Regression output issue

[MUCPA]

I'm running a regression on chemical prices. The Y (dependent) variable is my price, the X (independent) variables are 6 month rolling average prices for related chemicals.

Dep Var (Y)	Chem A	Chem B	Chem C	Chem D	Chem E	Chem F	Chem G	Chem H
1.55	1.38	2.96	1567.08	1238.33	854.75	3.09	1133.33	0.47
1.62	1.72	3.05	1810.00	1428.17	1404.42	3.10	1088.54	0.57
1.54	1.72	3.15	1810.00	1448.17	1431.71	3.19	1120.42	0.59
1.69	1.83	3.50	1985.83	1574.33	1538.75	3.45	1312.04	0.71
1.62	1.61	2.79	1944.17	1452.17	1465.64	2.78	1058.13	0.68
1.70	1.67	3.21	2180.00	1469.00	1408.00	3.26	1363.33	0.61
1.75	1.92	3.79	2132.50	1562.00	1490.00	4.04	1481.25	0.62

<tbody>
</tbody>

When I run this regression, the output is this:

Regression Statistics
Multiple R	1
R Square	1
Adjusted R Square	65535
Standard Error
Observations	7
ANOVA
	df	SS	MS	F	Significance F
Regression	8	0.037085714	0.004635714	#NUM!	#NUM!
Residual			65535
Total	8	0.037085714
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	-1.28363		65535	#NUM!	-1.283633148	-1.283633148	-1.283633148	-1.283633148
Butane monthly avg	1.555782		65535	#NUM!	1.555781703	1.555781703	1.555781703	1.555781703
Toulene monthly avg			65535	#NUM!
Acryl monthly avg	0.001087		65535	#NUM!	0.001086923	0.001086923	0.001086923	0.001086923
LDPE monthly avg	0.002284		65535	#NUM!	0.002283682	0.002283682	0.002283682	0.002283682
LLDPE monthly avg	-0.00219		65535	#NUM!	-0.002191373	-0.002191373	-0.002191373	-0.002191373
Mixed xylenes monthly avg	-0.26168		65535	#NUM!	-0.261680247	-0.261680247	-0.261680247	-0.261680247
Para xylene monthly avg	-0.00103		65535	#NUM!	-0.001028792	-0.001028792	-0.001028792	-0.001028792
Propylene chem monthly avg			65535	#NUM!

<tbody>
</tbody>

Regression Statistics
Multiple R	1
R Square	1
Adjusted R Square	65535
Standard Error
Observations	7
ANOVA
	df	SS	MS	F	Significance F
Regression	8	0.037085714	0.004635714	#NUM!	#NUM!
Residual			65535
Total	8	0.037085714
	Coefficients	Standard Error	t Stat	P -value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	-1.28363		65535	#NUM!	-1.283633148	-1.283633148	-1.283633148	-1.283633148
Butane monthly avg	1.555782		65535	#NUM!	1.555781703	1.555781703	1.555781703	1.555781703
Toulene monthly avg			65535	#NUM!
Acryl monthly avg	0.001087		65535	#NUM!	0.001086923	0.001086923	0.001086923	0.001086923
LDPE monthly avg	0.002284		65535	#NUM!	0.002283682	0.002283682	0.002283682	0.002283682
LLDPE monthly avg	-0.00219		65535	#NUM!	-0.002191373	-0.002191373	-0.002191373	-0.002191373
Mixed xylenes monthly avg	-0.26168		65535	#NUM!	-0.261680247	-0.261680247	-0.261680247	-0.261680247
Para xylene monthly avg	-0.00103		65535	#NUM!	-0.001028792	-0.001028792	-0.001028792	-0.001028792
Propylene chem monthly avg			65535	#NUM!

<tbody>
</tbody>

Please ignore the second regression output, it's not letting me delete the unintentional double-paste.

I can't tell if my confusion is because I'm not fully understanding the concepts statistically, or if there is some procedural reason that excel is giving me these wild values (R square of 1, Adjusted R square of 65535, no F value what so ever, etc...).

Any help would be greatly appreciated. Why does this regression output look so crazy?