Multiple Linear Regression - Estimated Regression Equation
Y[t] = + 405212.376212214 + 14.2876090146007DJIA[t] + 0.433366643601294Y1[t] + 0.117304164406053Y2[t] + 0.00146315681682760Y3[t] + 0.198193232954481Y4[t] -20549.0296296705M1[t] -58844.700821326M2[t] + 122216.654744061M3[t] -135295.969565926M4[t] -196839.08413439M5[t] -314012.44835748M6[t] -562394.662160664M7[t] -520562.784357975M8[t] -489669.430133837M9[t] -377128.669217277M10[t] -98765.5693057837M11[t] + 737.570519139868t + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)405212.37621221474469.2183995.44133e-062e-06
DJIA14.28760901460073.4824764.10270.0002080.000104
Y10.4333666436012940.1532492.82790.0074380.003719
Y20.1173041644060530.1684550.69640.4904450.245223
Y30.001463156816827600.1666950.00880.9930430.496521
Y40.1981932329544810.1483771.33570.1895780.094789
M1-20549.029629670541758.628709-0.49210.6254860.312743
M2-58844.70082132661514.799407-0.95660.3448190.172409
M3122216.65474406153218.6065552.29650.0272520.013626
M4-135295.96956592646548.744748-2.90650.0060670.003033
M5-196839.0841343963011.720563-3.12380.0034090.001705
M6-314012.4483574867733.758776-4.6364.1e-052.1e-05
M7-562394.66216066466408.528594-8.468700
M8-520562.78435797585788.088171-6.06800
M9-489669.43013383786000.973134-5.69381e-061e-06
M10-377128.66921727772659.905333-5.19037e-064e-06
M11-98765.569305783744491.573327-2.21990.0324690.016235
t737.570519139868341.7196372.15840.0372780.018639


Multiple Linear Regression - Regression Statistics
Multiple R0.996597096381513
R-squared0.993205772516062
Adjusted R-squared0.9901662496943
F-TEST (value)326.763716135021
F-TEST (DF numerator)17
F-TEST (DF denominator)38
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation26131.9690148321
Sum Squared Residuals25949432574.5016


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
114697981467376.270351852421.72964815017
214987211493800.750472434920.24952756512
317617691744957.2995805116811.7004194935
416532141635366.9960511417847.0039488613
515991041579670.1220800019433.8779200041
614211791431330.31392723-10151.3139272284
711639951157433.490175916561.509824087
810377351044819.99435049-7084.99435048725
91015407982686.14650664932720.853493351
1010392101037674.284368731535.71563126705
1112580491274970.42379117-16921.423791174
1214694451450730.3619584218714.6380415762
1315523461540970.3675890211375.6324109812
1415491441568915.75262806-19771.7526280553
1517858951803240.02427383-17345.0242738306
1616623351693500.70155881-31165.7015588062
1716294401627602.549908071837.45009193418
1814674301487867.60805326-20437.6080532646
1912022091214913.58318302-12704.5831830183
2010769821102450.219886-25468.2198860006
2110393671044208.95726232-4841.95726232361
2210634491088954.82497912-25505.8249791178
2313351351322555.9344454312579.0655545659
2414916021527873.09070757-36271.090707575
2515919721608387.94815593-16415.9481559265
2616412481634722.224726366525.7752736366
2718988491900915.43440801-2066.43440801189
2817985801794796.318025053783.68197495404
2917624441748405.1193634414038.8806365614
3016220441615181.505769646862.49423035942
3113689551345384.7189336823570.281066323
3212629731240351.4767969822621.5232030184
3311956501180218.4421345115431.5578654944
3412695301218206.4490351951323.5509648063
3514792791471061.376782258217.623217747
3616078191656987.37632816-49168.3763281587
3717124661701652.8015746310813.1984253682
3817217661721066.03950806699.960491935596
3919498431961329.90679539-11486.9067953871
4018213261832480.64676173-11154.6467617347
4117578021753588.69687924213.30312079985
4215903671574927.1600008115439.8399991883
4312606471285199.19503061-24552.1950306141
4411492351138921.7829490310313.2170509651
4510163671059677.45409652-43310.4540965218
4610278851055238.44161696-27353.4416169555
4712621591266034.26498114-3875.26498113887
4815208541454129.1710058466724.8289941574
4915441441552338.61232857-8194.61232857302
5015647091557083.232665087625.76733491793
5118217761807689.3349422614086.6650577361
5217413651720675.3376032720689.6623967256
5316233861662909.5117693-39523.5117692996
5414986581490371.412249058286.58775094537
5512418221234697.012676787124.98732322246
5611360291136410.52601750-381.526017495626


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
210.02369866833640310.04739733667280610.976301331663597
220.00592336355210120.01184672710420240.994076636447899
230.02105088969112840.04210177938225690.978949110308872
240.01307428844275360.02614857688550720.986925711557246
250.02192855487278140.04385710974556270.978071445127219
260.05658863318446310.1131772663689260.943411366815537
270.06968117032552660.1393623406510530.930318829674473
280.05336170537477380.1067234107495480.946638294625226
290.02631167834196650.0526233566839330.973688321658034
300.03571124447714930.07142248895429860.96428875552285
310.02403529884357420.04807059768714840.975964701156426
320.1122908925290110.2245817850580220.887709107470989
330.2361669168852920.4723338337705840.763833083114708
340.2966194224051080.5932388448102160.703380577594892
350.4987930838012260.9975861676024520.501206916198774


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level60.4NOK
10% type I error level80.533333333333333NOK