市场预测实验报告.docx

实验一回归方程的拟合实验二邹检验及虚拟变量实验三线性回归中的问题实验四随机时间序列的特征观察实验五单位根检验实验六ARMA模型运用实验四随机时间序列的特征观察实验属性综合型实验时间2022.5.26实验目的1 .准确掌握随机过程的平稳性和非平稳性的特征和判断方法。2 .熟练掌握运用自相关分析判断随机过程的平稳性。3 .学会利用自相关分析图判断序列的季节性。4 .熟练掌握运用相关分析图判断齐次非平稳序列平稳化需要的差分次数。实验内容实验步骤1 .根据数据频率和时间范围，创建EVIEWS工作文件2 .录入数据，并对序列进性初步分析。绘制财政存款余额数据原始序列和对数序列的折线图，分析序列的基本趋势。3 .利用相关分析图观察对数序列的随机特征。分别观察对数序列和一次差分后的对数序列的相关分析图，判断序列平稳性和季节性。4 .对财政存款余额对数序列进性季节调整，再观察相关分析图。分别观察季节调整后的对数序列和一次差分后序列的相关分析图，判断序列平稳性和平稳化需要的差分次数。实验结果分析1.NSAVEDate05y26718Time09:50iSample-199OMO12007M12Includedobservations,216AUtoCorrQIatiOr)PartialCorrelationACPACQ-StatProbII10985098521268OOOOIII209720021420450.000III309580004623460000II(I40944-005082122OOOOIII50929-0020101370000III60.913-0.0221200.70.000III70.898-0.0171382.20.000III0882-0004155840000III90866-0033172900000III100849-003118937OOOOIII1108320013205280.000III120817004922067OOOOIII130801-002423555OOOOIII140785-0009249900000III1507690011263750000III160753001727709OOOOIII170737-0004289940000III180721-0009302290000III190.705-0.0143141.50.000III200.688-0.0113255.40.000III210672-0017336450000III220656001234688OOOOIII230639-0005356860000III240624000366390.000III250609002537553OOOOIII260594000138427OOOOIII270580-000639264OOOOIII280565-001340063OOOOIII290551-000540827OOOOIII300.536-00124155.40.000III310522-000742247OQOOIII320.508-0.0064290.60.000III330.493-0.0124353.30.000III340479-001444126OOOOIII350465-0008446890.000III360.45100244522.20.000AutocoelatonPartialCOrreIatlOnACPACQ-StatProbIIIIIIIIIIIIIIIIII;IIIIII:1:IIIIIII-IIIIIIIIIIIIIIIII:IIIIFIIIIIII'IIIIIIIIIIIIIrIIIIIIIIIIIIIIII'1-0.262-026214.914OOOO20.0750.00716.1420.0003 00200.04416270.0014 0030004916.43100025 0036005716.72400056 0.022004316.8320.0107 0020003116.92300188 0007001216.93300319 0.0380.036172550.04510 0066008318.234005111 -0272-026535.134OOOO120.3720.26366.9820.000130031022667.204OOOO140.062011868.1010.00015-0010000368.126000016-00074)04568.1360000170024-002468.273OOOO180036001568.588OOOO190039003968.947OOOO200.013004668.9860000210.0200.01769.0850.000220.057QO3869.8750.000230023021370.0060.000240059008470.865OOOO250048-000271.4380.000260077900572.896OOOO2701-003672.897OOOo28-0017003972.969OOOO290002000772.9710.000300011000473.004OOOO310.0270.00273.1890.000320.011-0.02473.2220.00033-0001-COW73.222OOOO340013006873.2660.000350045-COOS73.794OOOO360049000474.428OOOOAutocorrelationPartialConeiationACPACQ-StatProb12345678g1011121314151617181920212223242526272829303132333435360.95509551889500000912-0012361.8500000864-0067517940.0000.817-0.025658.050.0000.767-0.051782.210.0000717-0028891340.000067000019870300000625OOo6107090.0000583-0000114430.0000540-00471207400000499000112617000004900339131440.0000470-01491363000000.452-0.0341408.10.0000440009514511OOOO043200211492900000426-041533700000419-00071573400000410-0.0211611600000399-00301647900000387-004216823OOOO03750028171470000036001001744800000.3610.0841775.30.000036200011806000000361002718368000003S8-00171867300000353-00471897000000347-00111925900000.340-0002195390.0000.332-00351980600000.322-00232005900000.311-0.022202960.0000.3000.0292051.80.0000.2880.082207250.0000.277-0.050209170000AutocorrelationPailiaIConeIationACPACOStatProb1I,l,1-0.025-0025012460724IIi200440044053020767'',3001800200595408971.40.0440.0431.00560.909II50.0110.0111.02980.960IIi>6-0026-0030117810978II117-0036-0040144970934IIIII8-0018-0020151900992IIIl900320034173SO0995IIdI10-0038-0031204930996mI白'11-0.433-04374273500IIiI120004-002642739OoOoIIIJI13-001900264282100'IqIU-0082-008244304000011Ii15-0054-0035449450000IIII16-0017-0007450060000II170012-0009450390000II»180.0340.01345.2960.000III1900330035455420001IIII2000060047455So0001II中210006-004545557OoOlIIcd«220037-0206458670.002II)8I23-0033-0053461160003II中24*0029-0031463100004IIl1250038-004546645Ooo5IIIII2600390007469940007III2700380038473410009IIII280007-0001473530013II»290.0000007473530.017II13000100049473750023II>1<310.0020.04247.3760.030IIIII320015-0004474280039IId>33-0017-0103475020049IIU1340.003-0.04947.5040.062II中35-0009-00584752400771MI)I3600290010477280091指导教师审阅（1）实验态度：不认真（），较认真（），认真（）（2）实验目的：不明确（）,较明确（）,明确（）（3）实验内容：不完整（），较完整（），完整（）（4）实验步骤：混乱（）,较清晰（）,清晰（）（5）实验结果：错误（）,基本正确（）,正确（）（6）实验结果分析：无（）,不充分（）,较充分（）,充分（）（7）其它补充：总评成绩：评阅教师（签字）：实验五单位根检验实验属性综合型实验时间2022.5.26实验目的1 .准确掌握单位根检验方程的形式和检验原理。2 .学会利用单位根检验方法对样本序列进行平稳性检验。实验内容实验步骤1 .根据数据频率和时间范围，创建EVlEWS工作文件2 .录入数据，并对序列进行初步分析。分别绘制上证综指和深证综指序列的折线图以及组形式的折线图，分析序列的基本趋势，以及两者的关系。运用ADF检验对上证综指和深证综指序列进行单位根检验。分别做原序列和差分序列的单位根检验，并判断单整的阶数。根据序列的折线图选择检验方程程式，根据AlC准则选择ADF检验时的最大滞后阶数Po1、折线图B股指数2、单位根检验a)上证指数NullHypothesis:SZhasaunitrootExogenous:Constant1.ag1.ength:0(Automatic-basedonSIC,maxlag=0)t-StatisticProb.*AugmentedDiCkeyFullerteststatistic08218430.8054Testcriticalvalues:1%level-3.5460995%level-2.91173010%level-2.593551*MacKinnon(1996)one-sidedp-values.AugmentedDickey-FullerTestEquationDependentVariable:D(SZ)Method:1.eastSquaresDate:05/26/18Time:10:35Sample(adjusted):2022M022022M12Includedobservations:59afteradjustmentsVariableCoefficientStd. Errort-StatisticProb.SZ(-D-0.0357180.043461-0.8218430.4146C104.7672115.30550.9086060.3674R-squared0.011711Meandependentvar12.68627AdjustedR-squared-0.005628S.D.dependentvar208.6358S.E.ofregression209.2220Akaikeinfocriterion13.55798Sumsquaredresid2495110.Schwarzcriterion13.628401.oglikelihood-397.9604Hannan-Quinncriter.13.58547F-Statistic0.675425Durbin-Watsonstat1.130185Prob(F-Statistic)0.414591b)B股指数NullHypothesis:BZhasaunitrootExogenous:Constant1.ag1.ength:0(Automatic-basedonSIC,maxlag=0)t-StatisticProb.*AugmentedDickey-Fullerteststatistic-09279370.7725Testcriticalvalues:1%level-3.5460995%level-2.91173010%level-2.593551wMacKinnon(1996)one-sidedp-values.AugmentedDickey-FullerTestEquationDependentVariable:D(BZ)Method:1.eastSquaresDate:05/26/18Time:10:39Sample(adjusted):2022M022022M12Includedobservations:59afteradjustmentsVariableCoefficientStd.Errort-StatisticProb.BZ(-1)0.0606000.065306-0.9279370.3574C18.4440518.050931.0217790.3112R-squared0.014882Meandependentvar2.033220AdjustedR-squared-0.002401S.D.dependentvar27.73204S.E.ofregression27.76532Akaikeinfocriterion9.518763Sumsquaredresid43942.03Schwarzcriterion9.5891881.oglikelihood-278.8035Hannan-Quinncriter.9.546254F-statistic0.861066Durbin-Watsonstat1.179314Prob(F-Statistic)0.357353B股指数上证指数NullHypothesis:BhasaunitrootExogenous:Constant1.ag1.ength:2(Automatic-basedonSIC,ma×lag=10)t-StatisticProb.*AugmentedDickey-Fullerteststatistic-1.0006750.7474Testcriticalvalues:1%level-3.5503965%level-2.91354910%level-2.594521wMacKinnon(1996)one-sidedp-values.AugmentedDickey-FullerTestEquationDependentVariable:D(B)Method:1.eastSquaresDate:05/26/18Time:10:55Sample(adjusted):2022M042022M12Includedobservations:57afteradjustmentsVariableCoefficientStd.Errort-StatisticProb.B(-1)-0.0664070.066362-1.0006750.3215D(B(-1)0.5471970.1288374.2472190.0001D(B(-2)-0.3514250.138779-2.5322640.0143C19.4883218.096301.0769230.2864R-squared0.287792Meandependentvar1.911579AdjustedR-squared0.247478S.D.dependentvar28.20860S.E.ofregression24.47040Akaikeinfocriterion9.300397Sumsquaredresid31736.42Schwarzcriterion9.4437691.oglikelihood-261.0613Hannan-Quinnenter.9.356116F-Statistic7.138824Durbin-Watsonstat2.001913Prob(F-Statistic)0.000409B1Jeveldifference:NullHypothesis:D(B)hasaunitrootExogenous:Constant1.ag1.ength:1(Automatic-basedonSIC,maxlag=10)t-StatisticProb.*AugmentedDickeyFullerteststatistic61140320.0000Testcriticalvalues:1%level-3.5503965%level-2.91354910%level-2.594521wMacKinnon(1996)one-sidedp-values.AugmentedDickey-FullerTestEquationDependentVariable:D(B,2)Method:1.eastSquaresDate:05/26/18Time:10:59Sample(adjusted):2022M042022M12Includedobservations:57afteradjustmentsVariableCoefficientStd.Errort-StatisticProb.D(B(-1)-0.8806680.144041-6.1140320.0000D(B(-1),2)0.4060460.1275963.1822790.0024C1.6732813.2447600.5156870.6082R-squared0.409900Meandependentvar0.751579AdjustedR-squared0.388044S.D.dependentvar31.28141S.E.ofregression24.47070Akaikeinfocriterion9.284026Sumsquaredresid32336.03Schwarzcriterion9.3915551.oglikelihood-261.5947Hannan-Quinncriter.9.325816F-Statistic18.75493Durbin-Watsonstat2.057590Prob(F-Statistic)0.000001D(B)NullHypothesis:ShasaunitrootExogenous:Constant1.ag1.ength:1(Automatic-basedonSIC,maxlag=10)t-StatisticProb.*AugmentedDickeyFullerteststatistic17199330.4161Testcriticalvalues:1%level-3.5482085%level-2.91263110%level-2.594027*MacKinno(1996)one-sidedp-values.AugmentedDickey-FullerTestEquationDependentVariable:D(三)Method:1.eastSquaresDate:05/26/18Time:10:56Sample(adjusted):2022M032022M12Includedobservations:58afteradjustmentsVariableCoefficientStd.Errort-StatisticProb.S(-1)-0.0691900.040228-1.7199330.0911D(S(-1)0.4636520.1219213.8028870.0004C183.8161106.21891.7305410.0891R-squared0.218032Meandependentvar10.93328AdjustedR-squared0.189597S.D.dependentvar210.0192S.E.ofregression189.0643Akaikeinfocriterion13.37239Sumsquaredresid1965993.Schwarzcriterion13.478961.oglikelihood-384.7993Hannan-Quinnenter.13.41390F-Statistic7.667681Durbin-Watsonstat1.828385Prob(F-Statistic)0.0011551leveldifferenceNullHypothesis:D(三)hasaunitrootExogenous:Constant1.ag1.ength:0(Automatic-basedonSIC,maxlag=10)t-StatisticProb?AugmentedDickey-Fullerteststatistic-47918180.0002Testcriticalvalues:1%level-3.5482085%level-2.91263110%level-2.594027*MacKinnon(1996)one-sidedp-values.AugmentedDickey-FullerTestEquationDependentVariable:D(S,2)Method:1.eastSquaresDate:05/26/18Time:10:58Sample(adjusted):2022M032022M12Includedobservations:58afteradjustmentsVariableCoefficientStd.Errort-StatisticProb.D(S(-1)-0.5808260.121212-4.7918180.0000C6.20223025.292710.2451900.8072R-squared0.290794Meandependentvar-0.355000AdjustedR-squared0.278129S.D.dependentvar226.3827S.E.ofregression192.3415Akaikeinfocriterion13.39030Sumsquaredresid2071733.Schwarzcriterion13.461351.oglikelihood-386.3186Hannan-Quinnenter.13.41797F-Statistic22.96152Durbin-Watsonstat1.800422Prob(F-Statistic)0.000013D(三)NullHypothesis:USD_URDhasaunitrootExogenous:Constant1.ag1.ength:0(Automatic-basedonSIC,maxlag=10)t-StatisticProb.*AugmentedDickey-Fullerteststatistic-1.2251770.6569Testcriticalvalues:1%level5%level10%level-3.562669-2.918778-2.597285wMacKinnon(1996)one-sidedp-values.AugmentedDickey-FullerTestEquationDependentVariable:D(USD_URD)Method:1.eastSquaresDate:05/26/18Time:12:01Sample(adjusted):253Includedobservations:52afteradjustmentsVariableCoefficientStd.Errort-StatisticProb.USD_URD(-1)-0.0610770.049851-1.2251770.2262C0.0437760.0357121.2258230.2260R-squared0.029146Meandependentvar4.77E-05AdjustedR-squared0.009729S.D.dependentvar0.008680S.E.ofregression0.008638Akaikeinfocriterion-6.627630Sumsquaredresid0.003731Schwarzcriterion-6.5525821.oglikelihood174.3184Hannan-Quinnenter.-6.598858F-Statistic1.501058Durbin-Watsonstat1.794929Prob(F-Statistic)0.226249NullHypothesis:D(USD_URD)hasaunitrootExogenous:Constant1.ag1.ength:0(Automatic-basedonSIC,ma×lag=10)t-StatisticProb.*AugmentedDiCkeyFullerteststatistic66383730.0000Testcriticalvalues:1%level5%level10%level-3.565430-2.919952-2.597905*MacKinnon(1996)one-sidedp-values.AugmentedDickey-FullerTestEquationDependentVariable:D(USD_URD,2)Method:1.eastSquaresDate:05/26/18Time:12:01Sample(adjusted):353Includedobservations:51afteradjustmentsVariableCoefficientStd.Errort-StatisticProb.D(SD-URD(-1)-0.9380210.141303-6.6383730.0000C0.0002130.0012250.1742720.8624R-squared0.473503Meandependentvar0.000109AdjustedR-squared0.462758S.D.dependentvar0.011933S.E.ofregression0.008747Akaikeinfocriterion-6.601842Sumsquaredresid0.003749Schwarzcriterion-6.5260841.oglikelihood170.3470Hannan-Quinnenter.-6.572892F-statistic44.06800Durbin-Watsonstat1.996560Prob(F-Statistic)0.000000NullHypothesis:D(USD_URD)hasaunitrootExogenous:Constant1.ag1.ength:0(Automatic-basedonSIC,maxlag=10)t-StatisticProb.*AugmentedDiCkeyFullerteststatistic66383730.0000Testcriticalvalues:1%level-3.5654305%level-2.91