Multiple Linear Regression - Estimated Regression Equation

PS[t] = + 1.01286297246682 -0.111002079465273D[t] -0.276532324735665Tg[t] + e[t]

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STAT H0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	1.01286297246682	0.125069	8.0984	0	0
D	-0.111002079465273	0.022068	-5.03	1.1e-05	6e-06
Tg	-0.276532324735665	0.066448	-4.1617	0.000168	8.4e-05

Multiple Linear Regression - Regression Statistics
Multiple R	0.78228935349227
R-squared	0.611976632587354
Adjusted R-squared	0.592077998361065
F-TEST (value)	30.7547053545427
F-TEST (DF numerator)	2
F-TEST (DF denominator)	39
p-value	9.61011681344104e-09
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	0.186453483961759
Sum Squared Residuals	1.35583116557764

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	Interpolation Forecast	Residuals Prediction Error
1	0.301029996	0.230975834281787	0.0700541617182133
2	0.255272505	-0.204104238132274	0.459376743132274
3	-0.15490196	-0.0548010941143446	-0.100100865885655
4	0.591064607	0.474876167244179	0.116188439755821
5	0	-0.148272770206387	0.148272770206387
6	0.556302501	0.404285067995433	0.152017433004567
7	0.146128036	0.248766804119539	-0.102638768119539
8	0.176091259	0.0021796308153188	0.173911628184681
9	-0.15490196	-0.219293876124056	0.0643919161240558
10	0.322219295	0.452979993212333	-0.130760698212333
11	0	0.39067283896396	-0.39067283896396
12	0.612783857	0.34197791374706	0.27080594325294
13	0.079181246	0.215897990033101	-0.136716744033101
14	-0.301029996	-0.142294942193302	-0.158735053806698
15	0.531478917	0.457880715376618	0.0735982016233817
16	0.176091259	0.212918852002346	-0.036827593002346
17	0.531478917	0.279670759498687	0.251808157501313
18	-0.096910013	0.0621067047950157	-0.159016717795016
19	-0.096910013	-0.24076189819937	0.14385188519937
20	0.146128036	0.200392349694723	-0.0542643136947228
21	0.301029996	0.432040768139269	-0.131010772139268
22	0.278753601	0.230852092999951	0.0479015080000494
23	0.113943352	0.326240028022372	-0.212296676022372
24	0.301029996	0.271384959509392	0.0296450364906081
25	0.748188027	0.603432394234039	0.144755632765961
26	0.491361694	0.326900069498374	0.164461624501626
27	0.255272505	0.197385038560811	0.0578874664391892
28	-0.045757491	-0.0479365707225534	0.0021790797225534
29	0.255272505	0.450599912943657	-0.195327407943657
30	0.278753601	-0.000994909667231259	0.279748510667231
31	-0.045757491	0.0454428588769199	-0.0912003498769199
32	0.414973348	0.314220358614303	0.100752989385697
33	0.380211242	0.427330499031055	-0.0471192570310555
34	0.079181246	0.178382895322352	-0.0992016493223519
35	-0.045757491	0.140404313631148	-0.186161804631148
36	-0.301029996	0.0294022341658747	-0.330432230165875
37	-0.22184875	-0.144704985558873	-0.0771437644411274
38	0.361727836	0.299142514642149	0.0625853213578509
39	-0.301029996	0.043547559990627	-0.344577555990627
40	0.414973348	0.331052524780883	0.0839208232191166
41	-0.22184875	-0.0733140455866349	-0.148534704413365
42	0.819543936	0.584919442761749	0.234624493238251

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
6	0.56055032911684	0.87889934176632	0.43944967088316
7	0.773019163324786	0.453961673350428	0.226980836675214
8	0.678180453588924	0.643639092822152	0.321819546411076
9	0.598619417506705	0.802761164986591	0.401380582493295
10	0.55161708690293	0.896765826194139	0.448382913097069
11	0.811376018300675	0.37724796339865	0.188623981699325
12	0.897465293041335	0.205069413917329	0.102534706958665
13	0.884260351661738	0.231479296676525	0.115739648338262
14	0.880438874214097	0.239122251571805	0.119561125785903
15	0.849750081687015	0.300499836625969	0.150249918312985
16	0.798104857086246	0.403790285827508	0.201895142913754
17	0.841906486946654	0.316187026106693	0.158093513053346
18	0.828366391540143	0.343267216919714	0.171633608459857
19	0.834714493726769	0.330571012546462	0.165285506273231
20	0.772035302077229	0.455929395845542	0.227964697922771
21	0.741370529228301	0.517258941543397	0.258629470771699
22	0.670610926146319	0.658778147707363	0.329389073853681
23	0.71925330478267	0.561493390434659	0.280746695217329
24	0.635085668312883	0.729828663374233	0.364914331687117
25	0.588974992423562	0.822050015152876	0.411025007576438
26	0.600071840929075	0.79985631814185	0.399928159070925
27	0.552541283054197	0.894917433891605	0.447458716945803
28	0.483989600645406	0.967979201290811	0.516010399354594
29	0.653128248176499	0.693743503647002	0.346871751823501
30	0.96936650447633	0.0612669910473412	0.0306334955236706
31	0.976552203528233	0.0468955929435339	0.023447796471767
32	0.969403119374236	0.0611937612515285	0.0305968806257642
33	0.9441648237251	0.111670352549802	0.055835176274901
34	0.925693654972276	0.148612690055448	0.074306345027724
35	0.943421133188992	0.113157733622015	0.0565788668110077
36	0.887599495934966	0.224801008130068	0.112400504065034

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	0	0	OK
5% type I error level	1	0.032258064516129	OK
10% type I error level	3	0.0967741935483871	OK