12 Apr 2023

Methodology - The K33 Vinter Quality Index

The KVQ index comprises an equally weighted mix of the most promising tokens amongst the top 30 crypto assets. Tokens with a low long term survival-probability are excluded, contributing to a substantial reduction in downside risk in the index.
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A top 30 token must pass the Quality Filter for inclusion in the index. The purpose of the Quality Filter is to evaluate the quality of crypto assets from an investor's standpoint. A high-quality asset is defined as an asset with a small probability of permanent financial loss, while a low-quality asset possesses a significant probability of permanent financial loss. The quality filter consists of the following four steps. 1. Categorize: Each asset is assigned to a category, which allows for relative comparison.2. Exclude: Assets with faulty tokenomics, missing information, or presenting a lack of transparency are taken out.3. Evaluate: Five pillars enable the evaluation of an asset's quality for each category. 4. Rank: The Quality Filter selects the highest-ranked assets with scores above the cutoff Quality Score.The quality filter must include subjective analysisThe selection assessments should not be considered a universal truth, and others could provide compelling adverse arguments to our selections. Contrary to traditional finance, all the "bank" 's data are there for all to see in crypto. However, in most cases, you won't know, in the strictest sense, whose data or what you are looking at. By looking at the blockchain data itself, it's impossible to evaluate what's "real" volume or "fake" volume, whether 1000 addresses are really just one guy or a thousand, etc. To make sense of the blockchain data, you must therefore make inferences from outside knowledge in combination with what the blockchain tells you. To assess whether a token should be included in the "K33 Vinter Quality Index," we use a combination of standardized metrics and our specialist knowledge.A good stock portfolio will not, by definition, include good companies but rather good investments, i.e., companies with a low price compared to the fair price. Crypto markets are still immature, and at the current time, there are no well-established pricing models like the discounted cash flow model in traditional valuation of stocks. We believe many tokens' prices will eventually go close to zero. At the moment, the K33 Vinter Quality Index is mainly about excluding the tokens with a low probability of keeping value long-term. As our work on- and understanding of token prices expand, the index will be updated accordingly.The Quality Filter1. CategoriesCategories regroup and enable the comparison of assets having similar purposes. Each asset in the top 30 by market capitalization belongs to one of these categories:
  • Smart Contract
  • Payment
  • DeFi
  • Inter-Blockchain Communication
  • Centralized Exchange
  • Money Infrastructure
  • Specialized Utility
  • Community
  • Gimmick
2. Pre-exclusionIn the second step, we exclude assets with faulty tokenomics since they have a large probability of permanent financial loss. Besides removing assets with clear red flags, we also exclude assets with missing information or lack of transparency since we cannot compare them with other assets.3 and 4. Pillars and scoring modelEach crypto asset that passed Step 2 can be evaluated through five pillars. Those pillars are adjusted for each category to conduct the appropriate evaluation, as some categories are not comparable.Pillar 1: Persistent Network EffectsA crypto asset's protocol code can easily be copied. Even though the technical setup is easily replicated, it is yet to be seen protocol copies overtaking the incumbent. Thus it becomes clear that it is not mainly about the technicalities or incentive mechanisms but mostly about network effects and if there exists some inertia that will likely uphold over time.The pillar Persistent Network Effects assesses the strength of the current network effects. A high score indicates that the token is unlikely to be made irrelevant with the emergence of new, similar tokens and that continued usage of the token is likely. On the contrary, a low score on persistent network effects entails that the token is more likely to be made irrelevant, either by competing tokens or the outlook for the use case being weak.Pillar 2: UseThe pillar Use assesses the volume of meaningful economic use of the asset. Meaningful economic use of an asset refers to payments for transactions or access utility where the value changes hands, and the payee would be willing to pay an equivalent amount in outside currency. A high Use score entails the asset being used extensively for meaningful economic activity, while a low score indicates that the asset is little used for meaningful economic activity.Pillar 3: Regulatory RiskWhen evaluating the price potential of different crypto assets, it is essential to consider regulatory risks. Regulatory risk is the potential for government regulation changes to impact a crypto asset's value and adoption significantly.Crypto assets with a high regulatory risk will get a low score as they are more likely to become subject to regulations that can significantly decrease demand and value. Conversely, crypto assets with a low regulatory risk will receive a high score on this pillar. Pillar 4: Ecosystem size and livenessA vibrant community of developers, users, and businesses that are actively working to build and use a crypto asset can be a determining factor for success.The pillar Ecosystem size and liveness measure the 'vibrancy' of the development and dedicated user community surrounding the asset. Where data is available, assess the economic strength of this community's demand. A high score indicates that many developers actively work in the asset's ecosystem and a large community of dedicated users. A low score suggests that few developers work actively in the ecosystem and that the amount of dedicated users is low. Pillar 5: Inflation schedule and ownership concentrationInflation and ownership concentration should be viewed in combination as they pose similar risk dynamics in terms of token pricing. Most crypto assets have an issuance schedule with diminishing inflation. The model of diminishing inflation is based on the simple principle that a scarce supply is positive for the value of a token. The inflation of a token is evaluated on the percentage of supply left to be issued. A high score on inflation says that a low percentage of the supply is left to be issued, whereas a low score tells that a large portion of the supply is yet to be issued. Ownership concentration measures the wealth distribution of the asset. An asset will score poorly on this pillar with a high ownership concentration. Large token owners then control supply and likely sell into increased demand or dump on the market at once. A good score on ownership concentration indicates that asset ownership is well distributed. Scoring modelEach pillar is scored from 0 to 5, where 5 is the best score. If an asset scores 0 on a pillar, it is automatically excluded and, therefore, cannot receive a Quality Score. The Quality Score is given as a weighted average of the five pillars using the following distribution of weights.Pillar 1 = 2/6Pillar 2 = 1/6Pillar 3 = 1/6Pillar 4 = 1/6Pillar 5 = 1/6Pillar 1 - Persistent Network Effects is given twice the weight of the other pillars, as the pillar best encompasses the essential attributes for a crypto asset to survive long-term. If an asset has missing data on a pillar compared to the other assets in the category, it will be handled as follows. If the lack of data poses a significant risk, then the grade for this pillar will be set to 0. If other relevant data sources can be used to evaluate the asset for this pillar, then the grade for this pillar will be set conservatively based on these data. Making the final selectionThe final selection of tokens in the K33 Vinter Quality Index is made by ordering all qualified tokens by their Quality Score. The cutoff score is set by applying the 'elbow eye test.'
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