Soravis Srinawakoon
Sep 6, 2017 · 17 min read

Our guide to Enigma Catalyst ICO. Note that this is long article intending to provide comprehensive information for the upcoming ICO.

What is Enigma Catalyst?

Enigma Catalyst are actually two different products: 1) Enigma and 2) Catalyst. Let me explain each of them to you.

Enigma is a decentralized data marketplace. The platform aims to become the central source for a standardized, reliable, and high-quality crypto data — for example, historical open-high-low-close (OHLC) data for various crypto assets. Enigma will make it easy for data curators (data provider) to monetize their data by providing easy-to-use platform for storing and selling data. At the same time Enigma will allow interested parties to subscribe and use these data easily.

Catalyst is a one-stop-shop for quantitative trading. It will allow quantitative analysts (quants) to develop trading algorithms, back test their strategies with real data hosted on Enigma, and deploy their strategies for live trading. In addition to deploying their own money, quants can choose to market their algorithms to regular investors and earn “royalty” fee when their algorithms are used. Catalyst will be the first application built on top of Enigma (according to the founders, the name “Catalyst” is selected because it is intended to accelerate the adoption of the Enigma platform.) The closest analogy to Catalyst is Quantopian (www.quantopian.com) which is a successful quantitative trading platform for equity asset.

Some of you might not be familiar with the concepts of quantitative trading or trading algorithm. I believe it is beneficial to some readers if I explain this idea further by providing an illustrative example. I believe the best way is to give you a sense of steps a quant has to go through as he tries to develop a winning-trading strategy. If you are already familiar with quantitative trading, you may skip the next section.


Quantitative trading explained:

A mean-reversion algorithm is one of the most basic strategies in a quantitative trading repertoire. The underlying idea behind mean-reversion strategy is quite simple and it goes like this: an investment will tend to “revert” to mean after a period of over or under performance. Or put it another way: what goes up tends to come back down, and what goes down tends to come back up. As a quant, you can utilize Catalyst to develop your trading strategy following the steps below:

1. Develop your trading hypothesis / thesis: for example, building your thesis from a mean-reversion theory, you could hypothesize that the worst-performing crypto assets from previous week will become strongest performers this week as its performance “revert” to mean

2. Define criteria and parameters: in this step, you need to start defining criteria (e.g., what does it mean for asset to be worst-performing? when does the week start and end? What are the universe of assets to consider?, etc.) and actions (conditions to buy and sell asset.) For example, you might define the followings:

  • “worst-performing” assets to be the bottom 10% in term of %change in price over the past week
  • Weekly time period to start at midnight Sunday
  • Universe of assets to consider are the top 200 assets by market cap
  • Buy condition could be to buy all assets defined as worst-performing in equal dollar amount and sell after one week of holding

Note that these criteria are based entirely on human judgment. What separate a winning vs. losing trading strategies is the ability for quants to define criteria and parameters effectively.

3. Develop code: once you have all your criteria defined, this is where Catalyst comes in. You can use the Catalyst platform to translate your idea into a computer code that can execute the intended trading behaviors. Catalyst will provide you with the tools necessary to create your trading algorithms.

4. Back-test and refine: This is where Enigma comes in; your code will run on real historical data hosted on Enigma. You can observe the performance of your trading strategy and refine your criteria and parameters to obtain better trading outcome.

5. Deploy and monitor: After refinement and more back-testing to ensure the code’s effectiveness, you can deploy it for live trading and monitor its performance. Sometimes, as market conditions change, a strategy becomes less effective and you will need to modify it to reflect the changing environment or retire the algorithm.

The example of steps provided above is grossly simplified and only meant to be illustrative. Real trading strategies can have significantly more added complexities on criteria and parameters used (e.g., sell conditions can be more sophisticated to lock-in profit or cut-loss based on what the asset does as opposed to just buy and hold for one week as given in an example above.)

If you would like to learn more about this topic, I recommend you visit www.quantopian.com where you can find wealth of knowledge under their “learn” section. You can actually get your first trading code up and doing back-testing with read data set in under 30 minutes.


What problem is Enigma Catalyst solving?

Since we have two products being developed, I will explain each of them separately:

Enigma: Enigma is trying to solve the lack of standardization and fragmentation of crypto data (e.g., Open-High-Low-Close (OHLC) data, etc.) The Enigma team believes that easy-to-access, high quality data set will lower barrier to entry for various participants in the crypto market (e.g., quants, researchers, etc.) The Enigma platform will make it easy for anyone to become a data curator. In the first instance, Enigma team itself will curate several key data-sets and makes it available for all users on the platform. With the right economic model in place, it hopes that the community will grow to populate other useful data sets.

Catalyst: Catalyst is trying to make it easy for quants to operate in the crypto ecosystem. Currently, the barrier to enter for quants into this new asset class is high due to several reasons:

  1. Lack of access to high-quality set of data: high-quality, reliable data set are scarce and fragmented, making data-driven trading strategies difficult to implement
  2. Platform-specific and complex environment: while many exchanges offer API for developers to connect and develop trading algorithms, they are platform-specific and not designed for easy experimentation and testing

I believe this is a worthy problem to tackle for several reasons:

  1. Quants looking to enter crypto arena: Given high volatility nature of the crypto market, it should be an attractive ecosystem for algo traders. Providing them with a highly-functional platform to operate will likely draw significant number of quants to experiment with crypto asset class. Opportunity cost to them would also likely to be low as algorithms from equity trade could be modified for crypto trading with some adjustments.
  2. Positive effects on the crypto market dynamics: In equity market, algorithmic trading accounts for over 80% of all the trading volume. Having higher percentage of quantitative trading can provide certain positive influence to the crypto market such as lower bid-ask spread and higher liquidity as these algo traders become market makers.

The Economics:

Now that we understand the pain points Enigma Catalyst is attempting to solve, I will explore the economics of the platform. There are three key stakeholders that we need to consider: 1) quants, 2) investors, and 3) Catalyst platform owner. We will do this by answering the following questions:

  • What is the potential market size for Enigma Catalyst?
  • How much could quants be expected to earn? Is there enough incentive for them to participate in this market platform?
  • How much can investors be expected to earn?
  • How much money can Catalyst platform be expected to earn?

Answers to above questions will inform us of the viability of this project.

Taking the answer first approach, I summarize my findings below. You can also read the detail of my analyses in subsequent paragraphs:

  • Expected # of users: 50K — 100K in the first five years (Catalyst only)
  • Expected annual earnings for quant: USD 72.5K — 517.5K
  • Expected return for investors: 40–120%
  • Expected income for Catalyst platform: ~ USD 25–150Mn in the next 5 years
  • Conclusion: Economics is attractive for all stakeholders to participate in the platform

We can use quantopian as a good benchmark for some of the data points required for our analyses. After 4 years of operations, Quantopian has over 130,000 members and over 500,000 algorithms developed on its platform.

Given crypto asset class is still relatively new, there might only be a subset of quants who are interested to participate in it. I believe a reasonable number of users would be a range between 50,000–100,000 in the first five years.

Next, we will calculate how much a quant can expect to earn on the platform. To do this, we need to make several assumptions, namely:

  • Capital under management (both own capital and investor’s capital)
  • Portfolio leverage
  • Trading algorithms return
  • Royalty fee

The figures I use rely heavily on the discussion posted on Quantopian (see reference #5) However, I adapt some of the figures based on my judgement to reflect the specific nature of Catalyst platform.

Capital under management: Unlike Quantopian, Catalyst does not plan to manage the allocation of capital to quants. Quants will instead need to rely on investors’ and their own funds for their trading algorithms. For our analysis, I will assume an allocation of USD 1–3Mn from investors to each performing algorithm (based on ranges used by Quantopian.) Quants might not have access to a lot of their own fund for investment and I will assume this amount to be USD 50k.

Leverage: Algorithmic trading portfolios are leveraged to achieve higher return on capital. While the range varies greatly depending on the strategy employed and asset class being traded (e.g., Fx trades use higher leverage than equity), I will assume a leverage range of 5x — 10x which is a typical range for equity trade.

Trading algorithm’s return: This figure is very difficult to estimate as return can vary greatly for different algorithms. Quantopian uses ~8% return in an example to calculate earning for a quant. Given lower competition from other algo traders in the crypto market, at least in the first few years when the market is still nascent, there might be potential to earn higher return. For this reason, I will assume 10% — 15% range of return in our calculation.

Royalty fee: No detail is provided by Enigma team in regard to how much the platform plans to charge, and how much quants can expect to earn as royalty fee. As such, I will assume 20% with 50/50 split between quants and platform, which is the management fee implemented on Quantopian, as proxy.

Based on our calculation above, a performing quant can expect to earn between USD 72.5K — 517.5K annually. This figure should be attractive for many of them, with top performers having potential to earn up to 10x avg. US household income. Participating on the Catalyst platform seems to be a natural extension for quants who want to have exposure in crypto asset class. The incremental effort required to be on the platform should also be relative low as existing algorithms can be adapted. For these reasons, I believe the economics incentives for quants to be strong.

The investors are also well-rewarded. Even after 20% management fee, they can expect to earn 40% — 120% return on capital. This figure seems high partly because of our assumption on portfolio leverage (5x — 10x). Once track records are established for high-performing quants, I expect many investors to allocate a portion of their portfolio to quantitative trading to seek higher return.

Now, I attempt to estimate how much Catalyst platform will earn. As of this writing, there is no detail provided on how much Catalyst plans to charge for the use of platform or how much profit cut (if any) it will take. The only mention is that ENG token will be needed to access data. To understand potential earning, I will assume that Catalyst takes a 10% cut of the profit (using Quantopian figure as a proxy.) Our task then comes down to estimating the total profit pool and asset under management on the Catalyst platform.

If we look at the overall market, the size of hedge fund industry is at USD 3,000Bn at the end of 2016 according to Finalternative. Quantopian aims to become a USD 10Bn platform, and has agreed with Steve Cohen to allocate up to USD 250Mn to the best algorithms on its platform. While there are opposing views and on-going debates on whether Quantopian can scale up to USD 10Bn, I believe it is possible for Catalyst platform to achieve USD 1Bn AUM level if it’s properly executed.

For our analysis, we just want to get estimate at an order of magnitude level, so let’s assume that the asset under management would be in the range of USD 0.5–1Bn.

Based on our analysis, Catalyst platform has a potential to earn between USD 25–150Mn in the next 5 years, if it chooses to charge usage fee of the platform.


Team:

Enigma catalyst has well rounded talent with complementing technical (software dev, options trading, and data analysis) and business skills. Advisers are also strong on paper. Overall, the team appears to have the capability to execute this project.

However, there are several concerns regarding the team:

  • Recent announcement of 50% market cap increase combined with other incidents (hacking, postponed of token sale date) calls into question the team’s integrity level (more detail in the token sale analysis section)
  • Level of involvement of advisers, given some of them have a role with already large responsibility (e.g., director of MIT media lab, etc.) Based on my experience working 4+ years in consulting industry, it is a common practice, unfortunately, to put down big names in project proposals for added credibility while in reality, the working team has limited interaction with those individuals listed. As of this publication date (6th September 2017), not all advisers listed on Enigma’s website have Enigma Catalyst listed on their Linkedin profile.

Below is a summary of the team and advisors profile and background:

Guy Zyskind (Co-founder & CEO)

  • 2+ yrs of experience as software developer at SAP
  • Master thesis at MIT on the development of Enigma platform

Can Kisagun (Co-founder & CPO)

  • 2.5 years of management consulting at Mckinsey
  • Co-founded multiple startups — Exim Chain, Steer Dust
  • MBA from MIT Sloan

Tor Bair (Head of Growth and Marketing)

  • Formers option trader
  • Data scientist at Snapchat
  • MBA from MIT Sloan

Victor Grau Serrat

  • Co-director at MIT D-Lab
  • 15+ years in software development

Advisers:

  • Professor Alex Pentland — Director at MIT media lab
  • Jacob Gibson — Co-founder and COO of Nerdwallet
  • Justin Lent — Former Director of Hedge Fund Management at Quantopian
  • Matthew Falk — Former Software Engineer at Two Sigma
  • Bill Barhydt — CEO of Abra
  • Josh Lim — Former VP of Treasury and Trading Operations at Circle
  • Mael Barut — Co-founder Galois Capital
  • Kevin Zhou — Co-founder Galois Capital, Former Head of Trading at Kraken

Competition:

There are several projects competing in the crypto investment platform space. However, each project focuses on different niche of investment products. I like Enigma Catalyst’s differentiating features — a one-stop-shop easy-to-use platform for quantitative traders to develop and deploy their trading algorithms.

Being the first mover in the market, if the team can execute their vision successfully, should give them a strong defensible position against future newcomers. As more and more data sets are populated on Enigma and people are used to its protocol and data standard, the switching cost to new platform will be high.

I provide below brief explanation of the key competing projects in this space and highlights their key differentiating features:

ICONOMI: Iconomi platform is geared toward traditional investment strategies (indexing, value investing, etc.) While individuals and third-party fund managers can propose and start their own investment fund on the platform (or in Iconomi’s lingo a Digital Asset Array or DAA), Iconomi does not provide tools for quants to develop trading algorithms or data for back-testing strategy. In term of development, Iconomi is most advanced compared to others projects with platform open for public registration and two funds available for investment. You can invest in its two funds now. It has also recently announced that Columbus Capital will become its first DAA manager.

Blackmoon Crypto: Blackmoon crypto focuses on tokenizing traditional assets onto crypto platform, at least initially. Their value proposition is for investors to be able to invest in traditional asset class without having to leave crypto space.The first two funds it is releasing are high-yield and low-risk fiat fixed income fund. Based on this information, it seems Blackmoon Crypto wants to target investors who might want to temporarily park their fund onto a low-risk assets without having to go through the trouble of exchanging crypto assets to fiat which is inefficient, incur high fee, and can be considered a taxable events in some jurisdictions.


Other considerations:

Hacking incident:

  • A hacker managed to gain access to slack account of one of the admins as well as the Enigma website. The hacker posted a phishing pre-sale message on slack and sent out emails with fake address for contribution. Unfortunately, they were able to get away with ~USD 500,000. This incident caused some outrage in the community as the messages were posted in the slack announcement channel using admin accounts, so some members fell prey to the scam thinking it was a legitimate announcement. It did also hurt the team credibility.
  • However, the CEO has since came out and promised to refund those affected by the scam. This is a smart move on their part to restore investors confidence, considering the amount is < 2% of the total amount raised during ICO . The team has changed their security measures to prevent any future malicious attempts

Market cap increase:

  • The team announced a 50% increase in amount of tokens to be created five days before the token sales which is essentially a 50% increase in market cap. This, unfortunately, appears to be a money-grabbing scheme and I am quite disappointed with their decision. More detail on this announcement can be found in token sale analysis section below.

Token sale analysis

What is the utility of tokens?

According to the team, ENG tokens are used for the followings purposes:

Primary purpose: ENG is used to access data sources on the decentralized Enigma Catalyst Data Marketplace. Payment is on subscription level.

Secondary purpose: ENG tokens are used for incentives to grow and ensure stability of the network. ENG tokens are used to create demand in the data marketplace: Reward tokens are provided to quants with winning strategies. This incentivizes more quants to come on the platform and consume data to refine their strategies and gain an edge.

“Most generally, Catalyst tokens are used to reward creation by and for the community (e.g. trading strategies, data sources) and are consumed when community members access premium services on the platform.”

As you can see, the information provided by the team regarding the token is unfortunately high-level and limited. Nonetheless, I try my best below to list out some of the pros and cons of the tokens.

Pros:

  • Value of ENG directly tied to the success of the platform: as the data quality and quantity grow, there will be more demand to access it and hence increase the demand for ENG tokens. With fixed supply in circulation (or decreasing as it is “consumed”? unclear if portion of the tokens are burned as transaction fee or full amount are transferred between stakeholders)
  • Usage token — unlikely to be classified as security: based on its description and purpose, one can see that ENG token is meant to be a usage token (i.e., tokens required to use service or transaction) as such it is relatively safe against future SEC or other regulator probes as it won’t be considered security.

Cons:

  • Difficult to value: With the available information currently, it’s practically impossible to estimate a fair value to ENG tokens. We do not know how much it will cost to subscribe to data sources, etc. thus, the price of ENG will be subjected to much speculation before real product and more information regarding its usage come out
  • No participation in the upside of Catalyst: the only link to Catalyst as stated are to use ENG as incentives for quants to use the platform (e.g., give away tokens to access free data) However, there is no mention whether Catalyst will charge for its platform in the future and how ENG holders will benefit from that potential upside. In my opinion, that is likely to be a lucrative part of the ecosystem

What are the terms for token sale?

Below are the terms of the token sale:

  • Token supply: 150M fixed supply of tokens created
  • Token type: ERC20 on Ethereum blockchain
  • USD raised: $45 million
  • Implied market cap: $90 million

Distribution:

  • 50% in the token sale
  • 25% reserved as incentives for the Catalyst platform
  • 25% for team and advisers

Use of fund:

  • 60% product and technology development
  • 15% blockchain research
  • 10% marketing
  • 10% operations
  • 5% legal and administrative costs

While initially the term of sale is typical of recent ICOs with no red flags or things that seem out of line, the team has announced an increase of token by 50% — and hence the market cap by 50%! The reason provided was to ensure a “broad and fair token sale for our community.” The individual cap is also set at USD 3,600 or 6,000 ENG tokens per individual with potentially up to 50% refund.

I am disappointed with their decisions for several reasons. The “fairness” reason provided by the team does not have much ground. I tend to believe that instead of “fairness”, the team saw an opportunity to collect more cash based on the overwhelming positive feedback from community and decided to go for it. Here are my supporting evidence:

  • Since the beginning, Enigma team had a pre sale set up for accredited investors with minimum contribution of USD 100K. Obviously, only whales can be part of this.
  • There is no dedicated allocation for pre sale, meaning the tokens that go to pre sale are from the same pool as crowd sale — so more money from pre sale means less for everyone else
  • Enigma team does not attempt to do KYC to prevent people from registering multiple accounts on Slack and apply to be on Whitelist
  • The concept of individual cap has only been introduced recently. Initially one can select in the Google form how much he plans to contribute when signing up to be on the whitelist.

There have been other ICOs, notably 0x and Kyber Network, whose token sale philosophy of broad distribution has been consistent with the way they conducted their sale process from beginning to end. Despite their overwhelming positive response from the community (e.g. Kyber has over 30k followers on slack), they did not increase their cap and proceeded to honor their original commitment. This is not the case for Enigma.


Key success factors:

  • Team’s ability to develop a well-functioning platform as planned
  • Data curators providing high-quality data set on the Enigma platform
  • Quants community on Catalyst able to produce high-quality algorithms
  • Ability to effectively attract data curators, quants, and investors to the platform

Key concerns:

  • Team’s motivation in executing project in the long term given their recent change in token sale terms
  • Over-valuation and recent bad feedback from community can potentially drive price down leading to big crash similar to CoinDash
  • Pricing of data access will greatly affect token value, but no detail provided currently
  • Future regulatory that might prevent / restrict investors to put money into the platform

Conclusions:

I believe Enigma Catalyst was a good investment opportunities for the following reasons:

  • Interesting concept, tackling real pain points
  • Strong team and advisers and backing from VCs
  • Attractive economics for all stakeholders involved
  • Reasonable token sale terms and valuation

However, due to recent developments, including account hacking incident, and market cap increase at the last minute before ICO, it calls into questions the team’s integrity and their capabilities to deliver.

In the short term, token price could still be well supported given strong interest in the community as evidenced by over-subscription in both presale and whitelist. Even after the market cap increase, given the current “ICO hype” sentiment in the market, the token could still do well.

In the medium to long-term, watch out for these key catalysts that will drive the value of token:

  • Adoption of the Enigma platform by data curators
  • Announcement on detail of data subscription pricing scheme
  • Creation of essential data set for crypto trading (e.g., OHLC data)
  • Release of Catalyst platform and adoption by quants

Disclosure: We originally planned to participate in the Enigma Catalyst crowdsale on September 11th, but due to recent developments, we are now going to pass on this opportunity.


cryptobro

Cryptocurrency analysis focusing on initial coin offering (ICO)

Soravis Srinawakoon

Written by

CEO and Co-Founder of Band Protocol, Stanford CS and MS&E

cryptobro

cryptobro

Cryptocurrency analysis focusing on initial coin offering (ICO)

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