Analysis of X-men Part 2 Issues 41 to 143
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 run of the
silver age issues 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 4/2015. 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 – Issues X-men 41 to 143
Table 1. Bias Scores (B SCORE) of All
Issues in the Run
Issue
|
B Score
|
Issue
|
B Score
|
|
#41
|
118.4
|
#93
|
6.8
|
|
#42
|
91.4
|
#94
|
616
|
|
#42
|
72.4
|
#95
|
79.8
|
|
#42
|
71.4
|
#96
|
2
|
|
#45
|
-93.6
|
#97
|
-31
|
|
#46
|
49.4
|
#98
|
13
|
|
#46
|
84.4
|
#99
|
-35
|
|
#46
|
5.4
|
#100
|
-141
|
|
#49
|
122
|
#101
|
-71.4
|
|
#50
|
-31
|
#102
|
-38.2
|
|
#51
|
99
|
#103
|
-9.2
|
|
#52
|
9.6
|
#104
|
-60.2
|
|
#53
|
-19.6
|
#105
|
-33.2
|
|
#54
|
104.2
|
#106
|
-73.2
|
|
#55
|
-1.8
|
#107
|
-51.2
|
|
#56
|
31.8
|
#108
|
-50.4
|
|
#57
|
47.2
|
#109
|
-16.2
|
|
#58
|
134
|
#110
|
-132
|
|
#59
|
145.8
|
#111
|
-55
|
|
#60
|
63.8
|
#112
|
-13
|
|
#61
|
23
|
#113
|
1
|
|
#62
|
53.8
|
#114
|
-24
|
|
#63
|
37.8
|
#115
|
-34
|
|
#64
|
28.8
|
#116
|
-39
|
|
#65
|
17.8
|
#117
|
-44
|
|
#66
|
55.8
|
#118
|
-31
|
|
#67
|
17.8
|
#119
|
-34
|
|
#68
|
101.8
|
#120
|
-57.6
|
|
#69
|
-47.2
|
#121
|
-15
|
|
#70
|
118.8
|
#122
|
-52.6
|
|
#71
|
13.8
|
#123
|
-51.6
|
|
#72
|
116.8
|
#124
|
-12.6
|
|
#73
|
307.8
|
#125
|
-19.6
|
|
#74
|
23.8
|
#126
|
-17.6
|
|
#75
|
9.8
|
#127
|
-44.6
|
|
#76
|
507.8
|
#128
|
-46.6
|
|
#77
|
51.8
|
#129
|
-52.6
|
|
#78
|
-47.2
|
#130
|
-46
|
|
#79
|
346.8
|
#131
|
-42.6
|
|
#80
|
42.8
|
#132
|
-50.6
|
|
#81
|
57.8
|
#133
|
-35
|
|
#82
|
171.8
|
#134
|
-32.6
|
|
#83
|
60.8
|
#135
|
-59.6
|
|
#84
|
-18.2
|
#136
|
-66.6
|
|
#85
|
29.8
|
#137
|
-52
|
|
#86
|
-67.2
|
#138
|
-28.2
|
|
#87
|
106.8
|
#139
|
-50.6
|
|
#88
|
-21.2
|
#140
|
-53.6
|
|
#89
|
26.8
|
#141
|
-45.4
|
|
#90
|
34.8
|
#142
|
-63.4
|
|
#91
|
-7.2
|
#143
|
-72
|
|
#92
|
-18.2
|
Using the data based on
that described in the introduction, I calculated the I/O bias between the two
groups and adjusted the scores to account for the extreme issues. I note the
very high insider bias with dark purple and high bias using light purple. Note
the low plus/ low minus numbers reflect a sight bias by the unsophisticated
outsider group followed by the more extreme biases. I use the Average followed
by Std. Dev. as a guide into
these cutoffs. (Note the term guide). These numbers only refer to this data set
unless I combine multiple runs. So you can not draw conclusions between
independent runs and numbers throughout this blog. The data suggests a bias
does exist within the run and invites a deeper focus (see Tables 2 and 3). I
think these data show promise in this run. However, the biggest message is
after 94/95 forget about it. Let the outsider swim in those waters. This
pattern is very dramatic in Bias differences as compared to ASM for example.
Even the FF runs had more promise late in the run. See the previous posts.
Table 2.
I/O SLN numbers calculated for issues
Issue
|
I SLN
|
O SLN
|
Issue
|
I SLN
|
O SLN
|
|
#41
|
222.7
|
114.1
|
#93
|
86.7
|
87.5
|
|
#42
|
206.0
|
114.1
|
#94
|
1090.0
|
820.0
|
|
#43
|
183.3
|
114.1
|
#95
|
194.7
|
196.8
|
|
#44
|
172.0
|
114.1
|
#96
|
120.0
|
164.0
|
|
#45
|
105.3
|
114.1
|
#97
|
114.0
|
136.7
|
|
#46
|
177.3
|
114.1
|
#98
|
133.3
|
136.7
|
|
#47
|
195.3
|
114.1
|
#99
|
93.3
|
136.7
|
|
#48
|
135.3
|
114.1
|
#100
|
107.3
|
164.0
|
|
#49
|
270.0
|
168.0
|
#101
|
176.0
|
174.9
|
|
#50
|
149.3
|
125.3
|
#102
|
80.0
|
87.5
|
|
#51
|
213.3
|
125.3
|
#103
|
76.0
|
87.5
|
|
#52
|
158.7
|
123.2
|
#104
|
62.0
|
87.5
|
|
#53
|
146.7
|
156.8
|
#105
|
60.0
|
87.5
|
|
#54
|
198.7
|
134.4
|
#106
|
40.0
|
87.5
|
|
#55
|
137.3
|
134.4
|
#107
|
54.7
|
87.5
|
|
#56
|
171.3
|
145.6
|
#108
|
70.7
|
92.9
|
|
#57
|
176.7
|
134.4
|
#109
|
78.0
|
87.5
|
|
#58
|
280.0
|
196.0
|
#110
|
-6.0
|
54.7
|
|
#59
|
228.0
|
145.6
|
#111
|
40.0
|
54.7
|
|
#60
|
196.7
|
145.6
|
#112
|
57.3
|
54.7
|
|
#61
|
156.7
|
140.0
|
#113
|
65.3
|
54.7
|
|
#62
|
193.3
|
145.6
|
#114
|
63.3
|
54.7
|
|
#63
|
162.7
|
145.6
|
#115
|
50.0
|
54.7
|
|
#64
|
143.3
|
142.1
|
#116
|
46.7
|
54.7
|
|
#65
|
115.3
|
142.1
|
#117
|
40.0
|
54.7
|
|
#66
|
190.0
|
142.1
|
#118
|
45.3
|
54.7
|
|
#67
|
117.3
|
87.5
|
#119
|
40.0
|
54.7
|
|
#68
|
153.3
|
87.5
|
#120
|
65.3
|
98.4
|
|
#69
|
80.7
|
87.5
|
#121
|
86.7
|
82.0
|
|
#70
|
171.3
|
87.5
|
#122
|
30.0
|
43.7
|
|
#71
|
94.7
|
87.5
|
#123
|
31.3
|
43.7
|
|
#72
|
166.7
|
87.5
|
#124
|
53.3
|
43.7
|
|
#73
|
290.7
|
87.5
|
#125
|
48.7
|
43.7
|
|
#74
|
105.3
|
87.5
|
#126
|
50.0
|
43.7
|
|
#75
|
103.3
|
87.5
|
#127
|
35.3
|
43.7
|
|
#76
|
444.0
|
87.5
|
#128
|
30.7
|
43.7
|
|
#77
|
120.0
|
87.5
|
#129
|
88.0
|
98.4
|
|
#78
|
83.3
|
87.5
|
#130
|
48.7
|
54.7
|
|
#79
|
340.0
|
87.5
|
#131
|
33.3
|
43.7
|
|
#80
|
114.0
|
87.5
|
#132
|
26.7
|
43.7
|
|
#81
|
126.0
|
87.5
|
#133
|
49.3
|
54.7
|
|
#82
|
190.0
|
87.5
|
#134
|
36.7
|
43.7
|
|
#83
|
122.7
|
87.5
|
#135
|
36.7
|
43.7
|
|
#84
|
70.0
|
87.5
|
#136
|
23.3
|
43.7
|
|
#85
|
110.7
|
87.5
|
#137
|
41.3
|
54.7
|
|
#86
|
60.7
|
87.5
|
#138
|
33.3
|
32.8
|
|
#87
|
153.3
|
87.5
|
#139
|
34.7
|
43.7
|
|
#88
|
82.0
|
87.5
|
#140
|
29.3
|
43.7
|
|
#89
|
110.0
|
87.5
|
#141
|
63.3
|
65.6
|
|
#90
|
116.7
|
87.5
|
#142
|
42.0
|
65.6
|
|
#91
|
77.3
|
87.5
|
#143
|
18.0
|
27.3
|
|
#92
|
70.0
|
87.5
|
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 of ASM between issues 81 to 149.
I
have added some more color indicators. Deep Green and Light Green are denoting
the issues with definite Insider Bias and are worthy of further digging for
investment choices. On the other hand, I denoted the issues with Outsider Bias
with Deep Red and Light Rose. I would not focus on these except as noted by the
Table 3 data. (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.
As
I look across the data landscape, I see a lot of negative issues to not focus
your investments. The big message from the B Score graph continues here. A
complete drop off in Buy signals after Issue 94).
In
conclusion based on this data, I suggest sell late issues and buy the earlier
ones. I suggest the green (dark and light) issues are the investment targets to
focus on the highest grades possible while the red/rose/white denoted issues
are targets for much less if any focus except if Table 3 data suggests
otherwise.
Table 3. Adjusted Average Differences of
I/O Data at Selected Grades
Issue
|
C9.4 ADF
|
C8 ADF
|
C6 ADF
|
Issue
|
C9.4 ADF
|
C8 ADF
|
C6 ADF
|
|
#41
|
$$
|
?
|
?
|
#93
|
X
|
X
|
?
|
|
#42
|
$$
|
?
|
?
|
#94
|
$$
|
XX
|
X
|
|
#43
|
$
|
?
|
?
|
#95
|
X
|
XX
|
X
|
|
#44
|
$
|
X
|
?
|
#96
|
XX
|
XX
|
X
|
|
#45
|
X
|
$
|
$
|
#97
|
XX
|
X
|
X
|
|
#46
|
$
|
?
|
?
|
#98
|
X
|
X
|
?
|
|
#47
|
$
|
?
|
?
|
#99
|
XX
|
X
|
X
|
|
#48
|
?
|
?
|
?
|
#100
|
XX
|
$
|
?
|
|
#49
|
$$
|
?
|
?
|
#101
|
?
|
$
|
$
|
|
#50
|
$
|
$
|
$
|
#102
|
X
|
?
|
?
|
|
#51
|
$$
|
?
|
?
|
#103
|
X
|
X
|
X
|
|
#52
|
$
|
?
|
?
|
#104
|
X
|
?
|
?
|
|
#53
|
X
|
X
|
X
|
#105
|
XX
|
X
|
?
|
|
#54
|
$
|
X
|
?
|
#106
|
XX
|
X
|
?
|
|
#55
|
?
|
X
|
?
|
#107
|
XX
|
X
|
?
|
|
#56
|
?
|
X
|
X
|
#108
|
X
|
?
|
?
|
|
#57
|
$
|
X
|
?
|
#109
|
X
|
X
|
?
|
|
#58
|
$$
|
X
|
$
|
#110
|
XX
|
?
|
?
|
|
#59
|
$
|
X
|
?
|
#111
|
X
|
?
|
?
|
|
#60
|
$
|
X
|
$
|
#112
|
X
|
?
|
?
|
|
#61
|
?
|
X
|
?
|
#113
|
X
|
X
|
?
|
|
#62
|
$
|
?
|
?
|
#114
|
X
|
?
|
?
|
|
#63
|
?
|
X
|
?
|
#115
|
X
|
?
|
?
|
|
#64
|
X
|
X
|
X
|
#116
|
X
|
?
|
?
|
|
#65
|
XX
|
XX
|
X
|
#117
|
X
|
?
|
?
|
|
#66
|
$
|
X
|
?
|
#118
|
X
|
?
|
?
|
|
#67
|
$
|
?
|
?
|
#119
|
X
|
X
|
?
|
|
#68
|
$
|
X
|
?
|
#120
|
X
|
X
|
?
|
|
#69
|
X
|
?
|
?
|
#121
|
X
|
?
|
?
|
|
#70
|
$
|
X
|
?
|
#122
|
X
|
?
|
?
|
|
#71
|
X
|
X
|
?
|
#123
|
X
|
?
|
?
|
|
#72
|
$
|
X
|
?
|
#124
|
?
|
?
|
?
|
|
#73
|
$$
|
X
|
?
|
#125
|
X
|
?
|
?
|
|
#74
|
X
|
X
|
?
|
#126
|
X
|
?
|
?
|
|
#75
|
X
|
X
|
?
|
#127
|
X
|
?
|
?
|
|
#76
|
$$
|
?
|
?
|
#128
|
X
|
?
|
?
|
|
#77
|
?
|
X
|
?
|
#129
|
X
|
?
|
?
|
|
#78
|
X
|
?
|
?
|
#130
|
X
|
?
|
?
|
|
#79
|
$$
|
?
|
?
|
#131
|
X
|
?
|
?
|
|
#80
|
?
|
X
|
?
|
#132
|
X
|
?
|
?
|
|
#81
|
?
|
X
|
?
|
#133
|
X
|
?
|
?
|
|
#82
|
$$
|
X
|
X
|
#134
|
X
|
?
|
?
|
|
#83
|
?
|
X
|
?
|
#135
|
X
|
$
|
?
|
|
#84
|
X
|
X
|
?
|
#136
|
X
|
?
|
?
|
|
#85
|
?
|
X
|
?
|
#137
|
X
|
?
|
?
|
|
#86
|
X
|
?
|
?
|
#138
|
X
|
?
|
?
|
|
#87
|
$
|
X
|
?
|
#139
|
X
|
?
|
?
|
|
#88
|
X
|
X
|
?
|
#140
|
X
|
?
|
?
|
|
#89
|
?
|
X
|
X
|
#141
|
X
|
?
|
?
|
|
#90
|
?
|
X
|
X
|
#142
|
X
|
?
|
?
|
|
#91
|
X
|
X
|
?
|
#143
|
X
|
$
|
?
|
|
#92
|
X
|
X
|
?
|
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.
Analysis of the Table 3 data revealed
that I/O data in Tables 1 and 2 may not reflect the whole truth. It can be seen
that 3 issues are favored across the three grade levels by the I crowd (Xmen
41, 42 and 50). In contrast, 23 issues show only the I/O bias by the insider
investors mainly in the Grade of 9.4. I
also have denoted via gray color on the issues that certainly need to be
watched. Finally the other issues are all pretty much biased by the outsiders
over the insiders’ opinions and buying habits.
Based on this data, I would conclude
one might focus on the 3 green denoted issues in the lesser cheaper grades
while the dark green issues would those you should focus on only in highest
grades or not at all. The grey ones are on the watch list. Other issues are not
recommended for a focus effort at this time. Note the after 94 and forget it
message remains with an interesting selection of Issue 101.
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