Exploring Quality and Price Irregularities

by James Jou

121343_ca65b9475b03f0ae3481d3bd9072980ef3ba0d72-201x300 Exploring Quality and Price IrregularitiesOutside of the usual speculation avenues of TV/movie rumors, 1st appearances, #1s, cover arts, etc, here we will look directly at the market numbers. In a previous article, while analyzing the market data for Giant-Size Spider-Man books, we came upon the odd occurrence of Giant-Size Spider-Man #1’s CGC 9.8 holding an FMV 7 times higher than its nearest grades. Here we will explore further into quality and price.



Why is it interesting that for some books there is a large price gap between grades and others a small price gap? It’s a direct real-world example of the comic book market’s willingness to pay for perceived quality. The classic battle of buying cheap versus buying quality. But just how big of a difference can there possibly be?120027_0da7e7eb2d01cc2be3d094c235440a1403792ba1-196x300 Exploring Quality and Price Irregularities

Focusing on the top 200 most actively sold Silver Age books in the marketplace, we find a prevalence of roughly 10% of the books has a 9.8 FMV that is at least 5 times higher than the 9.6 FMV. If we filter even further using the 7x difference of the previously observed Giant-Size Spider-Man #1, we are left with only 6 books. 6 out of 200 that people are willing to pay a 7-fold price when the average tends to be 2-4x.

Each one is arguably key or unique in their own right: Fantastic Four #49, Avengers #4, Amazing Spider-Man #39, Fantastic Four #33, The Amazing Spider-Man Annual #4, X-Men #58.

At this point, one might bring up that the large price gap at the 9.8/9.6 is due entirely to the rarity of books at the 9.8 and 9.6 quality. Yes, that contributes. But even with that, it’s peculiar that only a small percentage of the top 200 have such large price differences. To make sure we thoroughly look into this, we extend the examination to a middling willingness-to-pay vs quality of 9.4 to 8.0 and 8.0 to 6.0.

Using Fantastic Four #49 as our base, which has: 9.4/8.0: 3.97, and 8.0/6.0: 2.79. We can filter for books with similar or higher ratios and come up with books from the top 200 silver such as X-Men #1, Amazing Spider-Man #50, Fantastic Four #52, Fantastic Four #50, Batman #181, Marvel Super-Heroes #13, Amazing Fantasy #15, Tales of Suspense #94, Action Comics #252, Fantastic Four #55, etc.

This filter yields a ~5-10% occurrence in the top 200 books. A very subjective grade/FMV ratio filter, but the point is that within the high FMV books, there exists a large difference in perception of quality between each one.

Again, you can easily say that of course, this is obvious. But what is unknown is whether or not we can quantify and capitalize on this information. Is there a book with a quality (grade) that has been inefficiently valued in the market? For this, one possible avenue is to identify the outliers. The top 100 Silver Age books get all the usual attention and will likely always be popular, so we will instead focus on the #101-#200 ranked ones.

With a focus at the CGC 9.6 grade, the books of particular interest that come up are: Fantastic Four #33, The Amazing Spider-Man Annual #4, and X-Men #58117692_3410fb6337f3a1796348d3b652e53f230ff67040-199x300 Exploring Quality and Price Irregularities

Fantastic Four #33

  • CGC 9.6: 1700
  • CGC 9.8: 18000

The Amazing Spider-Man Annual #4

  • CGC 9.6: 875
  • CGC 9.8: 9750

X-Men #58

  • CGC 9.6: 1200
  • CGC 9.8: 9000

At the moment, so far we’ve only filtered out candidate books at specific grades for further analysis. Whether or not this strategy has indeed found good investments will be verified and examined more in a subsequent article, and hopefully see just how much price gap irregularities weigh on potential speculation.



“Beware of geeks bearing formulas.” – Warren Buffett




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1 comment

Ivan R Roliz June 11, 2020 - 7:39 am

I have been wanting to figure this out for a long time. I thought about why does a large price gap exist between small a small difference in grade? I tired using regression analysis and weighed factors like print run to CGC census. I think I am using the wrong gools. If someone can figure this out it would be potential to find the new future keys that have the same profit margins as the big keys you mentioned in your article.


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