远期运费协议价格波动与交易量相关性研究——基于VAR-EGARCH-X模型的实证分析
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摘要
针对全球金融危机后航运金融市场的巨变,运用VAR-EGARCH-X模型,研究从2007第三季度至2014年第四季度的干散货远期市场中远期运费协议价格波动与交易量的关系。结论显示FFA价格变化将造成交易量变动,表明更高的资本收益会鼓励更多的交易,但交易量的变动对FFA价格变化的影响极为有限。然而,交易量与价格波动性之间存在着同一时期的正相关,符合金融市场的实际表现与混合分布假说理论。最后发现,价格波动幅度的扩大会导致FFA交易量的减少。
Aiming at the changes of shipping financial market after global financial crisis, this paper uses VAR-EGARCH-X model to study the relationship between the price fluctuation in forward freight agreement in dry bulk forward market and trading volume from Quarter 3, 2007 to Quarter 4, 2014. The conclusion reveals that FFA price change will result in trading volume change, which indicates the higher capital profit will encourage more trade, but the influence of trading volume change on FFA price is very limited. Whereas, there is contemporaneous positive correlation between trading volume and price fluctuation, and it is in accordance with the practical behavior of financial market and mixture distribution hypothesis theory. Eventually, the enlargement in price fluctuation will reduce the FFA trading volume.
Aiming at the changes of shipping financial market after global financial crisis, this paper uses VAR-EGARCH-X model to study the relationship between the price fluctuation in forward freight agreement in dry bulk forward market and trading volume from Quarter 3, 2007 to Quarter 4, 2014. The conclusion reveals that FFA price change will result in trading volume change, which indicates the higher capital profit will encourage more trade, but the influence of trading volume change on FFA price is very limited. Whereas, there is contemporaneous positive correlation between trading volume and price fluctuation, and it is in accordance with the practical behavior of financial market and mixture distribution hypothesis theory. Eventually, the enlargement in price fluctuation will reduce the FFA trading volume.
引文
[1]Kavussanos M G,Visvikisand Menachof.D.A.The unbiasedness hypothesis in the freight forward market:evidence from cointegration tests[J].Review of Derivatives Research,2004(3):241-266.
[2]Kavussanos M G,Visvikis I D.Market interactions in returns and volatilities between spot and forward shipping freight markets[J].Journal of Banking&Finance,2004(8):2015-2049.
[3]杨柳.干散货FFA市场与现货市场的关系[J].中国远洋航务,2007(3):48-49.
[4]Clark,P.K.A subordinated stochastic process model with finite variance for speculative prices[J].Econometrica1973(41):135-155.?
[5]Karpoff,J.M.The relationship between price changes and trading volume:a survey[J].Journal of Financial and Quantitative Analysis,1987(22):109-126.
[6]Copeland,T.E.A model for asset trading under the assumption of sequential information arrival[J].Journal of Finance,1976(31):1149-1168.
[7]Harris,L.Cross-security tests of the mixture-of-distributions hypothesis[J].Journal of Financial and Quantitative Analysis 1986(21):39-46.
[8]Gallant,R.,Rossi,P.,Tauchen,G.Stock prices and volume[J].Review of Financial Studies 1992(5):199-242.?
[9]Gervais,K.R.,Kaniel,R.,Mingelgrin,D.H.The highvolume return premium[J].The Journal of Finance 2001(56):877-919.
[10]Hiemstra,C.,Jones,J.Testing for linear and non-linear Granger causality in the stock price–volume relationship[J].Journal of Finance 1994(49):1639-1664.
[11]Llorente,Guillermo,Michaely,Roni,Saar,Gideon,Wang,Jiang.Dynamic volume–return relation of individual stocks[J].Review of Financial Studies,2002(4):1005-1047.
[12]Nelson,D.B..Conditional heteroscedasticity in asset returns:a new approach[J].Econometrica,1991(59):347-370.
[13]陈海萍.FFA市场亟待信息透明化[R].航运交易公报,2012(47).
[14]Kavussanos,M.The dynamics of time-varying volatilities in different size second-hand ship prices of the dry-cargo sector[J].Applied Economics 1997(29):433-443.
[15]Engle,R.F.,Autoregressive conditional heteroscedasticity with estimates of variance of United Kingdom inflation[J].Econometrica1982(4):987-1006.
[2]Kavussanos M G,Visvikis I D.Market interactions in returns and volatilities between spot and forward shipping freight markets[J].Journal of Banking&Finance,2004(8):2015-2049.
[3]杨柳.干散货FFA市场与现货市场的关系[J].中国远洋航务,2007(3):48-49.
[4]Clark,P.K.A subordinated stochastic process model with finite variance for speculative prices[J].Econometrica1973(41):135-155.?
[5]Karpoff,J.M.The relationship between price changes and trading volume:a survey[J].Journal of Financial and Quantitative Analysis,1987(22):109-126.
[6]Copeland,T.E.A model for asset trading under the assumption of sequential information arrival[J].Journal of Finance,1976(31):1149-1168.
[7]Harris,L.Cross-security tests of the mixture-of-distributions hypothesis[J].Journal of Financial and Quantitative Analysis 1986(21):39-46.
[8]Gallant,R.,Rossi,P.,Tauchen,G.Stock prices and volume[J].Review of Financial Studies 1992(5):199-242.?
[9]Gervais,K.R.,Kaniel,R.,Mingelgrin,D.H.The highvolume return premium[J].The Journal of Finance 2001(56):877-919.
[10]Hiemstra,C.,Jones,J.Testing for linear and non-linear Granger causality in the stock price–volume relationship[J].Journal of Finance 1994(49):1639-1664.
[11]Llorente,Guillermo,Michaely,Roni,Saar,Gideon,Wang,Jiang.Dynamic volume–return relation of individual stocks[J].Review of Financial Studies,2002(4):1005-1047.
[12]Nelson,D.B..Conditional heteroscedasticity in asset returns:a new approach[J].Econometrica,1991(59):347-370.
[13]陈海萍.FFA市场亟待信息透明化[R].航运交易公报,2012(47).
[14]Kavussanos,M.The dynamics of time-varying volatilities in different size second-hand ship prices of the dry-cargo sector[J].Applied Economics 1997(29):433-443.
[15]Engle,R.F.,Autoregressive conditional heteroscedasticity with estimates of variance of United Kingdom inflation[J].Econometrica1982(4):987-1006.