场套期保值绩效的实证研究,中国农业大学学报,2005(4):131-137。
[163] 王骏,张宗成,SHFE 金属铜期货的套期保值比率与绩效,统计与决策,2005(5 下)41-43。
[164] 王明涛,王秋红,基于下偏矩的资源配置优化模型求解方法研究,郑州工业大学学报,2001(12):38-42。
[165] 王乃生,上海期货市场流动性研究,证券市场导报,2004, (8): 44-49。
[166] 王远志,李晔,刘卉,上海期铜日内交易特征的实证研究,天津工业大学学报,2005(4):76-80。
[167] 王征,樊治平,张权,期货套期保值的多期多目标规划模型,系统工程,1997(3):50-53。
[168] 吴冲锋,冯芸等, 深圳股票市场流动性研究,[C]深交所研究报告,2002。
[169] 吴冲锋,钱宏伟,吴文锋,期货套期保值理论与实证研究(Ⅰ),系统工程理论方法应用,1998(4):20-26。
[170] 吴文锋,刘太阳,叶中行,上海与伦敦期铜市场风险变异性实证研究,系统工程理论方法应用,2006(6):256-259。
[171] 杨春鹏等, 限定亏损概率下期权交易中的套期保值比率研究,预测, 2000,3。
[172] 张建刚,中国期货市场品种创新研究,博士论文,天津大学,2006。
[173] 张维,梁朝晖,期货交易与风险管理,中国期货业协会研究报告,2006。
[174] 张小艳,张宗成,期货市场有效性理论与实证检验,中国管理科学,2005(6):1-5。
[175] 张亦春,林海,自融资交易策略、复制资产组合和风险管理,河南金融管理干部学院学报,2003(6):25-27。
[176] 周蓓,齐中英,周春伟,沪铜期货收益波动性的分阶段实证研究,技术经济于管理研究,2006(3):42-45。
[2] Alizadeh, A. and Nomikos, N., A Markov Regime Switching Approach for Hedging Stock Indices, The Journal of Futures Markets, 2004, 24 (7): 649-674.
[3] Amihud, Y. and Mendelson, H., The effect of computer base trading on volatility and liquidity, H.C. Lucas, 1989.
[4] Anderson, R.W. and Danthine, J.P., The time pattern of hedging and the volatility of futures prices, Review of Economic Studies, 1983, 50: 249-266.
[5] Ang, A. and G. Bekaert, International asset allocation with time-varying correlations, Working paper, Columbia University, 2000.
[6] Ang, A., J. Chen and Y. Xing, Downside risk and the momentum effect, Working paper, Columbia University, 2001.
[7] Ang, A. and J. Chen, Asymmetric correlations of equity portfolios, Journal of Financial Economics, 2002, 63, No. 3 (March 2002): 637–654.
[8] Baillie, R. T. and R. Myers, Bivariate GARCH estimation of the optimal commodity futures hedge, Journal of Applied Econometrics, 1991, 6: 109-124.
[9] Balke, N. S. and Fomby, T. B., Threshold Cointegration, International Economic Review, 1997, 38: 627 - 645.
[10] Balkema, A. and L. de Haan, Residual life time at great age, Annals of Probability, 1974, 55: 792–804.
[11] Bawa, V.S., Safely-first, stochastic dominance and optimal portfolio choice, Journal of Financial and Quantitative Analysis, 1978, 33: 25- 71.
[12] Bekaert, G. and C. R. Harve, Emerging equity market volatility, Journal of Financial Economics 1997, 43: 29–77.
[13] Bekaert, G. and C. R. Harvey, Foreign speculators and emerging equity markets, Journal of Finance, 2000, 55 (2): 565–613.
[14] Bekaert, G. and G. Wu, Asymmetric volatility and risk in equity markets, Review of Financial Studies, 2000, 13 (1): 1–42.
[15] Bell, D.E. and Krasker, W.S., Estimating Hedge Ratios, Financial Management, 1986, 15:34-39.
[16] Bollerslev, T., Generalized autoregressive conditional heteroscedasticity, Journal of Economics, 1986, 31: 307-327.
[17] Bollerslev, T., Chou, R.Y. and Kroner, K.F., ARCH modeling in finance: A review of the theory and empirical literature, Journal of Econometrics, 1992, 52 (1): 5-59.
[18] Bookstaber, R., Global risk management: Are we missing the point? Journal of Portfolio Management, 1997: 102-107.
[19] Boyer, B. H., M. S. Gibson and M. Loretan, Pitfalls in tests for changes in correlations, International Finance Discussion Papers, No. 597R, Board of Governors of the Federal Reserve System, March 1999.
[20] Broll, U., Chow, K.W. and Wong, K.P., Hedging and Nonlinear Risk Exposure, Oxford economic papers, 2000, Forthcoming.
[21] Brooks, C., O. T. Henry, and G. Persand, The effect of asymmetries on optimal hedge ratios, Journal of Business, 2002, 75 (2, April 2002): 333-352.
[22] Campbell, J. Y., M. Lettau, B. G. Malkiel, and Y. Xu, Have individual stocks become more volatile? An empirical exploration of idiosyncratic risk, Journal of Finance, 2001,56 (1): 1-43.
[23] Campbell, R., K. Koedjik, and P. Kofman, Increased correlations in bear markets, Financial Analysts Journal, 2002, 24(January/February 2002): 87-94.
[24] Cecchetti, Stephen G., Cumby, Robert E. and Figlewski, Stephen, Estimation of the Optimal Futures Hedge, The Review of Economics and Statistics, 1988, 70 (4): 623-630.
[25] Charles J. Jacklin, Allan W. Kleidon, and Paul Pfleiderer, Underestimation of Portfolio Insurance and the Crash of October 1987, Review of Financial Studies, 1992, 1:35-63.
[26] Charnes M. John, Asymmetric Correlation of Future Markets and Optimal Hedging, working paper, Kansas University, 2003.
[27] Chou, W. L., Fan, K. K., & Lee, C. F., Hedging with the Nikkei index futures: The conventional model versus the error correction model, Quarterly Review of Economics and Finance, 1996, 36: 495–505.
[28] Chow, G., E. Jacquier, M. Kritzman, and K. Lowry, Optimal portfolios in good times and bad, Financial Analysts Journal, 1999 (May/June): 65-73.
[29] Cornew, R., Crowson, L., and Town, D., Stable Distributions and Commodity Price and Performance Measurements, The Journal of Futures Markets, 1984, 4: 531-557.
[30] Das, S. and R. Uppa, Systemic risk and portfolio choice, Working paper, London Business School, 2001.
[31] Davison, A. C. and R. L. Smith, Models for exceedances over high thresholds (with Discussion), Journal of the Royal Statistical Society, 1990,B 53, 377–392.
[32] De Santis, G., B. Gerard, and P. Hillion, The relevance of currency risk in the EMU, Working paper, UCLA, 1999
[33] Dickey, D.A. and Fuller, W.A., Distribution of Estimators for Time Series Regressions with a Unit Root, Journal of the American Statistical Association, 1979, 74,427-431.
[34] Duffee, G. R, Stock returns and volatility: A firm-level analysis, Journal of Financial Economics, 1995, 37, 399–420.
[35] Ederington, L. H., The Hedging Performance of the New Futures Markets, The Journal of Finance, 1979, XXXIV (1), 157-170.
[36] Embrechets, P., Mcneil, A. and Traumann, U. S., Correlation and dependency in risk management: properties and pitfalls, http:// www.math.ethz.ch/~mcneil/ftp/pitfalls.pdf, 2000-12-26.
[37] Engle, R.F., Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation, Econometrica, 1982, 50: 987-1007.
[38] Engle, R.F. and Bollerslev, T., Modeling the persistence of conditional variances, Econometric Reviews, 1986, 5: 1-50, 81-87.
[39] Engle R.F. and Kroner K.F., Multivariate simultaneous generalized Arch Econometric Theory, 1995, 11:122-150.
[40] Fama, Eugene. F., Portfolio Analysis in a Stable Paretian Market, Management Science, 1965, 11(3, Series A, Sciences): 404-419.
[41] Fama, E.F. and French, K., Commodity futures prices: Some evidence on forecast power, premiums and the theory of storage, The Journal of Business, 1987, 60: 55-73.
[42] Fishburn, P.J., Mean-risk analysis with risk associated with below-target retures, American Economic review, 1977, 67: 116-126.
[43] Fong, W.M. and See, K.H., A Markov switching model of the conditional volatility of crude oil prices, Energy Economics, 2002, 35: 71-95.
[44] Garbade, K. D. and Silber, W. L. , Price Movements and Price Discovery in Futures and Cash Markets, Review of Economics and Statistics, 1983, 65: 289-297.
[45] Ghosh, A., Hedging with stock index futures: estimation and forecasting with error correction model, Journal of Futures Markets, 1993, 13: 743-752.
[46] Glen R., Components of The Bid-ask Spread and The statistical properties of Transaction prices, Journal of Finance, 1994, 42: 1293-1308.
[47] Granger, C. W. J., Developments in the Study of Cointegrated Economic Variables, Oxford Bulletin of Economics and Statistics, 1986, 48: 213-228.
[48] Gray, R.W. and Rutledge, D.J.S., The economics of commodity futures markets: A survey, Review of Marketing and Agricultural Economics, 1971.
[49] Gray, S. F., Modeling the conditional distribution of interest rates as a regime switching process, Journal of Financial Economics, 1996, 42: 27–62.
[50] Haigh, M.S. and Holt, M.T., Hedging multiple price uncertainty in international grain trade, American Journal of Agricultural Economics, 2000, 82: 881-896.
[51] Hamilton, James D., A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle, Econometrica, 1989, 57 (2): 357-384.
[52] Hardle, W., Applied nonparametric regression, Cambridge England: Cambridge University Press, 1990.
[53] Harlow W V., Asset allocation in a downside risk framework, Financial Analysts Journal, 1991, Sep-Oct: 28-40.
[54] Hasbrouck, Joel and Seppi, Duane J., Common factors in prices, order flows, and liquidity, Journal of Financial Economics, 2001, 59: (383-411).
[55] Helms, B., and Martell, T., An Examination of the Distribution of Commodity Price Changes, Journal of Futures Markets, 1985, 5: 259-272.
[56] Herbst, A. F., Kare, D. D., and Marshall, J. F., A Time Varying, Convergence Adjusted, Minimum Risk Futures Hedge Ratio, Advances in Futures and Options Research. 1993, 6: 137-155.
[57] Hogan, William W. and Warren, James M., Computation of the Efficient Boundary in the E-S Portfolio Selection Model, The Journal of Financial and Quantitative Analysis, 1972, VII (4): 1881.
[58] Hogan, William W. and Warren, James M., Toward the development of an equilibrium capita-market model based on semivariance, Journal of Financial and Quantitative Analysis, January 1974: 1.
[59] Howard C T, D’Antonio L J., A risk-return measure of hedging effectiveness, Journal of Financial and Quantitative Analysis, 1984,19: 101-112.
[60] Hsiang-Tai Lee, Jonathan Yoder, R.C. Mittelhammer and Jill J. McCluskey, A Random Coefficient Autoregressive Markov Regime Switching Model of Dynamic Futures Hedging, Journal of Futures Markets, 2006, 26 (2): 103-129.
[61] Hull, J. C., Introduction to Futures and Options Markets, 3rd Edition, New Jersey: Prentice Hall, 1998.
[62] Jansen, D. W., and C. G. Devries, On the frequency of large stock returns: Putting booms and busts into perspectives, Review of Economics and Statistics, 1991, 73: 18–24.
[63] Jenkinson, A. F., The frequency distribution of the annual maximum (or minimum) values of meteorological elements, Quarterly Journal of the Royal Meteorological Society, 1955, 81: 145–158.
[64] John C. Hull, Options, Futures, and Other Derivative Securities, New York: Prentice-Hall, 1993.
[65] Johnson, L. L., The Theory of Hedging and Speculation in Commodity Futures, Review of Economic Studies, 1960, 27: 139-151.
[66] J.R.Hicks,Value and capital, London:Oxford University Press, 1946(2nd edition)
[67] Kahl, K.H., Determination of the recommended hedging ratio, American Journal of Agricultural Economics, 1983, 65: 603-605.
[68] Kahneman, D., and Tversky, A., Prospect Theory: An Analysis of Decision under Uncertainty, Econometrica, 1979, 47: 263-291.
[69] Keynes,J.M.,A Treatiseon Money, Vol,Ⅱ,London:Macmillan, 1930.
[70] Kim, C.J., source of monetary growth uncertainty and economic activity: The time-varying-parameter model with heteroskedastic disturbances, The review of economics and statistic, 1993b, 75: 483-492.
[71] Kolb, R. W. and Okunev, J., Utility Maximizing Hedge Ratios in the Extended Mean-Gini Framework, Journal of Futures Markets, 1993,13: 597-609.
[72] Krolzig, H.M., statistical analysis of cointegrated VAR processes with Markovian regime shifts, Unpublished manuscript, Department of Economics, University of Oxford, 1993.
[73] Kyle, Albert S., Continuous auctions and insider trading [J], Econometrica, 1985, 53:1315-1335.
[74] Lamoureux, C.G. and Lastrapes, W.D., Persistence in variance, structural change, and the GARCH model, Journal of Business and Economic Statistics, 1990, 8: 225-234.
[75] Ledford, A. W., and J. A. Tawn, Statistics for near independence in multivariate extreme values, Biometrika, 1996, 83 (1): 169-187.
[76] Lee, W. Y., and R. Rao, Mean lower partial moment valuation and log normally distributed returns, Management Science, 1988, 34, 446–453.
[77] Lence, S. H. and Hayes, D.J., The Empirical Minimum-Variance Hedge, American Journal of Agricultural Economics, 1994a, 76: 94 -104.
[78] Lence, S. H. and Hayes, D.J., Parameter-Based Decision Making Under Estimation Risks: An Application in Futures Trading, Journal of Finance, 1994b, 49: 345 - 357.
[79] Lien, D., The Effect of the Cointegrating Relationship on Futures Hedging: A Note, The Journal of Futures Markets, 1996, 16 (7): 773-780.
[80] Lien, D., A Note on Loss Aversion and Futures Hedging, Journal of Futures Markets, 2000, forthcoming.
[81] Lien, D. and Luo, X., Estimating multiperiod hedge ratios in cointegrated markets, Journal of Futures Markets, 1993, 13: 909–920.
[82] Lien, D. and Shaffer, D., A Note on Estimating the Minimum Extended Gini Hedge Ratio, Journal of Futures Markets, 1999, 19: 101-113.
[83] Lien, D. and Tse, Y. K., Hedging Time-Varying Downside Risk, Journal of Futures Markets, 1998, 18: 705-722.
[84] Lien, D., & Tse, T. K., Fractional Cointegration and Futures Hedging, The Journal of Futures Hedging, 1999, 19(4): 457-474.
[85] Lien, D. and Tse, Y. K., Hedging Downside Risk with Futures Contracts, Applied Financial Economics, 2000a, 10: 163-170.
[86] Lien, D. and Tse, Y. K., A Note on the Length Effect of Futures Hedging, Advances in Investment Analysis and Portfolio Management, 2001, 7: 131-143.
[87] Lien, D. and Tse, Y.K., Some recent developments in futures hedging, Journal of Economic Survey, 2002, 16 (3): 357-396.
[88] Longin, F. M., The asymptotic distribution of extreme stock market returns, Journal of Business, 1996, 69 (3): 383–408.
[89] Longin, F. M., and B. Solnik, Extreme correlation of international equity markets, Journal of Finance 2001, 56, (2, April 2001): 649–676.
[90] Loretan, M. and W. English, Evaluating correlation breakdowns during periods of market volatility, Working paper, Federal Reserve Board, Washington D.C., 2000.
[91] Malevergne, Y., and D. Sornette, Investigating extreme dependences: Concepts and tools, Working Paper, Institute of Geophysics and Planetary Physics and Department of Earth and Space Sciences, UCLA, 2002.
[92] Mandelbrot, B., The variation of certain speculative prices, Journal of Business, 1963, 36: 394-419.
[93] Mao, J., Models of capital budgeting, E-V vs E-S, Journal of Financial and Quantitative Analysis, 1970, 4: 657–675.
[94] Markowitz, Harry, Portfolio Selection, The Journal of Finance, 1952, 7(1): 77-91
[95] Mathews, K.H. and Holthausen, Jr., D. M., A simple multi period minimum risk hedge model, American Journal of Agricultural Economics, 1991, 73: 1020-1026.
[96] Michael S. Haigh and Matthew T. Holt, Combining Time-Varying and Dynamic Multi-Period Optimal Hedging Models, European Review of Agricultural Economics, 2002.
[97] Myers, R. J., & Thompson, S. R., Generalized Optimal Hedge Ratio Estimation, American Journal of Agricultural Economics, 1989: 858-867.
[98] Nelsen, R. B., An introduction to copulas, New York: Springer, 1998.
[99] O'Hara, Maureen, Market Microstructure Theory, Cambridge, MA: Blackwell Publishers Inc., 1995.
[100] Park, H. Y., and Bera, A. K., Interest-Rate Volatility, Basis Risk and Het-eroskedasticity in Hedging Mortgages, Journal of American Real Estate and Urban Economic Analysis, 1987, 15:79–97.
[101] Patton, A. and Skewness, J., Asymmetric Dependence, and Portfolios, Working paper, London School of Economics & Political Science, 2002.
[102] Pennings, J.M.E. and Leuthold, R.M., Commodity futures contract viability: a multidisciplinary approach, OFOR Paper, 1999: 99-102.
[103] Perez-Quiros, G. and Timmerman, A., Firm size and cyclical variations in stock returns, The Journal of Finance, 2000, 55: 1229-1262.
[104] Petty, J. W. and D. F. Scott, Capital budgeting practices in large American firms: A retrospective analysis and update in Derkinderen, G. J. and R. L. Crum (eds), Readings in Strategies for Corporate Investment, Boston: Pitman Publishing, 1981.
[105] Pickands, J., Statistical inference using extreme order statistics, Annals of Statistic, 1975, 3: 119–131.
[106] Robert F. Engle, Autoregressive Conditional Heteroskedasticity with Estimates of the Variance of U.K. Inflation,Econometrics,1982, Vol.50:987-1008.
[107] Robert F. Engle and T. Bollersler, Modeling the Persistence of Conditional Variances,Econometric Reviews, 1986, Vol.5: 1-50.
[108] Robert R. Trippi and Richard B. Harriff, Dynamic Asset Allocation Rules: Survey and Synthesis, Journal of Portfolio Management, 1991, 4: 19-26.
[109] Sarno, L. and Valente, G., The cost of carry model and regime shifts in stock index futures markets: An empirical investigation, The Journal of Futures Markets, 2002, 20: 603-624.
[110] Sayantani Ghose, Downside Risk in the DJ-AIG Commodity Index Futures Market, working paper, University of Rochester, 2005.
[111] Sephton, Peter S., Optimal Hedge Ratios at the Winnipeg Commodity Exchange, The Canadian Journal of Economics, 1993, 26 (1): 175-193.
[112] Shalit, H. and Yitzhaki, S., Mean-Gini, Portfolio Theory and the Pricing of Risky Assets, Journal of Finance, 1984, 38: 1449-1468.
[113] Silvapulle, P. and C. W. Granger, Large returns, conditional correlation and portfolio diversification: A value-at-risk approach, Quantitative Finance, 2001, 1: 542–551.
[114] Silverman, B.W., density Estimation for statistics and Data Analysis, NY: Chap-man and Hall, 1986.
[115] Stein, J. L., The Simultaneous Determination of Spot and Futures Prices, American Economic Review, 1961, 51: 1012-1025.
[116] Tawn, J. A., Bivariate extreme value theory, Models and estimation, Biometrika, 1988, 75: 397-415.
[117] Tehranian, Hassan, Empirical Studies in Portfolio Performance Using Higher Degrees of Stochastic Dominance, The Journal of Finance, 1980, 35(1): 159-171.
[118] Tim Bollerslev,Ray Y. Chou and Kenneth F. Kroner, ARCH Modeling in Finance:A Review of the Theory and Empirical Evidence,Econometrics, 1992, Vol.52:5-59
[119] Tse, Y.K., Lead—Lag Relationship between Spot and Futures Prices of the Nikkei Stock Average. Journal of Forecasting. 1995, 14: 553-563.
[120] Uhlig, H., Bayesian Vector Autoregressions with Stochastic Volatility, Econometrica, 1997, 65: 59-73.
[121] Wahab, M. and Lashgari, M., Price Dynamics and Error Correction in Stock Index and Stock Index Futures Markets: A Cointegration Approach, Journal of Futures Markets, 1993, 13: 711 -742.
[122] Wei, G., Hu, T. Z., Supermodular dependence ordering on a class of multivariate copulas, Statistics and Probability Letters, 2002, 57(4): 375-385.
[123] Working H., New concepts concerning futures markers and prices, American Economic Reviews, 1952, 52:431-459.
[124] Yeh, S.C. and Gannon, G.L., Comparing trading performance of the constant and dynamic hedge models: a note, Review of Quantitative Finance and Accounting, 2000, 14:155-160.
[125] Yitzhaki, S, On an Extension of the Gini Inequality Index, International Economic Review, 1983, 24: 617-628.
[126] 曹瑞庆,何晓彬,我国期货市场套期保值比率的估计方法, 统计与决策,2005(7 下):98-100。
[127] 崔援民,杨春鹏,限定亏损概率下期货交易中的套期保值比率研究,预测,1999(2):63-70。
[128] 陈晓红,林孝贵,套期保值交易时机分析,中南工业大学学报,2000(6):213-315。
[129] 冯春山,吴家春,蒋馥,石油期货套期保值时变套期比研究,上海理工大学学报,2004(26):328-332。
[130] 管炎彬,童宛生,期货市场流动性研究,中国期货业协会 2001 年重点课题,北京工商大学证券期货研究所,深圳金牛期货经纪有限公司,2002。
[131] 郭峰,动态套期保值策略的模拟检验及在我国的应用,浙江大学硕士论文,2002。
[132] 韩高峰,鲍建平,商品期货市场尾部相关性初探,证卷市场导报,2005(2):45-49。
[133] 何晓彬,周恒,对我国期货市场套期保值有效性的测度,统计与决策,2006(7 下):56-59。
[134] 花俊洲,吴冲峰, 期铜套期保值有效性实证研究[J]. 系统工程理论方法应用, 2003,(9):204-208。
[135] 华仁海,仲伟俊,上海期货交易所期货价格有效性的实证检验,数量经济技术经济研究,2003,(1):133-136。
[136] 华仁海,陈百助,我国期货市场期货价格收益及波动方差的长记忆性研究,金融研究,2004(2):52-61。
[137] 华仁海,上海期货交易所铜、铝套期保值问题研究,中国金融学,2004(5):169-183。
[138] 华仁海,仲伟俊, 我国期货市场期货价格波动与成交量和空盘量动态关系的实证分析[J]. 数量经济与技术经济研究, 2004,(7):123-132。
[139] 华仁海,我国期货市场期货价格收益及条件波动方差的周日历效应研究,统计研究,2004(8):33-37。
[140] 华仁海,现货价格和期货价格之间的动态关系:基于上海期货交易所的经验研究,世界经济,2005(8):32-39。
[141] 黄长征,期货套期保值决策模型研究,数量经济技术经济研究,2004(7):96-102。
[142] 蒋涛. 中国沪深股票市场流动性研究, [C]深交所研究报告,2002。
[143] 李国荣,吴大为,余方平,基于差异系数 σ / μ的期货套期保值优化策略,系统工程,2005(8):78-81。
[144] 李萌,余思勤,袁象,计算股指期货套期保值比率的新方法——LPM 法,当代经济,2005(4):35-36。
[145] 李暮春,张国元,期货市场流动性研究,大连商品交易所课题,2002。
[146] 梁朝晖,张维,套期保值计算模型在中国市场的有效性,天津大学学报(博士后专刊),2006,283-287。
[147] 林孝贵,陈晓红,套期保值率的最小二乘估计,中南工业大学学报,2000(6):128-129
[148] 林孝贵,期货套期保值的最小二阶矩方法,应用概率统计,2002(8):239-243。
[149] 林孝贵,期货市场逐步组合套期保值的理论与方法,系统工程理论与实践,2002(11):100-103。
[150] 林孝贵,基于收益与风险比率的期货套期保值策略,系统工程,2004(1):74-77。
[151] 林孝贵,期货套期保值最大概率于最小风险分析,数学的实践与认识,2004(5):24-29
[152] 林孝贵,二重期货套期保值模型及其代数解法,广西工学院学报,2004,(9):22-26。
[153] 刘卉,李晔,王远志,中国期货市场波动性交易量市场深度动态关系的日内特征分析,长春理工大学学报,2005(12):44-48。
[154] 罗俊鹏,史道济,徐付霞,SHFE 和 LME 期铜相关模式的研究,西北农林科技大学学报,2006(9):69-74。
[155] 欧阳资生,极值估计在金融保险中的应用,北京:中国经济出版社,2006,16-34,168-186。
[156] 齐明亮,套期保值比率与套期保值的绩效——上海期铜合约的套期保值实证分析,华中科技大学学报,2004(2):51-54。
[157] 司继文,蒙坚玲,龚朴,国内外期货市场相关性研究,华中科技大学学报,2004(12):16-19。
[158] 申唯正,上海期货市场流动性实证研究,期货日报,2004.03.04。
[159] 唐小我,马永开,组合套期保值策略及其理论研究[EJ].预测,1999,(4):48—51.
[160] 汪贵浦,王明涛,Harlow 下偏矩证券组合优化模型的求解方法研究,系统工程理论与实践,2003(6):42-47。
[161] 汪炜,杜利辉,基于协整关系的中国大豆期货合约套期保值策略,粮食经济研究, 2005(1):25-29。
[162] 王骏,张宗成,赵昌旭,中国硬麦和大豆期货市场套期保值绩效的实证研究,中国农业大学学报,2005(4):131-137。
[163] 王骏,张宗成,SHFE 金属铜期货的套期保值比率与绩效,统计与决策,2005(5 下)41-43。
[164] 王明涛,王秋红,基于下偏矩的资源配置优化模型求解方法研究,郑州工业大学学报,2001(12):38-42。
[165] 王乃生,上海期货市场流动性研究,证券市场导报,2004, (8): 44-49。
[166] 王远志,李晔,刘卉,上海期铜日内交易特征的实证研究,天津工业大学学报,2005(4):76-80。
[167] 王征,樊治平,张权,期货套期保值的多期多目标规划模型,系统工程,1997(3):50-53。
[168] 吴冲锋,冯芸等, 深圳股票市场流动性研究,[C]深交所研究报告,2002。
[169] 吴冲锋,钱宏伟,吴文锋,期货套期保值理论与实证研究(Ⅰ),系统工程理论方法应用,1998(4):20-26。
[170] 吴文锋,刘太阳,叶中行,上海与伦敦期铜市场风险变异性实证研究,系统工程理论方法应用,2006(6):256-259。
[171] 杨春鹏等, 限定亏损概率下期权交易中的套期保值比率研究,预测, 2000,3。
[172] 张建刚,中国期货市场品种创新研究,博士论文,天津大学,2006。
[173] 张维,梁朝晖,期货交易与风险管理,中国期货业协会研究报告,2006。
[174] 张小艳,张宗成,期货市场有效性理论与实证检验,中国管理科学,2005(6):1-5。
[175] 张亦春,林海,自融资交易策略、复制资产组合和风险管理,河南金融管理干部学院学报,2003(6):25-27。
[176] 周蓓,齐中英,周春伟,沪铜期货收益波动性的分阶段实证研究,技术经济于管理研究,2006(3):42-45。