Abstract
This article provides a comprehensive categorization of cryptoasset classes and describes historical market cap trends of different crypto sectors. Our analysis will help you better understand general developments on the blockchain market and it will provide you with tools for further research. The proposed three-level categorization model can be used to identify the most attractive cryptoasset sectors, diversify one’s crypto portfolio, forecast macro developments based on historical trends, etc.
Although several cryptoasset categorizations exist (most notably, those by Fundstrat and Multicoin Capital), they fail to fully appreciate the complexity of the crypto space. To our best knowledge, no publicly available in-depth analysis of crypto sectors’ growth exists at the moment. This article is the first attempt to fill these research gaps.
Our cryptoasset categorization groups blockchain projects into the following three high-level categories:
- Store of Value / Currency / Mode of Payment
- Blockchain Infrastructure
- Services Built on the Blockchain
Second and third level cryptoasset classes provide more granular grouping that reflects the vastly different areas of blockchain applications:
Figure 1. Three-Level Cryptoasset Categorisation
Our analysis of market cap trends revealed that growth rates of cryptoasset sectors differ significantly. The largest cryptoassets (Bitcoin and Ethereum) both underperformed in terms of market cap growth in the observation period (+84% and +76% respectively), while smaller cap projects grew stronger (+167%). On the second level of our cryptoasset classification, top performers are: Non-Ethereum General Smart Contract Platforms (+602%) and Enterprise Smart Contract Platforms (+285%). Privacy-focused cryptoassets significantly underperformed with only +30% market cap growth. On the third classification level, Gambling & Gaming subcategory is the leader of growth (+423%), while Tokenized Assets (+7%) are the clear loser. The details on other cryptoasset classes’ performance are described in Findings section.
You may have already observed the trends we describe and some of the developments may seem obvious to an expert. Yet, this article is of value even to trained experts, as it puts an exact number on the growth rates of different cryptoasset categories and allows you to benchmark them easily.
Subscribe to our pub to get the latest analytics on crypto: Crypto Data Science.
Analysis
Several cryptoasset categorizations currently exist, yet these categorizations do not properly reflect the complexity of the crypto universe, which contains vastly different applications of blockchain technology. The existing categorizations either remain too abstract and lack the required level of detail or contain extremely granular subcategories failing to organize those into larger meaningful groups. For example, Tom Lee (Fundstrat) groups cryptoassets into commodities, privacy, platforms, exchanges and stablecoins — categorizing cryptos based on how they trade. General partners of Multicoin Capital group cryptoassets based on their valuation models. The resultant categories are: currencies (stores of value), security tokens (represent real-world assets) and utility tokens (work tokens). Jake Ryan (Tradecraft Capital) recognizes the need for a more granular approach than those outlined above and proposes the following categorization: core/reserve, currencies, platforms, utility tokens, security tokens, commodities, appcoins and stablecoins. We would argue about the exact categories created by Jake (e.g., we are particularly sceptical about core/reserve group that contains Bitcoin and Ethereum); however, our point is that we need an altogether different approach to cryptoasset categorization. We need to appreciate the vast functional differences of cryptoassets and yet be able to talk about meaningful high-level cryptoasset categories. To ensure that we provide both the required level of detail and abstraction, we created our three-level categorization model.
Cryptoasset categorization is an important intellectual pursuit, yet on its own it provides little value to an investor other than being a tool for further analysis. In this article, we use this new tool and make an in-depth analysis of historical trends, highlighting what cryptoasset (sub)categories have been growing the fastest and how they benchmark. To our best knowledge, such an analysis has never been published, at least not at the level of detail we deliver.
Prerequisites
In this section, we provide a description of different cryptoasset types that we further use in this article and that may not be intuitively clear to all our readers. If you are sufficiently familiar with different types of cryptoassets and their distinct qualities, you may skip directly to Methodology.
Store of Value (SoV) — a function of a (crypto)asset that can be saved, retrieved and exchanged at a later time, and be predictably useful when retrieved. More generally, it is an asset that retains its purchasing power into the future. Precious metals (in particular gold) are examples of classical store-of-value assets.
Currency / Mode of payment — asset that is designed to work as a medium of exchange, i.e. being a tradeable entity used to avoid the inconveniences of a pure barter system (exchanging goods or services in return for other goods or services).
Smart Contract Platform — provides means (both software and hardware) to create and execute smart contracts on a blockchain network without any need for a centralized authority. Smart contracts are contracts with terms and conditions written in self-executing computer code.
Blockchain Interoperability — a function or service that drastically improves information sharing between different blockchains.
Blockchain Discovery Tools — search and browse tools that help you find blockchain applications (dApps), smart contracts, data, and blockchains themselves.
Tokenized Assets — digital contracts for fractions of off-chain assets that already have value (e.g., real estate or equity in a company)
Stablecoin — cryptocurrency pegged to a stable asset (e.g., fiat currency).
Methodology
This analysis is based on historical market cap (MC) data from July 2015 to July 2018. Currently, out of 1.6K cryptoassets listed on Coinmarketcap.com, the top 25 cryptos account for 90% of total MC while the bottom 1,000 cryptos for less than 1%. Due to this, we decided to focus our analysis only on major cryptoassets. We defined “major” as a listing that appeared in the top 95% of cumulative MC on any given day starting from 2015. This way we could focus only on those blockchain projects that have received wide recognition from crypto investors while filtering out all the minor long-tail cryptoassets.
149 cryptoassets have satisfied the above-mentioned criteria. In order to prepare the data, we first carefully categorized all the 149 cryptoassets as granularly as possible based on the publicly available information. When a cryptoasset exhibited hybrid properties (e.g., Store of Value and Smart Contract Platform) we categorized it based on its main value proposition. In the next step, we analysed the initial categories and built clusters of cryptoassets with distinct qualities. The final result of the categorization is our three-level hierarchy.
In order to compare the performance of different cryptoasset classes we indexed our data to September 2017. Why did we decide to index our data? When we first built MC domination graphs similar to those on Coinmarketcap.com (daily changes in MC dominance by cryptoasset, see below) we quickly realized that it is highly challenging to recognize and evaluate patterns when looking at this graph. We can easily recognize MC development patterns of dominant cryptoassets (e.g., Bitcoin or Ethereum); however, at the level of detail we provide with our crypto categorization, the task becomes very difficult and error-prone. So when we index the data, we set a common ground for all crypto classes and can then see how those perform relative to the given point of time. This also enables us to easily compare all the crypto classes, identify the winners and see exactly by how much percent of MC growth they outperformed the rest.
When we were selecting the base period for our index, we wanted it to be relatively recent and representative of a stable market — both in terms of overall MC and Bitcoin/Altcoin dominance. For this reasons we avoided the turbulent time of December 2017 — January 2018 and picked end of September 2017 as our base period. During this time, the crypto market was on the rise and this rise was steady and sustainable, unlike the explosive (and irrational) growth in December 2017. By September last year, Altcoins had already established a strong position on the crypto market and achieved a stable share of MC (with Bitcoin dominance stabilizing at around 48%). All this gave us confidence in selecting end of September 2017 as the base period for our analysis.
Figure 2. Market Cap Dominance of Selected Cryptoassets (coinmarketcap.com)
Limitations
We expect that many of our readers will think in terms of investment opportunities when interpreting our analysis results. Since we focus on MC data and not cryptoasset prices to identify trends, the following limitations apply when you think about returns on your investments.
MC growth is not equal to price increase. Although changes in MC roughly indicate changes in cryptoassets’ prices, token issuance model affects the prices as well. For example, Bitcoin may well be losing on MC dominance, but since new token issuance or inflation level is very low (currently around 4% per year), price may be rising faster than that of other coins with high inflation level but increasing MC. This has to be accounted for when making investment decisions about a specific cryptoasset.
Number of blockchain projects is another variable that affects MC of cryptoasset sectors and prices of individual projects in different ways. MC of a sector may be expanding due to a growing number of new blockchain projects that enter this particular sector, not due to valuation increase of old projects. If new projects compete for the same market and therefore investors, then their total sector MC can grow, while on individual project level MC may well be shrinking.
Findings
Cryptoasset Categories
Below you can see our three-level cryptoasset categorization. We avoid lengthy descriptions of the categories, as those are self-explanatory, in our opinion. If you are not sure about the categories’ definitions, refer to Prerequisites section above. You can find the details on how we approached the cryptoasset grouping in Methodology section.
Figure 3. Three-Level Cryptoasset Categorisation
Current State of the Cryptoasset Categories
In order to visualize the current state of cryptoasset categories, we calculated market share and counted the number of blockchain projects for each level of our cryptoasset categorization (as of 07.07.2018).
Figure 4. Current State of The Cryptoasset Categories
Not surprisingly, SoV / Currency / Mode of Payment category currently dominates the market with 62% MC, while Blockchain Infrastructure projects account for 28% MC. Services Built on the Blockchain is the largest category in terms of the total number of distinct projects, yet it currently only accounts for 6% of overall MC.
While looking at the current state of cryptoasset categories is informative, it is a static image that does not illustrate the rapid changes in crypto categories’ relative importance over time. The section below dives deep into those historical developments.
Historical developments
For the analysis of the MC growth trends we indexed our data to 24.09.2017 (the rationale behind the date selection is outlined in Methodology). Growth numbers in text descriptions below compare 07.07.2018 to 24.09.2017, unless stated otherwise.
MC growth of major cryptoassets (as defined in Methodology) was at +106%. Contrary to bitcoin maximalists’ intuition, the world’s first cryptocurrency has been clearly underperforming in terms of MC growth. Bitcoin grew only by +84% in the given time period. Ethereum had an even weaker growth: +76%. If we exclude Bitcoin and Ethereum from the data, then we see that the overall market capitalization increased by +167%.
When we look at the high level of the proposed cryptoasset categorization, we notice that category SoV / Currency / Mode of Payment grew by +94%, Blockchain Infrastructure by +134% and Services on the Blockchain by +133%.
Figure 5. Market Cap Growth: 1st Level of Cryptoasset Categorization
Now let’s take a look at the same data but this time excluding Bitcoin (and its hardforks) as well as Ethereum (and Ethereum Classic). Non-Ethereum Blockchain Infrastructure category is performing the strongest (+495%), while SoV / Currency / Mode of Payment category excluding Bitcoin grows at a less impressive but still higher than the original rate (+129%). So alternatives to Ethereum clearly outperformed the original during the observation period, while cryptoassets similar to Bitcoin in their function performed less impressively, but still better than the world’s first cryptocurrency.
Figure 6. Market Cap Growth: 1st Level of Cryptoasset Categorization (excl. Bitcoin and Ethereum)
On the second level of cryptoasset categorization we see an outlier — Blockchain Discovery Tools with +530% MC growth. However, this group of cryptoassets had a relatively small starting base in September 2017, so we excluded the outlier and took a look at the remaining categories.
Figure 7. Market Cap Growth: 2nd Level of Cryptoasset Categorization
The remaining top-performers are: Payment Settlement (+198%) and Blockchain Interoperability (+189%) categories. They are followed by Financial Services (+145%), Smart Contract Platforms (+132%) and Non-Financial Services (+108%). General SoV / Currency category had been strongly underperforming since January 2018; however, in the past month this category strengthened its relative position but still underperformed by the end of the observation period with only +86% growth. The clear loser in the MC dominance race is Privacy SoV / Currency group. Privacy-focused cryptoassets lost their position and finished with a meager +30% growth by July 2018.
Figure 8. Market Cap Growth: 2nd Level of Cryptoasset Categorization (excl. Blockchain Discovery Tools)
When we drill down on the Smart Contract Platform category we notice a very strong growth in the Enterprise subcategory (+285%), while General Smart Contract Platforms ones only slightly outperformed the overall market growth (+130%).
Figure 9. Market Cap Growth: 3rd Level of Cryptoasset Categorization — Smart Contract Platforms
However, when we exclude Ethereum and Ethereum Classic, General subcategory outperformed with staggering +602% MC growth. This is in line with our previous observations on the first level categories and it once again highlights the strength that Ethereum’s competitors have gained over the past few months.
Figure 10. Market Cap Growth: 3rd Level of Cryptoasset Categorization — Smart Contract Platforms (excl. Ethereum)
Subcategories of Financial Services group grew at very different rates. MC of Stablecoins rose the fastest overall (+571%) , with most growth occurring between December and February. Between February 2018 and today, Stablecoins remained stable not only in their price (as they are supposed to) but also in their MC. Invoice Trading subcategory enjoyed a skyrocketing growth in December and January but failed to sustain it, ending up with +156% overall growth. Exchange Services’ MC increased by +204%, while Crypto Wallets subcategory grew by +136% and Asset Management by +90%. Tokenized Assets is the clear underperformer with only +7% growth.
Figure 11. Market Cap Growth: 3rd Level of Cryptoasset Categorization — Financial Services
A closer look at Non-Financial Services reveals an explosive growth of Connectivity subcategory. It is by far the fastest growing subsector of Non-Financial services (+1,386%). However, since Connectivity was in a nascent stage in September-November 2017, we exclude it as an outlier.
Figure 12. Market Cap Growth: 3rd Level of Cryptoasset Categorization — Non-Financial Services
Among the remaining Non-Financial Services, Gambling & Gaming enjoyed the strongest growth (+423%). Social Media subcategory outperformed the market (+181%), while Other non-financial services − this group is highly fragmented and includes such projects as Labor Market, Supply Chain Management, Authentication Service, etc. − had a moderate MC growth of +110%. Underdogs grew within a narrow range of +43% to +54%: Marketing, Prediction Markets, Data Storage, Computation, Data Exchange, Healthcare. Interestingly, Healthcare enjoyed a strong MC boost in January but this growth ended abruptly by the end of the month. Overall, Healthcare subcategory underperformed ending up with a lower-than-average +49% growth.
Figure 13. Market Cap Growth: 3rd Level of Cryptoasset Categorization — Non-Financial Services (excl. Connectivity)
When we indexed the data to a more recent date (25.03.2018), the relative trends remain similar with very few exceptions. Those exceptions are: Asset Management being the fastest growing subcategory (+32%) in Financial Services and Computation (+25%) in Non-Financial ones. Overall, from 25th March to 7th July 2018, the MC of major cryptoassets declined by 19%.
Conclusions
In order to understand the developments in the blockchain market, one needs a comprehensive categorization of cryptoassets. Such categorization reduces the complexity of the highly fragmented crypto space and allows one to see the developments on the market beyond short-term speculation on individual cryptoassets. Our three-level categorization model appreciates the vast functional differences of cryptoassets and provides both the required level of detail and abstraction. It can serve as a tool for a crypto investor or blockchain researcher to identify the most attractive cryptoasset sectors, diversify one’s crypto portfolio, forecast macro developments based on historical trends, etc.
Our analysis revealed that growth rates of cryptoasset sectors differ significantly. The largest cryptoassets (Bitcoin and Ethereum) both underperformed in terms of MC growth in the observation period (+84% and +76% respectively), while smaller cap projects grew notably stronger (+167%). High-level crypto category SoV / Currency / Mode of Payment grew by +94%, while Blockchain Infrastructure increased its MC by +134% and Services Built on the Blockchain by +133%. On the second level of categorization, the top-performers are Non-Ethereum General Smart Contract Platforms (+602%), Enterprise Smart Contract Platforms (+285%), Payment Settlement (+198%) and Blockchain Interoperability (+189%). Privacy-focused cryptoassets had the weakest performance with meager +30% growth. Third-level subcategory of Gambling & Gaming enjoyed the strongest growth (+423%), while Exchanges (+204%) and Social Media (+181%) subcategories also outperformed the market. Other subcategories, including Prediction Markets, Data Storage, Computation, Healthcare and in particular Tokenized Assets disappointed their investors with below-the-average growth rates.
Once you identified the fastest growing and most attractive cryptoasset sectors, you made the first step in making an intelligent investment decision. In the next step, you should evaluate the long-term outlook of the selected sectors, choose the specific blockchain projects, do your due diligence, while paying attention to token issuance model and the competitive landscape. Alternatively, a blind investment into all major cryptos belonging to an attractive cryptoasset sector with positive long-term outlook is likely to produce decent, albeit not stellar results.
Subscribe to our pub to get the latest analytics on crypto: Crypto Data Science.
The information in this article is not an investment / financial / trading advice. Please do your own due diligence before making any investment decisions. We do not recommend you should buy, sell or hold any cryptoassets.