Methodology has created a suite of its own frameworks for establishing the fundamentals of a crypto project. In deriving the proper models and frameworks, universal foundational laws were applied (in no specific order):

— A projects 3 fundamental scores are evaluated and established against itself. Projects grades by no means are dependant on one another; if two very technologically similar projects score very differently from one another no slack is given to the lower scorer.

— A project’s final grades are rated against themselves and the standard of the greater crypto ecosystem.

— Every grade is subjected to and influenced by its own Industry, Purpose, and Archetype. 

— Privacy centric projects are likely to lack sensitive public information, henceforth their models are weighted differently.

— The Community & Value Proposition scores directly impact the outcome of a projects final score, whereas the Governance merely acts as an amplifier to the grade.

— Low grades in one of 3 fundamentals do not necessitate a low final score, however, a low final score necessitates low fundamental scores.

The frameworks are applied in 4 generalized segments:

     Segment 1 – A.I.M. (Asset Identification Matrix)

AIM is a framework used to deduce the Archetype of a crypto asset.

The A.I.M. framework is used as a guiding map to explore an asset’s intrinsic qualities and characteristics.

     Segment 2 – Archetype

 Not all Crypto-assets are made equally; an crypto asset can fall into 4 generalized classifications:

               – Currency                              – Security
               – Utility                                   – Reward

Given the still young and abstract nature of crypto, some assets can fall into multiple frameworks at the same time; Most commonly, A crypto is both a Utility & a Currency. Whenever a layover happens, the dominant identity is selected.

     Segment 3 – Scoring / Grading 

When establishing where on the scale between 0 – 100 a crypto-assets fundamental aspects place it, aggregates as much possible publicly accessible information as possible.  

Whenever establishing an assets final score, abstract concepts such as information obfuscation (as in the case with Privacy assets) are accounted for and included in the grade.

     Segment 4 – Risk Class

“Risk class” is a parameter used to define a project’s likelihood of impacting its participants financially.

There are 5 risk classifications: (A/B/C/D/F) each with a variant of +/-, While traditionally high risk usually mean high reward, in Crypfo’s framework High-risk does not always mean high reward.

Name Price24H (%)
Bitcoin (BTC)
Ethereum (ETH)
Litecoin (LTC)
Tezos (XTZ)
Monero (XMR)
Dash (DASH)

BTC: bc1qcskmel9llhrdqj3arxyqnennx4ashvfutlreyy
LTC: ltc1qa0fj4lcu5365rep50aza5fqqvx8ef0afemh6s5
ETH: 0x071D72dbc48ad2Fe35daE256eCF0834C5dde688c
DASH: XgXHqVyJiQNdVVszH9cnqCP4uWcP8tVxdK
BNB: bnb1mau4j8kry0jgw45ufy69hvhd0k04llet8fk2p6

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