Analysis of Tales of Suspense issues 39 to 99
Amazingly Secret Approach Using an Incredibly Novel Data Analysis Procedure for Comic Book Investing and Speculation.
Analysis of Tales of Suspense issues 39 to 99
Analysis of Tales of Suspense issues 39 to 99
Introduction and Material and Methods
In
order to isolate potential key issues to focus my investing efforts on, I used
a data analysis approach based on established values from two collecting
universes within in the entire run of the silver age Tales of Suspense
(TOS issues 39 to 99), I gathered value data from a variety of sources representing
both serious investors (Insiders – I)
and not serious investors (Outsiders-O).
This data is current as on 3/2015. I choose
to keep my methodology and data gathering proprietary at this time but I am
giving my readers a simplified representation of my data that I currently use
for my decisions.
Results – Tales of Suspense (TOS issues 39
to 99)
Table 1. Bias Scores (B SCORE) of All
Issues in the Run
Issue
|
B Score
|
Issue
|
B Score
|
|
#39
|
722.1
|
#71
|
-5.9
|
|
#40
|
-12.6
|
#72
|
-3.8
|
|
#41
|
15.0
|
#73
|
-6.0
|
|
#42
|
38.0
|
#74
|
-6.1
|
|
#43
|
13.2
|
#75
|
-2.7
|
|
#44
|
23.7
|
#76
|
-6.4
|
|
#45
|
24.4
|
#77
|
-6.9
|
|
#46
|
-37.0
|
#78
|
-4.4
|
|
#47
|
1.2
|
#79
|
-3.9
|
|
#48
|
-1.5
|
#80
|
-5.4
|
|
#49
|
12.5
|
#81
|
-5.5
|
|
#50
|
16.5
|
#82
|
-4.7
|
|
#51
|
15.7
|
#83
|
-6.1
|
|
#52
|
19.3
|
#84
|
-6.1
|
|
#53
|
3.7
|
#85
|
-6.7
|
|
#54
|
-1.9
|
#86
|
-4.3
|
|
#55
|
13.2
|
#87
|
-4.5
|
|
#56
|
1.6
|
#88
|
-6.3
|
|
#57
|
21.3
|
#89
|
-4.4
|
|
#58
|
13.6
|
#90
|
-5.6
|
|
#59
|
-2.4
|
#91
|
-5.5
|
|
#60
|
0.7
|
#92
|
-6.4
|
|
#61
|
-4.2
|
#93
|
-5.8
|
|
#62
|
-0.8
|
#94
|
-3.4
|
|
#63
|
-1.0
|
#95
|
-7.8
|
|
#64
|
-4.9
|
#96
|
-3.8
|
|
#65
|
-2.3
|
#97
|
-5.7
|
|
#66
|
3.5
|
#98
|
-6.2
|
|
#67
|
-3.1
|
#99
|
-4.9
|
|
#68
|
-4.7
|
|||
#69
|
1.0
|
|||
#70
|
-4.1
|
Using the data based on
that described in the introduction, I calculated the I/O bias (B Score) between the two groups and
adjusted the scores to account for the extreme issue of TOS 39. Very high
insider bias is denoted with dark purple (range 38 to 19) and high bias
is denoted using light purple (range16 to 13). Minus
numbers reflect a bias by the unsophisticated outsider group while positive
numbers reflect bias by the sophisticated insider group. I have denoted the
issues that have the insider bias with a dark grey fill-in.
The
data suggests a bias does exist and invites a deeper focus (see Tables 2 and 3).
I think these data show promise in this run and that surprisingly no extremes
exist in issue values biased to outsiders’ opinions. That finding may need further
thought.
I note the few
issues that show a slight bias (# 47, 53, 56, 60, 66, and 69) as denoted in yellow. I would put these on my watch list to expect change.
Note that issue 47 is last yellow suit
appearance, 53 is the second appearance of black widow, 60 is the second
appearance of the real Captain America in TOS, 66 has the Red Skull appearance
and cover, and 69 has the first appearance of Titanium Man.
Table 2.
I/O SLN numbers calculated for issues 39 to 99.
In
order to begin this deeper analysis I developed a measure called SLN. The SLN
looks at the slope of the values in both the I/O databases from 9.4 to 6 conditions.
Table 1 shows the SLN values between issues 39 to 99. Note issue 39 is off-scale but shows a bias to
the Insiders
Issue
|
I
SLN
|
O
SLN
|
Issue
|
I
SLN
|
O
SLN
|
|
#39
|
138.9
|
99.0
|
#71
|
0.2
|
0.4
|
|
#40
|
2.5
|
10.3
|
#72
|
0.6
|
0.4
|
|
#41
|
5.7
|
8.3
|
#73
|
0.2
|
0.4
|
|
#42
|
8.1
|
4.1
|
#74
|
0.2
|
0.4
|
|
#43
|
4.5
|
4.1
|
#75
|
0.6
|
0.6
|
|
#44
|
5.9
|
4.1
|
#76
|
0.2
|
0.4
|
|
#45
|
6.2
|
5.0
|
#77
|
0.2
|
0.4
|
|
#46
|
2.7
|
3.3
|
#78
|
0.4
|
0.4
|
|
#47
|
2.1
|
3.3
|
#79
|
0.6
|
0.6
|
|
#48
|
2.1
|
5.0
|
#80
|
0.4
|
0.5
|
|
#49
|
4.4
|
5.8
|
#81
|
0.3
|
0.4
|
|
#50
|
4.4
|
2.5
|
#82
|
0.4
|
0.4
|
|
#51
|
3.9
|
1.7
|
#83
|
0.2
|
0.4
|
|
#52
|
6.3
|
5.8
|
#84
|
0.2
|
0.4
|
|
#53
|
2.1
|
1.7
|
#85
|
0.1
|
0.4
|
|
#54
|
1.1
|
0.8
|
#86
|
0.5
|
0.4
|
|
#55
|
3.2
|
0.8
|
#87
|
0.4
|
0.4
|
|
#56
|
1.5
|
0.8
|
#88
|
0.2
|
0.4
|
|
#57
|
5.9
|
4.1
|
#89
|
0.5
|
0.4
|
|
#58
|
4.3
|
3.3
|
#90
|
0.3
|
0.4
|
|
#59
|
1.7
|
2.9
|
#91
|
0.3
|
0.4
|
|
#60
|
1.5
|
1.2
|
#92
|
0.2
|
0.4
|
|
#61
|
0.7
|
0.8
|
#93
|
0.2
|
0.4
|
|
#62
|
1.1
|
0.8
|
#94
|
0.6
|
0.4
|
|
#63
|
1.4
|
2.1
|
#95
|
0.4
|
0.4
|
|
#64
|
0.6
|
0.8
|
#96
|
0.5
|
0.4
|
|
#65
|
1.2
|
1.7
|
#97
|
0.3
|
0.6
|
|
#66
|
1.8
|
1.0
|
#98
|
0.3
|
0.4
|
|
#67
|
0.7
|
0.5
|
#99
|
0.4
|
0.5
|
|
#68
|
0.5
|
0.5
|
||||
#69
|
1.3
|
0.5
|
||||
#70
|
0.5
|
0.5
|
As I look across the data landscape, I have
to focus on issue 59, which is the first Iron Man appearance. Clearly it is the
star of the show in this run. I see that the SLN numbers are near but the
insiders are valuing it more that outsiders (138 to 99). Next I focus attention
onto the issues that insiders are valuing higher vs. the outside group; issues
42 to 45, 50 to 53, 55 to 58, 66, and 69. I see that from issues #70 to 99 that
none rate any serious focus. (I note that extreme high grades equal or above
9.4 are always going to be valued greatly by both groups just due to the
rarity). Green
denotes I to O bias while Red denotes the
opposite.
In conclusion based on this
data, I suggest the green issues are the
investment targets to focus on the highest grades possible while the red/white denoted issues are targets for much less if
any focus. The greys
are put on my watch list to monitor for any changes.
Table 3.
Adjusted Average Differences of I/O Data at Selected Grades
Given the I/O differences in the data
across grades, I focused on the average of those differences between the I and
O data. I adjusted these averages to normalize it and allow a sharper clarity
in the results. That data is presented in Table 3. $ represents I bias while x represents O
bias.
Issue
|
C9.4 ADF
|
C8 ADF
|
C6 ADF
|
Issue
|
C9.4 ADF
|
C8 ADF
|
C6 ADF
|
|
#39
|
$
|
$
|
$
|
#71
|
x
|
x
|
x
|
|
#40
|
x
|
$
|
$
|
#72
|
x
|
x
|
x
|
|
#41
|
$
|
x
|
x
|
#73
|
x
|
x
|
x
|
|
#42
|
$
|
$
|
$
|
#74
|
x
|
x
|
x
|
|
#43
|
$
|
$
|
$
|
#75
|
x
|
$
|
x
|
|
#44
|
$
|
$
|
x
|
#76
|
x
|
x
|
x
|
|
#45
|
$
|
x
|
x
|
#77
|
x
|
x
|
x
|
|
#46
|
$
|
$
|
$
|
#78
|
x
|
x
|
x
|
|
#47
|
x
|
x
|
x
|
#79
|
x
|
x
|
x
|
|
#48
|
x
|
x
|
x
|
#80
|
x
|
x
|
x
|
|
#49
|
$
|
x
|
$
|
#81
|
x
|
x
|
x
|
|
#50
|
$
|
$
|
$
|
#82
|
x
|
x
|
x
|
|
#51
|
$
|
x
|
x
|
#83
|
x
|
x
|
x
|
|
#52
|
$
|
$
|
$
|
#84
|
x
|
x
|
x
|
|
#53
|
$
|
x
|
$
|
#85
|
x
|
x
|
x
|
|
#54
|
x
|
x
|
x
|
#86
|
x
|
x
|
x
|
|
#55
|
$
|
x
|
x
|
#87
|
x
|
x
|
x
|
|
#56
|
$
|
x
|
$
|
#88
|
x
|
x
|
x
|
|
#57
|
$
|
$
|
$
|
#89
|
x
|
x
|
x
|
|
#58
|
$
|
$
|
x
|
#90
|
x
|
x
|
x
|
|
#59
|
x
|
$
|
x
|
#91
|
x
|
x
|
x
|
|
#60
|
x
|
x
|
x
|
#92
|
x
|
x
|
x
|
|
#61
|
x
|
x
|
$
|
#93
|
x
|
x
|
x
|
|
#62
|
x
|
x
|
x
|
#94
|
x
|
x
|
x
|
|
#63
|
x
|
x
|
x
|
#95
|
x
|
$
|
x
|
|
#64
|
x
|
x
|
x
|
#96
|
x
|
x
|
x
|
|
#65
|
x
|
x
|
$
|
#97
|
x
|
x
|
x
|
|
#66
|
$
|
x
|
x
|
#98
|
x
|
x
|
x
|
|
#67
|
x
|
x
|
x
|
#99
|
x
|
x
|
x
|
|
#68
|
x
|
x
|
x
|
|||||
#69
|
x
|
x
|
x
|
|||||
#70
|
x
|
x
|
x
|
Analysis of the Table 3 data revealed
that I/O data in Table 1 and 2 might not reflect the whole truth. It can be
seen that 7 issues are favored across the three grade levels by the I crowd (39,
42, 43, 46, 50, 52, 57). In contrast, 10 issues show only the I/O bias by the
insider investors mainly in the Grade of 9.4 (41, 44, 45, 49, 51, 53, 55, 56,
58, and 66) In some of these issues the other grades of 8 and 6 are favored by
the unsophisticated outsiders. I note and cannot explain issue 40. I
hypothesize that since 39 is out of bounds for most; outsiders are going to
issue 40 because of it being affordable relative to insides at the high grade.
“I got the second Iron Man at 9.4 yea me!”
Finally the in the other issues after #66, the outsiders bias all issues
in the entire run over the insiders’ opinions and buying habits.
Based on this data, I would conclude
one might focus on the 7 dark purple denoted issues in the lesser cheaper
grades while the lighter purple issues would those you should focus on only in
highest grades or not at all. Other issues are not recommended for a focus
effort at this time. Note this table may be of greater usage and certainly
suggests a different approach, as did the data in Table 2
Legend for Focusing
on Table 3’s Data
$ $ $ ----- I-bias is
strong across the grades High Focus
$ $ x ----- I-bias is
stronger in the higher grades Mid Focus
$ x $ ----- I-bias is only in
the high grade 9.4
$ x x ----- I-bias is
only in the high grade 9.4
x $ $ ----- Some I-bias but
not in the high grade
x x $ ----- Some I-bias but
not in the high grade Light/Low
Focus
x $ x ----- Some I-bias but
not in the high grade
x x x -----
O-bias across all grades No
Focus
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