1、时间序列分析作业时间序列分析作业 1、数据收集通过长江证券金长江网上交易软件收集中信证券(600030)股价数据（2010-7-12011-5-9，共200组），保存文件，命名为“股价数据”。2、工作表建立打开eviews，点击file下拉菜单中的new项选择workfile项，弹出窗口如下：（1）、在datespecification中选择integer date。（2）、在start和end中分别输入“1”“200”（3）、在wf项后面的框中输入工作表名称hr，点击ok。 窗口如下：3、数据导入在hr工作文件的菜单选项中选择pro，在弹出的下拉菜单中选择import，然后再下拉二级菜单中选
2、择read text-lotus-excell，找到数据，双击弹出如下对话框：默认date order，选择右边upper-left data cell下面的空格填写，输入excel中第一个有效数据单元格地址B6，在names for series or number if named in file 中输入序列名称，不妨设为s，点击ok，导入数据。4、平稳性检验点击s序列，选择菜单view/correlogram，弹出correlogram specification对话框，如下图，在对话框中默认level，lags to include 改为20（200/10），可得下图：序列的自相关系数
3、没有很快的趋近0，说明原序列是非平稳的序列。5、对原序列做对数差分处理A、在主窗口输入smpl 2 200，对样本数据进行选取，B、在主命令窗口输入series is=log(s)-log(s(-1)可以得到新的序列is对is序列做同上的平稳性检验可以得到如下图：可以看出，自相关系数和偏相关系数很快的接近于0，故该序列是平稳的。根据上图，初步将模型的阶数拟定为p=5，q=5。6、不同的阶数（p，q）对应的统计表对is序列建立ARMA模型，其各个不同的p、q下的估计结果整理成表格的形式，不要只是截图放在上面；表格中须包含估计系数、标准差、t统计量值及p值、调整后的可决系数及AIC、SC等统计表如
4、下表：（p，q）估计系数标准差t统计量p值调整可决系数AICSC(1,1)AR(1)-0.8250 0.1163 -7.0929 0.0000 0.0178 -4.4604 -4.4271 MA(1)0.9116 0.0868 10.5018 0.0000 (1,2)AR(1)-0.8401 0.1363 -6.1636 0.0000 0.0133 -4.4508 -4.4009 MA(1)0.9427 0.1545 6.1022 0.0000 MA(2)0.0236 0.0862 0.2733 0.7849 (1,3)AR(1)-0.7647 0.1686 -4.5365 0.0000 0.
5、0163 -4.4489 -4.3825 MA(1)0.8689 0.1790 4.8541 0.0000 MA(2)0.0874 0.0962 0.9092 0.3644 MA(3)0.0991 0.0807 1.2290 0.2206 (1,4)AR(1)-0.7578 0.2163 -3.5030 0.0006 0.0112 -4.4388 -4.3558 MA(1)0.8620 0.2276 3.7876 0.0002 MA(2)0.0872 0.0986 0.8852 0.3772 MA(3)0.0973 0.0949 1.0258 0.3063 MA(4)-0.0050 0.092
6、3 -0.0537 0.9573 (1,5)AR(1)0.4881 0.2606 1.8732 0.0626 0.0286 -4.4516 -4.3520 MA(1)-0.4252 0.2582 -1.6467 0.1013 MA(2)-0.0266 0.0784 -0.3394 0.7347 MA(3)0.1316 0.0770 1.7087 0.0891 MA(4)-0.0843 0.0838 -1.0055 0.3159 MA(5)0.2021 0.0745 2.7129 0.0073 (2,1)AR(1)0.8116 0.3243 2.5024 0.0132 0.0076 -4.441
7、6 -4.3916 AR(2)0.0054 0.0945 0.0573 0.9544 MA(1)-0.7388 0.3157 -2.3400 0.0203 (2,2)AR(1)-0.0295 0.2814 -0.1049 0.9166 0.0190 -4.4481 -4.3815 AR(2)0.7062 0.2100 3.3630 0.0009 MA(1)0.1616 0.2984 0.5415 0.5888 MA(2)-0.7042 0.2524 -2.7899 0.0058 (2,3)AR(1)-0.0115 0.2478 -0.0464 0.9630 0.0184 -4.4426 -4.
8、3592 AR(2)0.6425 0.2391 2.6866 0.0079 MA(1)0.1025 0.2541 0.4034 0.6871 MA(2)-0.6424 0.2643 -2.4303 0.0160 MA(3)0.0793 0.0910 0.8721 0.3843 (2,4)AR(1)-0.0380 0.3481 -0.1090 0.9133 0.0135 -4.4327 -4.3327 AR(2)0.6459 0.2338 2.7630 0.0063 MA(1)0.1259 0.3548 0.3547 0.7232 MA(2)-0.6548 0.2541 -2.5773 0.01
9、07 MA(3)0.0836 0.0901 0.9286 0.3543 MA(4)0.0250 0.1089 0.2298 0.8185 (2,5)AR(1)0.0463 0.2967 0.1559 0.8763 0.0200 -4.4344 -4.3177 AR(2)0.3905 0.2898 1.3474 0.1795 MA(1)0.0266 0.2960 0.0897 0.9286 MA(2)-0.4050 0.2886 -1.4031 0.1622 MA(3)0.0892 0.0808 1.1032 0.2713 MA(4)0.0174 0.0949 0.1834 0.8547 MA(
10、5)0.1443 0.0931 1.5500 0.1228 (3,1)AR(1)0.7126 0.3547 2.0088 0.0460 0.0072 -4.4325 -4.3656 AR(2)-0.0333 0.0923 -0.3611 0.7184 AR(3)0.0729 0.0838 0.8702 0.3853 MA(1)-0.6388 0.3519 -1.8155 0.0710 (3,2)AR(1)-0.1231 0.3087 -0.3987 0.6906 0.0169 -4.4374 -4.3537 AR(2)0.6392 0.2538 2.5189 0.0126 AR(3)0.076
11、7 0.0902 0.8502 0.3963 MA(1)0.2163 0.3048 0.7096 0.4788 MA(2)-0.6242 0.2970 -2.1019 0.0369 (3,3)AR(1)0.0464 0.1979 0.2345 0.8149 0.0686 -4.4865 -4.3861 AR(2)-0.3631 0.1473 -2.4659 0.0146 AR(3)0.7630 0.1881 4.0557 0.0001 MA(1)0.0368 0.2322 0.1584 0.8743 MA(2)0.4802 0.1706 2.8141 0.0054 MA(3)-0.6952 0
12、.2313 -3.0060 0.0030 (3,4)AR(1)0.0616 0.2559 0.2406 0.8101 0.0647 -4.4774 -4.3603 AR(2)-0.3505 0.1931 -1.8154 0.0711 AR(3)0.7783 0.2452 3.1735 0.0018 MA(1)0.0460 0.2680 0.1717 0.8639 MA(2)0.4516 0.2523 1.7897 0.0751 MA(3)-0.7120 0.3032 -2.3480 0.0199 MA(4)-0.0359 0.0939 -0.3821 0.7028 (3,5)AR(1)0.53
13、55 0.3220 1.6632 0.0979 0.0275 -4.4335 -4.2997 AR(2)0.2973 0.2927 1.0156 0.3111 AR(3)-0.3590 0.2751 -1.3048 0.1936 MA(1)-0.4640 0.3209 -1.4461 0.1498 MA(2)-0.3342 0.2878 -1.1610 0.2471 MA(3)0.4477 0.2721 1.6453 0.1016 MA(4)-0.0483 0.1042 -0.4636 0.6435 MA(5)0.1675 0.0972 1.7235 0.0864 (4,1)AR(1)-0.7
14、974 0.1359 -5.8691 0.0000 0.0104 -4.4264 -4.3424 AR(2)0.0955 0.0928 1.0290 0.3048 AR(3)0.1108 0.0923 1.1998 0.2317 AR(4)0.0193 0.0815 0.2364 0.8134 MA(1)0.8997 0.1138 7.9095 0.0000 (4,2)AR(1)-0.1307 0.4714 -0.2771 0.7820 0.0119 -4.4228 -4.3221 AR(2)0.6336 0.3490 1.8158 0.0710 AR(3)0.0779 0.1004 0.77
15、60 0.4387 AR(4)0.0005 0.1144 0.0048 0.9962 MA(1)0.2232 0.4662 0.4787 0.6327 MA(2)-0.6175 0.3849 -1.6045 0.1103 (4,3)AR(1)0.1247 0.4091 0.3047 0.7609 0.0643 -4.4725 -4.3550 AR(2)-0.3675 0.2106 -1.7455 0.0825 AR(3)0.7907 0.3195 2.4751 0.0142 AR(4)-0.0454 0.1084 -0.4186 0.6760 MA(1)-0.0103 0.4080 -0.02
16、51 0.9800 MA(2)0.4636 0.2817 1.6454 0.1016 MA(3)-0.7304 0.4010 -1.8217 0.0701 (4,4)AR(1)0.8564 0.0390 21.9537 0.0000 0.0597 -4.4626 -4.3283 AR(2)0.1159 0.0556 2.0834 0.0386 AR(3)0.7237 0.0550 13.1636 0.0000 AR(4)-0.8554 0.0379 -22.5608 0.0000 MA(1)-0.7907 0.0187 -42.2067 0.0000 MA(2)-0.1694 0.0303 -
17、5.5921 0.0000 MA(3)-0.7895 0.0222 -35.6174 0.0000 MA(4)0.9607 0.0137 70.1511 0.0000 (4,5)AR(1)0.9432 0.5337 1.7671 0.0788 0.0439 -4.4411 -4.2900 AR(2)0.3895 0.5392 0.7224 0.4710 AR(3)-0.7435 0.3108 -2.3922 0.0177 AR(4)0.0519 0.3900 0.1330 0.8943 MA(1)-0.8887 0.5364 -1.6567 0.0993 MA(2)-0.4636 0.5164
18、 -0.8978 0.3705 MA(3)0.8633 0.3441 2.5089 0.0130 MA(4)-0.0969 0.4762 -0.2036 0.8389 MA(5)0.0726 0.0926 0.7842 0.4339 (5,1)AR(1)0.4242 0.3788 1.1197 0.2643 0.0178 -4.4247 -4.3236 AR(2)-0.0210 0.0836 -0.2512 0.8020 AR(3)0.0760 0.0784 0.9698 0.3334 AR(4)-0.0527 0.0839 -0.6278 0.5309 AR(5)0.1621 0.0751
19、2.1594 0.0321 MA(1)-0.3477 0.3829 -0.9082 0.3649 (5,2)AR(1)0.7318 0.1289 5.6790 0.0000 0.0448 -4.4476 -4.3297 AR(2)-0.8080 0.1416 -5.7047 0.0000 AR(3)0.1357 0.1064 1.2757 0.2036 AR(4)-0.0955 0.0927 -1.0301 0.3043 AR(5)0.2133 0.0756 2.8219 0.0053 MA(1)-0.6603 0.1161 -5.6889 0.0000 MA(2)0.8108 0.1156
20、7.0137 0.0000 (5,3)AR(1)0.4310 0.2077 2.0757 0.0393 0.0367 -4.4343 -4.2995 AR(2)0.3119 0.2006 1.5548 0.1217 AR(3)-0.5747 0.1925 -2.9857 0.0032 AR(4)0.0114 0.0898 0.1274 0.8988 AR(5)0.1619 0.0843 1.9192 0.0565 MA(1)-0.3535 0.2009 -1.7595 0.0801 MA(2)-0.3458 0.1898 -1.8216 0.0701 MA(3)0.6493 0.1775 3.
21、6587 0.0003 (5,4)AR(1)0.9424 0.5983 1.5751 0.1169 0.0453 -4.4383 -4.2867 AR(2)0.4628 0.5750 0.8050 0.4219 AR(3)-0.8087 0.3199 -2.5276 0.0123 AR(4)0.0245 0.4461 0.0550 0.9562 AR(5)0.0482 0.0768 0.6274 0.5312 MA(1)-0.8888 0.6022 -1.4760 0.1416 MA(2)-0.5454 0.5417 -1.0067 0.3154 MA(3)0.9331 0.3637 2.56
22、57 0.0111 MA(4)-0.0522 0.5335 -0.0978 0.9222 (5,5)AR(1)-0.2207 0.2478 -0.8905 0.3743 0.2329 -4.6521 -4.4837 AR(2)0.5246 0.1657 3.1654 0.0018 最小AR(3)0.5804 0.0338 17.1752 0.0000 AR(4)-0.3397 0.1408 -2.4117 0.0169 AR(5)-0.6602 0.2057 -3.2088 0.0016 MA(1)0.3562 0.2300 1.5485 0.1232 MA(2)-0.4450 0.1299
23、-3.4264 0.0008 MA(3)-0.7621 0.0645 -11.8208 0.0000 MA(4)0.4290 0.1711 2.5067 0.0131 MA(5)0.9769 0.2488 3.9271 0.0001 7、IAR 、IMA判别从上表可以看出，对应的p=5，q=5时，AIC的值最小。且从回归输出可以看出此时对应的IAR为虚根，其模为0.9391，IMA为虚根，其模为0.9931，满足题意。故IS = 0 + AR(1)=-0.220663319179,AR(2)=0.524648611464,AR(3)=0.580391980871,AR(4)=-0.339657902652,AR(5)=-0.660162055075,MA(1)=0.356239746585,MA(2)=-0.444974944734,MA(3)=-0.762099158189,MA(4)=0.42899673081,MA(5)=0.9768799420918、对模型的检验操作方
