我用rat软件做的VAR-DCC-GARCH,有两种不同形式的结果,但我不明白他们的区别,请教大家!
GARCH(P=1,Q=1,model=varbefore,mv=DCC,hmatrices=hd,rvectors=rd,dist=t)
Variable Coeff Std Error T-Stat Signif
********************************************************************************
1. HS{1} 0.916663724 0.034820200 26.32563 0.00000000
2. ZHONGCHUANG{1} -0.050861318 0.020072394 -2.53389 0.01128029
3. DQS{1} 0.103041821 0.114586661 0.89925 0.36852060
4. NASDAQ{1} -0.071775150 0.086808978 -0.82682 0.40834072
5. Constant 0.035299647 0.023769996 1.48505 0.13753042
6. HS{1} 0.143677846 0.049393634 2.90883 0.00362780
7. ZHONGCHUANG{1} 0.902844633 0.024006845 37.60780 0.00000000
8. DQS{1} 0.167998201 0.151692101 1.10749 0.26808009
9. NASDAQ{1} -0.069374773 0.106574812 -0.65095 0.51507937
10. Constant 0.014903023 0.020673109 0.72089 0.47097764
11. HS{1} 0.075462663 0.030456182 2.47775 0.01322155
12. ZHONGCHUANG{1} 0.025640052 0.018338139 1.39818 0.16205848
13. DQS{1} 0.779885657 0.026037817 29.95204 0.00000000
14. NASDAQ{1} 0.012694923 0.022229497 0.57108 0.56794230
15. Constant 0.028457755 0.009579194 2.97079 0.00297037
16. HS{1} 0.033107850 0.037734913 0.87738 0.38028038
17. ZHONGCHUANG{1} 0.010651704 0.021583754 0.49351 0.62165537
18. DQS{1} 0.245451577 0.029652719 8.27754 0.00000000
19. NASDAQ{1} 0.664057377 0.020902315 31.76956 0.00000000
20. Constant 0.063928045 0.009240497 6.91825 0.00000000
21. C(1) 0.033929235 0.002813645 12.05882 0.00000000
22. C(2) 0.042532528 0.001965969 21.63438 0.00000000
23. C(3) 0.027237733 0.003385332 8.04581 0.00000000
24. C(4) 0.053947659 0.006271777 8.60166 0.00000000
25. A(1) 0.263180497 0.017945117 14.66586 0.00000000
26. A(2) 0.546483182 0.015219798 35.90607 0.00000000
27. A(3) 0.160277016 0.011925703 13.43963 0.00000000
28. A(4) 0.127118635 0.010040606 12.66045 0.00000000
29. B(1) -0.116877263 0.037109557 -3.14952 0.00163539
30. B(2) -0.092772507 0.002814485 -32.96251 0.00000000
31. B(3) 0.198282638 0.023344844 8.49364 0.00000000
32. B(4) 0.254036112 0.021604480 11.75849 0.00000000
33. DCC(1) 0.414838488 0.031632324 13.11439 0.00000000
34. DCC(2) 0.585916762 0.039655961 14.77500 0.00000000
35. Shape 3.374649868 0.054588594 61.81969 0.00000000
GARCH(P=1,Q=1,model=varbefore,MV=DCC,VARIANCES=VARMA,RVECTORS=RD,HMATRICES=HD,DIST=T)
Variable Coeff Std Error T-Stat Signif
********************************************************************************
1. HS{1} 0.969448836 0.009888338 98.03961 0.00000000
2. ZHONGCHUANG{1} -0.015713535 0.004835152 -3.24985 0.00115465
3. DQS{1} 0.261977563 0.028301441 9.25669 0.00000000
4. NASDAQ{1} -0.164005706 0.022575052 -7.26491 0.00000000
5. Constant 0.016106556 0.003082466 5.22522 0.00000017
6. HS{1} 0.010976430 0.007896087 1.39011 0.16449547
7. ZHONGCHUANG{1} 0.953861767 0.006467491 147.48560 0.00000000
8. DQS{1} 0.198539801 0.027487215 7.22299 0.00000000
9. NASDAQ{1} -0.134248389 0.022870931 -5.86983 0.00000000
10. Constant 0.005380339 0.004323977 1.24430 0.21338793
11. HS{1} -0.007685708 0.003620063 -2.12309 0.03374660
12. ZHONGCHUANG{1} 0.000859668 0.002092318 0.41087 0.68116895
13. DQS{1} 0.977396975 0.013727983 71.19742 0.00000000
14. NASDAQ{1} -0.012306044 0.008146622 -1.51057 0.13089801
15. Constant -0.000531159 0.001839640 -0.28873 0.77278810
16. HS{1} -0.008837234 0.005299063 -1.66770 0.09537577
17. ZHONGCHUANG{1} -0.006624368 0.002973692 -2.22766 0.02590333
18. DQS{1} 0.036760031 0.018047510 2.03685 0.04166530
19. NASDAQ{1} 0.940859981 0.013741410 68.46896 0.00000000
20. Constant 0.002819442 0.002464336 1.14410 0.25258294
21. C(1) 0.002023728 0.000387772 5.21886 0.00000018
22. C(2) 0.000490370 0.000580968 0.84406 0.39863725
23. C(3) 0.000174995 0.000036673 4.77176 0.00000183
24. C(4) 0.000572716 0.000054594 10.49045 0.00000000
25. A(1,1) 0.879976134 0.027011895 32.57736 0.00000000
26. A(1,2) -0.092146633 0.010587227 -8.70357 0.00000000
27. A(1,3) -0.599869034 0.049461275 -12.12805 0.00000000
28. A(1,4) 0.405351983 0.051788394 7.82708 0.00000000
29. A(2,1) 0.003110682 0.048266038 0.06445 0.94861298
30. A(2,2) 0.652876469 0.029441398 22.17546 0.00000000
31. A(2,3) 0.181695317 0.122576513 1.48230 0.13826016
32. A(2,4) -0.155396043 0.107517212 -1.44531 0.14836994
33. A(3,1) 0.051242791 0.011765514 4.35534 0.00001329
34. A(3,2) -0.101450856 0.006437525 -15.75929 0.00000000
35. A(3,3) 0.718375925 0.034475784 20.83712 0.00000000
36. A(3,4) 0.009496814 0.026006705 0.36517 0.71498606
37. A(4,1) 0.025849092 0.000396750 65.15203 0.00000000
38. A(4,2) -0.151410881 0.003847649 -39.35153 0.00000000
39. A(4,3) -0.298261623 0.030946201 -9.63807 0.00000000
40. A(4,4) 1.055354217 0.034726590 30.39038 0.00000000
41. B(1,1) 0.056798068 0.025894059 2.19348 0.02827290
42. B(1,2) 0.035761086 0.011545605 3.09738 0.00195242
43. B(1,3) -0.032945417 0.071138505 -0.46312 0.64328085
44. B(1,4) 0.029336038 0.065999419 0.44449 0.65668884
45. B(2,1) -0.167669047 0.046194706 -3.62962 0.00028384
46. B(2,2) 0.473868451 0.028828262 16.43763 0.00000000
47. B(2,3) -0.315883743 0.085008171 -3.71592 0.00020246
48. B(2,4) 0.259980110 0.068794449 3.77909 0.00015741
49. B(3,1) -0.039524382 0.012686353 -3.11550 0.00183631
50. B(3,2) 0.065315185 0.006796670 9.60988 0.00000000
51. B(3,3) 0.417864026 0.017054884 24.50114 0.00000000
52. B(3,4) 0.007201495 0.018420871 0.39094 0.69584001
53. B(4,1) -0.056560235 0.011102740 -5.09426 0.00000035
54. B(4,2) 0.084388663 0.006283543 13.43011 0.00000000
55. B(4,3) 0.226480712 0.027458378 8.24815 0.00000000
56. B(4,4) 0.169300071 0.027896380 6.06889 0.00000000
57. DCC(1) 0.870580476 0.001036298 840.08676 0.00000000
58. DCC(2) 0.127198609 0.001140170 111.56111 0.00000000
59. Shape 5.582767417 0.120330037 46.39546 0.00000000