VEC 模型如下, 如何怎么判定模型好坏呢,R2都很低。 新手上路,先谢谢大家
Vector Error Correction Estimates
Date: 07/06/12 Time: 21:27
Sample (adjusted): 3 1319
Included observations: 1317 after adjustments
Standard errors in ( ) & t-statistics in [ ]
Cointegrating Eq: CointEq1
LSP(-1) 1.000000
LEXUSD(-1) 3.319568
(2.49599)
[ 1.32996]
C -14.41920
Error Correction: D(LSP) D(LEXUSD)
CointEq1 -0.004620 -0.000371
(0.00198) (0.00010)
[-2.33443] [-3.63481]
D(LSP(-1)) 0.015450 0.001103
(0.02756) (0.00142)
[ 0.56065] [ 0.77541]
D(LEXUSD(-1)) 0.338214 -0.109576
(0.53149) (0.02743)
[ 0.63635] [-3.99482]
C 0.001568 -0.000175
(0.00067) (3.5E-05)
[ 2.34536] [-5.06115]
SPREAD -0.001098 -9.39E-06
(0.00031) (1.6E-05)
[-3.54459] [-0.58709]
R-squared 0.010412 0.022855
Adj. R-squared 0.007395 0.019876
Sum sq. resids 0.606042 0.001614
S.E. equation 0.021492 0.001109
F-statistic 3.451046 7.671711
Log likelihood 3191.118 7094.788
Akaike AIC -4.838448 -10.76657
Schwarz SC -4.818770 -10.74689
Mean dependent 0.000460 -0.000165
S.D. dependent 0.021572 0.001120
Determinant resid covariance (dof adj.) 5.68E-10
Determinant resid covariance 5.64E-10
Log likelihood 10286.09
Akaike information criterion -15.60226
Schwarz criterion -15.55503