Fantom Archive — Token Economics Research

by Andre Cronje

Note: This article was written back in January 2019, and is being released now to give the community an idea of how our thinking has developed over time.

Introduction

The following key indicators have been selected for their community sentiment, and price indicators, each is presented and a high level provided.

Buyback, an organization uses a percentage of their profits to buy back their own token at market value.

Snapshot, an event in time (normally once off) where you have to hold a minimum amount of tokens to quality for the rewards of the event.

Split, a mechanism used to either decrease or increase circulating supply, tokens are increased or decreased at a ratio of 1:x

Incentivized lockup, token holders can voluntarily lockup their tokens to show their long term commitment, they are rewarded for the lockup with a bonus or a more favourable release schedule.

Transmining, by creating volume and usage users are rewarded their fee’s back in the native token, this creates system volume as well as a dividend hold structure.

Staking, coins staked provide returns on investment.

Tiered staking, based on holding, more coins staked provide higher tier rewards.

Secondary coin airdrops, by holding the primary coin, you receive airdrop tokens from secondary coins.

Gas generation, by holding the primary coin, you receive gas for the primary coin.

Tokenomics

Token Purpose

The key aspect of a token is to secure the network.

A tokens purpose is to reward good behavior, and punish malicious behavior.

At the core design of a blockchain, the token model is easy. Reward for hosting nodes and providing useful work. In a staking model this is usually done via token dilution.

The lack of blocks, create the lack of block rewards. Instead, for any given epoch, fees are accumulated and distributed proportional to stake of the epoch.

Token Minimum

There is an inverse correlation to reward and fees. As fees decrease, reward should increase, as fees increase, rewards should decrease. No system yet models this dynamic relationship.

Ethereum, as an example, has to hard fork with every block reward decrease. Instead this introduces the concept of a minimum reward threshold.

We consider a reward mechanism of 10 FTM per epoch. A 10 FTM minimum is proportionally rewarded for each epoch, should fees accumulate in access of 10 FTM, the fees are instead used and no new FTM is minted.

This liquid relationship between minimum reward and fees allows the system to reach an equilibrium of self sustainability.

Rewarding Positive Behavior

Positive qualities;

• Accept pending transactions
• Validate transactions
• Finalize transactions

Negative qualities;

• Dismiss or Deny transactions
• Create false transactions
• Spam transactions
• Double spend transactions

Positive behavior is passive. By virtue of acting as a passive actor the node promotes positive behavior.

Dismiss or Deny transactions

Positive nodes are inherently scored by their participation in transaction finalization. Positive nodes thus create an inherent reputation score. As a node refuses to finalize transactions their reputation score deviates further and further from the median. If this score falls below the median stake is revoked and participation is no longer counted.

False transactions

Separation of Node and Actor become important. Malicious transactions (and double spends) originate from an account. The concept of account level denial needs to be incorporated into a positive system. Quite a few systems introduce the idea of account limiting, soft thresholds to stop spam behavior. The concern is this excludes enterprise level interaction, this speaks more towards spam transactions than false transactions.

Spam transactions

This is a subject that has been dealt with extensively and is primarily augmented via fees. Fee’s can make a system prohibitively expensive to use. Fixed fees can be introduced via Oracles, although Oracles can lead to other malicious attack vectors.

Dynamic fees based on nonce are proposed. Increased nonce allows for decreased fees. This rewards consistent positive behavior

Tokenomics & Marketcap

Marketcap is used as a metric for evaluation. Our research shows the formula has different implementations;

• Trading Price x Circulating Supply
• Trading Price x Total Supply
• Trading Price x Minted Supply
• Trading Price x Minted Supply — Owner supply

We collected data based on the above metrics on the top Cryptocurrencies and found the following fallacies;

Circulating Supply

Most accurate and often a subset or combination of the other 3. The problem comes in with the definition of circulating. To illustrate;

Consider 5 $20 notes valued at $100. If I burn 3 notes. Is the value still $100? Clearly, no. Circulating supply assumes the 5 notes, and cannot assume the 3 burned notes. An undefined amount of tokens have been lost in dead wallets and these can not be recovered. Do these contribute to circulating supply? An undefined amount of tokens have been locked in inactive exchanges or from accounts on exchanges that have lost their username and password. Do these contribute to circulating supply?

The current calculation assumes that if completely liquidated the value would be Trading Price x Circulating Supply. This can only be true if circulating supply is 100% available on exchanges. We can clearly see that is not the case.

Chainalysis provided that 17% — 23% of all existing bitcoins have been lost in dead wallets. 2% have been lost due to exchanges. 2% have been lost due to strategic investments no longer active. 27% inactive possibility.

Next we need to consider micro balances, balances small enough that they do not warrant transfer as the fees are more expensive than the actual value transferred.

We assume all addresses with a balance less than current trading fees in Bitcoin are excluded. This gives us 15 million addresses with an ownership of 23,018 BTC. Another 0.13%

Circulating supply we can see needs to be adjusted by 21% — 27%.

Trading Price

Trading Price is the next vector. This assumes that it is possible to liquidate each token at the current trading price. Our research into order book depths shows this is not the case. The general standard is a sliding scale down to 0, so you would see something similar to;

$1 1%

$0.9 9%

$0.8 10%

$0.7 11%

$0.6 12%

$0.5 13%

$0.4-$0.01 44%

This hypothetical would give us a trading price of $0.495

Given a circulating supply of 100 @ $1 would provide a marketcap of $100, however given the above order book and adjusted circulating supply it should instead be 100–27% x $0.495 or $36.135

A 63.865% decrease in value.

Minted Supply

Circulating supply is predominantly calculated from minted supply. Most current coins have pre-minted their supply. This leads to an inflated marketcap. Consider the following distribution

10% Sale

10% Team

10% Community

10% Marketing

10% Opex

50% Mined

If the trading price was $1 and total supply was 100, which of the following is true

$100 (100% x 100 x $1)

$10 (10%[Sale] x 100 x $1)

$50 (50%[-Mined] x 100 x $1)

$90 (90%[-Team] x 100 x $1)

$10 would be the accurate representation assuming Team, Community, Marketing, Opex, and Mined have not been minted.

Very quickly we can see the relationship between the varying degrees of tokenomics and marketcap and how each interpretation can lead to a different net result.

Token Conundrum

What is the evaluation of a project? It is supposed to be the value of the ecosystem. Bitcoin as of writing is at $104,470,319,794. Let’s consider we sell every bitcoin, every miner, and every node. Could we get to that evaluation? So this point is already a bit invalid since there isn’t a real correlation between value and evaluation.

Then how are we currently evaluating projects? Money raised as a fully diluted value. This means if you raise $1m at 1% of total tokens, you are evaluated at $100m fully diluted. In the previous chapter we explained how fully diluted was an erroneous measurement as well, but that aside.

Now let’s compare two cases, case 1 has 1% sold, and 99% owned by the public. case 2 has 1% sold, 99% owned by the seller. Both have a $100m fully diluted evaluation, but these two cases are not equivalent.

To proceed, let’s take a step back and do a very naive budget, we will be using round numbers for simplicity sake, we are also using high numbers for a worst case scenario.

We start from the core, development.

Core developers (x5 @ $100k)

Eco system developers (x3 @ $100k)

Web developers (x3 @ $100k)

Core testers (x5 @ $100k)

Technical Writers (x2 @ $100k)

Designers (x3 @ $100k)

$2m (2.1 technically, but keeping to round numbers)+ 25% buffer for support services. $2.25m

Marketing, we allocate as much budget as we do for development. $2m + 25% operational. $2.25m

Legal. $1m + 25% contingency.

$5.75m at this point. This is a strong budget already and a significant Round A.

The above can deliver fairly easily in terms of a product roadmap.

Next comes the Crypto Game.

Exchanges. $5m.

Hackathons. $1m.

Roadshows. $2m.

Partnerships. $2m.

Media. $1m.

An extra $11m just to play the game.

$16.75m. Of which $11m is solely focused on investor ROI, not the product.

The Role of the Token

Consider the traditional corporate structure. We are service provider p and you are consumer c. P incurs a base cost x. Adds a markup for services rendered (profit margin) x+y. C purchases at x+y. x was P’s cost, y is P’s profit.

Consider the service we were providing was hosting a blockchain. We incur costs x for server fees. We charge x+y.

We want to design a structure in which the corporate is not required. So instead we look towards decentralization.

Participant P hosts a node. Consumer C wishes to use the service. For services rendered P is rewarded with a monetary value. The token T.

There exists a strange duality to the token. P would prefer T as high as possible (highest profit), C would like T as low as possible (cheapest service). If C could be provided the service cheaper at another competitive provider, they would change services.

For the equilibrium to exist T must be greater than P’s minimum, but less than C’s maximum. Pm < T < Cm. T is volatile. If T exceeds Cm, C will stop participating. If C stops participating there is no longer reward for P. This is where block rewards come in. Block rewards are a mechanism to allow for reward even if C is absent. It is life support.

In theory then, a token should find a fixed equilibrium of Pm < T < Cm. In practice we see this is not the case. Instead we relish in the volatility of T at the expense of the system.

The Role of the Investor

Investors, Tokens, Adoption, and Decentralization solutions do not mix. The investor wants the token value to be as high as possible. Adoption requires the service to be as cheap as possible.

The investors traditional role is funding for future profit dividends. Decentralized solutions lack profit dividends.

How can these two interact with one another?

Continuous Value

Traditional equity has a continuous benefit. Similar to a hardware investment for mining. At point T you have paid off your original capex and the rest is operational costs and profit.

In the ICO, you do not have this option. You have a chance to sell once and make profits.

How then do you consolidate the need to raise funds, the need for ROI, and the need for a token to remain within Pm < T < Cm?

Designing token price

We have previously discussed the equilibrium value of a token and its impact in a decentralized ecosystem. We settled on Pm < t < Cm, where Pm is the (P)roviders (m)inimum cost and Cm is the ©onsumers (m)aximum expenditure.

The objective, solve for t within the proposed architecture. We have noticed a current design trend where token price does not take system equilibrium into consideration. We explain this statement shortly.

Solve for Pm

We start with an investigation on current Proof of Work based systems.

We define the following metrics

• Hashing Power (H/s)
• Power Consumption (W)
• Cost per KWh in $(cpk)
• Cost / Day in $(cd) (cpk x 24)
• Price in $ (p)
• Mined / Day (md)
• Income / Day in $ (id) (md x p)
• Profit / Day in $ (pd) (id — cd)

Bitcoin

• 4730 GH/s
• 1293 W
• 0.12 cpk
• 3.72384 cd
• 6616.73 p
• 0.0002217 md
• 1.466929041 id
• -2.256910959 pd

Bitcoin currently has a profit per day of -$2.26

For the sake of brevity we will simply list the averaged conclusions

• BTC -$2.26 @ $6616.73 / BTC
• ETH $0.23 @ $474.58 / ETH
• ETC $0.11@ $17.12 / ETC
• XMR $-0.11 @ $138.05 / XMR
• ZEC $-0.24 @ $181.85 / ZEC
• DASH -$0.50 @ $247.29 / DASH
• LTC -$0.31 @ $84.86 / LTC

There is a trend towards 0.

How does this have a direct impact on token price?

We will use Ethereum as our example. Ethereum has a block time of ~13 seconds. 6,646.153 blocks per day (24 hours x 60 minutes x 60 seconds / 13 second block time). 3 ETH ( ByzantiumBlockReward) per block. 19,938.46 ETH per day @ 282 978 GH/s

A GeForce 1070 can have 31.06 MH/s for 130 watts, or 0.0021 ETH per day for 130 watts. 0.0021 ETH @ $474.58 gives and income of $0.99 per day. 130 watts @ $0.12 KWh costs $0.37 per day. $0,62 / day.

Let us reverse the Ethereum price and work it off of total hashing rate.

282 978 GH/s x 1000 (MH/s) / 31.06 (MH/s) gives us 9,110,688. This will require 1,184,389,568.57 watts. At $0.12 KWh this would cost $142,126.74 per hour (watts / 1000 x 0.12). $3,411,041.95 per day (cost per hour x 24). This produces 19,938.46 ETH per day, production cost value of $171.07 ETH (Total cost per day / total ETH per day produced)

The above is inaccurate as there are varying miners, each with a different hashing vs cost efficiency rate as well as price fluctuations from country to country. For a detailed model you would need average hash contribution per country and cost per country.

How do we derive a tokens value in a PoW based model?

Total daily hashing power (represented in kW) x KWd / total daily token production

If the total daily hashing power was 31.06 MH/s (represented as 130 w) then we could conclude that the cost of a single ETH would be $0,0000018. (130 (w) / 1000 (kW) x 0.12 (KWh) x 24 (KWd) / 19,938.46 (ETH per day)

Unsurprisingly, the cost of an ETH is the cost of its production.

How do we transfer this to a Proof of Stake based model?

Cost of production is as simple as hosting a node and including stake.

Theory 1: Stake is tied to production cost.

Theory 2: Stake is equivalent to up front hardware expenditure and thus does not contribute.

Continuing on from theory 2.

Operational cost of running a node.

• AWS t2.nano $0.0058 per hour
• AWS t2.medium $0.0464 per hour
• AWS t2.2xlarge $0.3712 per hour

Total network nodes x operational cost / total daily token production

Production leans towards higher tier nodes as production can occur faster, higher likelihood of being accepted in the network.

Ethereum currently has 16,970 nodes reported. Averaged to AWS t2.medium ($0.0464 per hour, $1,11 per day) we have a production cost of $18,897.79 per day or an ETH price of $0,94.

Let’s test with Qtum (Confirmed details are vague)

4 QTUM per block. 2 minute blocks. 2880 QTUM per day. May 21 reported ~7000 staked nodes. A cost of $7,770 per day. $2,69 QTUM, trading at ~$16

We will be collecting more network participation test to confirm staked node participation relationship to production cost.

The theory proposes that network participation x cost of nodes / total daily rewards is the equilibrium of token value.

POA Network, 12 validators, 5 second blocktime, 1 POA per block. 17,280 POA per day. Assuming stronger hardware, $0.3712 (t2.2xlarge x 12 validators x 24 hours) or $106,90 production cost per day should gravitate the token equilibrium towards $0.0061.

Calculating storage

Current gas used for SSTORE (Save 256 bit word to storage) is 20,000 gas. 1 KB (1024 bytes, 8,192 bits, 32 256 bit words) would cost 640,000 gas, at 50 gwei (0.00000005 ETH) it would cost 0.032 ETH, 32.768 ETH for an MB (1 KB x 1024).

AWS S3 costs $0.023 per GB vs 33,553.432 ETH (1 MB x 1024), so for competitive storage 1 GB would need to cost 0.0000483 ETH

Can production cost and storage cost be consolidated? Production cost is a function of computational and network operational expenses. Storage cost is a function of production cost of 1 bit.

There are thus two economic incentives at play that are opposing forces. The primary use case for a system will prevail.

This suggest a secondary token requirement for storage cost. This will be explore in another article.

Solve for T

Consider a Proof of Stake based network with 1 node (n) and 1 Token (t) per day. t would be valued at $1.11. For 100n = $111t.

Reward rates must form part of evaluation. A token sold at $1, with a block size of 1s and a reward of 1t would find a equilibrium towards $0.00001284 (1n@$1.11 / (24 (hours) x 60 (minutes) x 60 (seconds) x (token))). It would require a 100 000 node participation to reach over $1.28

We must consider block size, block reward, and theoretical node participation for the value of t.

First design block rewards. Then design tokenomics. Be reasonable with regards to node participation.

T will gravitate towards Pm < t < Cm

100 nodes @ $1.11 with a token price of $0.24 should produce 462.5t per day or 0.005t per second.

Token Trilemma

In our previous analysis we proposed the production cost correlation to token evaluation.

Why does a token need to exist?

To incentivize a provider to provide a service. In the case of Proof of Work, the service is mining (providing hashing power to secure the network). The provider takes an expense x and is paid for with value x + y, with y representing market value markup.

So we have proposed that in a;

• Proof of Work system, production cost is equal to, total energy cost for total hashing power / total tokens generated.
• Proof of Stake system, production cost is equal to, total hosting costs / total tokens generated.

We identify three actors

• Provider (Miner or Validator)
• Consumer (Participant in the eco system)
• Investor (Token purchaser)

Test case 1: Investor best interest

We establish the following metrics

• Production cost of token $1
• Investor price $0.1

This design has the best value for an investor, since providers won’t sell for less than $1 (why sell at a loss?), (assuming no outside factors to create sell off pressure and the system is in use), consumers will purchase tokens from investors and keep circulating to providers, providers won’t sell until profitable, and the price will gravitate upwards towards it production equilibrium of $1.

This design has a critical flaw. Why would providers join? A provider needs to provide their service at a loss until the price equilibrium is established. This risk could be mitigated by the originating entity (chain developer), but then it isn’t a decentralized solution and highly dependent on the originating entity. The speculative mining community could potentially carry this risk.

Consumers would be using the system actively, so fees could offset static (block) rewards.

Results

• Discounted value for Consumers (high adoption)
• Best ROI value for Investors (high participation)
• No incentive for Providers (low adoption)
• Theoretical upwards buy pressure
• High risk for Provider adoption

Test case 2: Providers best interest

We establish the following metrics

• Production cost $1
• Investor price $10

Providers would have a profit margin of $9, (dependent on current provider profitability ratio’s), Consumers would be paying a high price for usage. Investors would lose return on investment. The price would decrease towards production cost until it is viable for Consumer costs. System has to provide static (block) rewards (Consumers won’t be using the system, fees won’t offset the equilibrium)

Results

• High cost for Consumers (low adoption)
• Losses for Investors (low participation)
• High rewards for Providers (high adoption)
• Strong sell pressure
• High risk for Consumer adoption

Test case 2.1: Too high interest for providers

Above we propose that high Provider profit will create an influx of Providers. We need to quickly discuss the ratio of provider influx vs production increase. We have discussed that as the network grows, the production cost increases, and the profitability decreases. The ideal is that, new Providers are introduced into the system at the same ratio as sell pressure from Provider profit taking is occurring.

If the profit value is too high, you will have an influx of providers, they will each be taking profits as soon as possible (as each provider is selling to maximize current profits), this will create a strong downtrend on price until it reaches production equilibrium and then the profit seeking miners will leave the ecosystem.

Results

• High influx of profit taking Providers
• Strong downtrend in price

Test case 3: Equilibrium

• Production cost $1
• Investor price $1

Provider participation is again limited as low profit margins. Investor participation is limited as very little reward incentive. Consumer participation (if designed correct) is neutral.

Results

• Neutral cost for consumers (will only use service is valuable)
• Neutral for investors (low participation)
• Neutral for providers (low adoption)
• Price equilibrium
• Ecosystem needs a strong value proposition

Theory: Perfect storm

Provider participation increases at a ratio greater than the current production sell off pressure. If new nodes are introduced into the system faster than the sell pressure of production, price will increase.

The initial price would need to be at a level where an artificial influx of providers are not created, but value is still provided for providers.

We split providers into three categories

• Profit hunters (will gravitate to whichever system gives them the most profit, and leave when profit decreases)
• Speculative providers (will provide a service with speculation towards a future return on investment)
• Supporters (provide the service because they believe in the ethos)

We see the same rules in traditional technology exists in a blockchain driven world.

• The creators must fund the risk until adoption (and actively drive adoption)
• Providers will gravitate towards the most profitable solution and should be considered rogues in the system
• Community support allows for a stable equilibrium

Identifying the consumers

Till now we have discussed two entities, we have established the investors and the providers, but we have yet to flesh out the consumer. We consider the following consumers

• Purchaser wishes to purchase product xyz with cryptocurrency

Why would the purchaser need cryptocurrency?

• The product is only available for purchase in the currency
• The purchaser already owned the cryptocurrency
• The purchaser owns speculative value for future purchases

A following assumptions is made here, the purchaser speculates that there will be more value in the future, and thus purchases now for a future discounted value.

Is the chain being built for purchases?

• ICO participant speculates on discounted value

Why would the ICOer need cryptocurrency?

• The ICOer believes that ICO’s will be run on the system and purchases with speculative value
• The ICOer wishes to participate in an ICO that is only available in the currency

Is the chain being built for ICOs?

• Service consumer that wishes to use a service (Same as product purchasing)

We are starting to see, that a secondary metric comes into play, the value of the product itself.

Why is the chain being built? Will it integrate payment options? Will it have services on top of it? Will it host ICO’s? Will it be used as a DEX? Will it be used to build dApps?

Who are the consumers of these systems?

If we can align the consumer with the investor, we are essentially giving the consumer a discounted future value of service usage.

It becomes important to align the consumer with the investor and this should be considered in each ecosystem.

Let’s look at a few detailed use cases of consumers

Supply Chain

The purchaser wishes to know if their purchase is authentic. What are they willing to pay for this knowledge? Would they be willing to pay more if the product was more expensive? Should fees be correlated to product value?

The supplier wishes to have stock value metrics for better stock management. What are they willing to pay for this? Does this require a different fee mechanism than the purchaser?

The manufacturer wishes to optimize their supply line based off of supplier sales. What are they willing to pay for this?

Payment processor (Service, Product, ICO)

The purchaser is willing to pay a fee for purchasing an item. Is this fee cheaper than traditional processing mechanisms? Is this purchase faster?

We look towards some of the solutions we have built

Crypto based salary payment scheduler

• Consumer wishes to pay their employees in Crypto, they are willing to pay a subscription and management fee. (fixed cost)

Decentralized SMS provider

• Senders pay to send an SMS. (fixed cost)

Crowd funded p2p insurance platform

• Consumers pay monthly fees. (fixed cost)

Enterprise Data share

• Consumers are willing to pay a subscription fee for data access. (fixed cost)

So when considering a tokens value we must consider

• What is the product and how does it benefit the consumer?
• Who are the consumers, and what are they willing to pay?
• Who are the providers, and for what value are they willing to provide?

A token will gravitate towards its production cost, so if the services provided at production cost are expensive, consumers will not use the system unless it is their only option to use the system.

Framework

Transactions require fees to pay validators. For validators to join the network, the reward must offset their base cost. The protocol has high network and storage requirements, but not CPU. AWS t2.micro and mobile devices will be used as the baseline.

5% annual inflation rate, 158,750,000 FTM per year. 434,931 FTM per day. 18,122 FTM per hour. 302 FTM per minute, 5 FTM per second.

Baseline of 434,931 FTM per day proportionate to stake. At a cost of $0.02 this is $8,698 per day. At a hosting cost of roughly $0.1392, this will require 62,485 nodes to reach break even. At 1000 nodes, it is a profitability of $8.5588 per day. This means increased sell pressure for each miner, but it does mean increased miner penetration into the network. Token price will only start increasing after 62,385 nodes.

Dual token model design. FTM becomes a store of value and we introduce Gas (FTMG). 434,931 FTMG is generated per day per stake proportionally. The 20% inflation is permanently staked for FTMG, generating a share of 434,931 FTMG per day. Foundation generated FTMG is sold at 75% of market value. All funds from foundation generated FTMG is used to buy back FTM off of exchanges. The bought FTM is permanently staked.

Stake rewards increment based on lock away period.

100% dilution = 434,931 FTMG per day

Permanent lockup = 100% FTMG (numbers not finalized)

1 year lockup = 75% FTMG

6 month lockup = 50% FTMG

No lockup = 25% FTMG

Assuming all staked FTM is No lockup, there would only be 108,732 FTMG generated per day

Staking tiers (numbers not finalized)

1,000,000+ FTM = 100% FTMG

500,000+ FTM = 75% FTMG

250,000+ FTM = 50% FTMG

100,000+ FTM = 25% FTMG

Locking up 1,000,000 FTM permanently, would give a 100% proportional amount of 434,931 FTMG per day

No lockup on 100,000 FTM, would give 6.25% proportional FTMG per day

Optional features

Burn FTM for FTMG

Binance buyback (b) (2)

% of profits are used to buy back tokens

Token Burn

Coin burns are similar to share buybacks in the traditional corporate world. Listed companies buy back their shares from the market, which in most cases results in the shares’ price appreciation, as those shares are removed from the circulating supply. The share buyback scheme is a way to reward shareholders’ (as companies avoid paying dividends). However, companies might decide to buy their shares for other reasons, such as restructuring their financial ratios, consolidating ownership, or to benefit from a perceived undervaluation as the companies are able to reintroduce the shares onto the market at a later point.

In the cryptocurrency ecosystem, in the same way as in corporate finance, projects might decide to buy back their tokens. Some projects, such as Huobi, lock the bought tokens into a fund for later use, while others such as Binance (BNB), Tron (TRX) or Substratum (SUB), decide to burn the tokens by sending them to an invalid address which does not have a private key. While the former is very close to a share buyback scheme, the later has a more important impact on price as the tokens are indeed “destroyed”, and will never be circulating again — and the supply decreases forever.

In the case of Binance, each quarter, the exchange uses 20% of its profits to buy back its native coin, BNB, from the open market, and “burns” them by sending the coins to the aforementioned unrecoverable wallet. This process will continue until 100 million BNB are burnt (half of the total supply), with 5 million already burnt. The burn is Binance’s way of redistributing some of its profits to its community, as ultimately in the long-run, the aim of the burn is to increase the token’s value.

Burn Impact

From the chart below, it is clearly shown that Binance Coin (BNB) has been on an uptrend since inception when compared against BTC. The trend is hardly surprising as the exchange has rapidly and strategically grasped market share, to become the world’s leading cryptocurrency exchange by daily volume.

One of the strategies which paid off for the exchange was the early offering of coins and tokens, such as Waltonchain (WTC), despite the Chinese ICO ban — leading to many people signing up to the platform to gain access to them. Another reason for Binance’s success is the team’s responsiveness to changes in regulatory frameworks, as over the last 9 months the team changed its location multiple times (China, Hong-Kong, Japan, and soon Malta). The team also capitalised on the power of the community, such as allowing people to vote for coin listings (using BNB tokens), and enabling people to gain access to their “gas” (payouts made by holding certain coins, such as NEO in this case) which Bittrex, one of the leading alt exchanges, was not doing at the time.

Having an overview of what a coin burn is, and who Binance is, we can now dig into Binance Coin burn events, and see if they present a buying opportunity.

Ref: Trading View

The first BNB coin burn, which occurred on the 18th of October 2017, saw approximately 1 million tokens being burnt. As displayed on the chart, Binance being a small exchange at that time, the burn had little impact on the coin. This is mainly explained by the fact that as a Chinese exchange, Binance had many uncertainties and fears surrounding the state of its operations. Additionally, the exchange’s revenue and customer base was still small; therefore, the BNB token had little attractiveness to investors.

The second burn, which destroyed 2.2 million tokens, occurred on the 15th of January. At the time, Binance was already one of the leading crypto exchanges. Prior to this period, Binance increased its user base with the help of a referral program, and even had to refuse new ones in early January, leading to an increased demand for BNB tokens. This time, the burn had the expected effect: a pump leading to an all time high (current resistance), with an expected selloff a few days before the Binance Coin burn.

However, during this period, Bitcoin was on a massive bull run that led to it reaching a $20,000 high; therefore the market was overall pushed to new highs, and it was close to impossible not to make money within the cryptocurrency market. This could also explain the rise of Binance Coin, as during these times, the halving of trading fees was likely also very attractive to the many active traders (as holding BNB coins permits you a 50% fee discount).

Lastly, the third burn had a similar pattern to the second one. This time, news surrounding Binance was more regulation-related than user growth and BNB usage-related — with not only Binance disclosing their intent to move their operations to Malta, but also the future launch of its own chain, powered by BNB. However, the classic “sell the news” occurred, this time a dozen days prior to the burn; whether this is true correlation or just coincidence — as usual in the crypto markets, nobody truly knows.

However, it is worth noting that despite the BTC crash, Binance managed to reach its all-time-high resistance from the previous burn. Seeing the coin comparatively stable while the rest of the market has crashed (for example, ICX lost more than half of its value since ATH) is bound to be reassuring to investors and traders alike, and the steady growth that can be seen on the chart above is testament to that.

From the chart and analysis above, it is difficult to determine what the correct strategy to undertake is when it comes to trading the BNB coin burn news. The first burn had no impact on BNB’s price, the second played exactly the way we would expect it to (“buy the hype, sell the news”), and the third one sold off a week prior to the event, possibly due to the expectations, and traders taking profit beforehand. However, due to the non-stop good news for the exchange, it is hard to separate the effect of this news, that of the burn anticipation, and just regular, independent market movement. We would even go so far as to say that the burn has a negative effect on Binance Coin, as, from what we have witnessed so far, the expectations concerning a sell-off are so strong, that it becomes a self-fulfilling prophecy.

Nevertheless, we still believe BNB is primed for future growth, as the Binance is preparing itself to comply with European laws, is about to become a fiat gateway (accepting fiat deposits and withdrawals), and is preparing a Decentralised Exchange (DEX) which will run on its own chain and be powered by BNB — increasing BNB’s use cases and likely value.

Vechain snapshot (b/h) (1)

The X Node on-going seniority tracking has begun(block 5287109). We’re happy to announce that an estimated 51.9% of 511M circulating supply are de facto locked up. Approx.7707 wallets will be granted X Node status, estimated 162M VET are being locked up by Authority and X Nodes. pic.twitter.com/cexb2J9SJP

— VeChain Foundation (@vechainofficial) March 20, 2018

12% of all VET has gone from the exchanges in the last 48 hours alone! $VET $VEN

— Wolf of Hype (@WolfofHODL) March 11, 2018

Pundix 1:1000 split (b) (3)

For every PXS token that you own, you will get 1000 the-new-PXS tokens. Before explaining the metrics and the timing, I would like to walk you through how we came to this decision.

Why did we decide to do the token split?

During our public token sale, we’ve received numerous requests from our participants to split the tokens into smaller fractions. After evaluating the token economy and taking into consideration the price of ETH tripling since we launched the project in late September 2017, we decided to perform a split and announced it on Jan 13, 2018. At that time, there were already around 615 participants who have received PXS tokens from their pre-sale purchase as the smart contract had been written and settled.

However, on the eve of the split day on February 1, we had discovered a relatively higher spike in trading volume in P2P crypto exchanges than usual — which meant people were continuously selling and buying the PXS tokens. Over 9 million PXS tokens were traded in the past 24 hours from the time when the team took the snapshot for the unlock token. These new token holders might not know that they could not get the split if we had continued performing the split at that time. Some were trading in good faith, but some might be taking advantage of would-be buyers not knowing about the split, which means would-be buyers would have bought our PXS tokens and realized its worth plummet to 1/1000 right after. It is something that we would forbid. Hence, we suspended the split.

PXS will become the-new-PXS (Token name to be announced)

Now we have come out with a solution, which we believe can allow both the split to happen and also to protect would-be buyers from falling prey to the 1/1000 value speculation. We will perform a swap. A swap, as the name suggests, would be to transfer, say, 1 PXS to our smart contract, and in return you will receive 1000 new Pundi X tokens — the the-new-PXS. The the-new-PXStokens will function exactly the same except that the it is a 1/1000 denomination of PXS.

The swap suggestion has received support from our exchange partners and community members. They agree that the swap mechanism will allow existing contributors to receive more tokens as promised by Pundi X but also making sure that new buyers are aware of the changes.

The PXS to the-new-PXS Swap starts March 20th

The PXS:the-new-PXS swap smart contract will be live from 16:00 GMT+8 (Singapore / Hong Kong time) on 20th March, 2018. This means that PXS holders can start swapping at that time and receive the-new-PXS tokens in return. The-new-PXS tokens will be sent out to the sending address. Delay might occur due to Ethereum blockchain congestion.

Aion TRS (b/h) 1

Eye on the Supply: Aion’s Token Distribution Analyzed

One of the main features of distributed ledger technology is that it creates an immutable, shared, public record of transactions. This record allows us to trace tokens all the way back to their origin — the smart contract that generated them. This article intends to do that with Aion: go back to contract creation and examine how the Aion ERC20 token supply was initially distributed, what has happened since, and what the future holds.

The initial creation and distribution of Aion ERC20 tokens was on October 11, 2017, when 465,934,586.66 tokens were distributed to 1,477 addresses.

• 239,956,299.06 (51.5%) of those tokens were set aside for the TRS Contracts (explained below).
• 186,413,834.66 (40%) of those tokens were sent to addresses controlled by the Aion Foundation, the Founding Organization (Nuco), and Partners (collectively “Aion” or “Aion Founders”).
• The remaining 39,564,452.94 (8.5%) tokens were sent to private addresses.

Original plan for token distribution. Public sale was eventually cancelled.

To raise startup funds, Aion originally planned to conduct a private pre-sale, a public pre-sale, and finally a public sale. Any remaining unsold tokens would be split 50/50 between Aion Founders and early purchasers through Aion’s Token Release Schedule (“TRS”) program.

• 30,000,000 tokens were sold in the private pre-sale for $0.50 per token ($15 million raised).
• 9,564,452.94 tokens were sold in the public pre-sale in tranches from $0.75–1.00 per token ($8,010,994 raised).

After raising $23,010,994 total during the pre-sales, Aion determined that it had raised sufficient capital and cancelled the public sale. The roughly 240 million tokens that had been set aside for potential public sale would be distributed through the TRS program, instead.

The TRS program was intended to incentivize long-term holding by early purchasers and to demonstrate Aion’s long-term commitment to the project.

The TRS is executed by two separate contracts: one for Aion Founders and the other for early purchasers (regardless of whether purchased during the pre-sales or on the secondary market, i.e. EtherDelta). The unsold tokens were split evenly between the two contracts. Participants had to send their Aion tokens to a contract address by early December 2017 to opt in. A participant’s initial contribution plus a proportional share of the unsold tokens would then be distributed monthly through the contract.

• Purchasers contributed 37,216,967.28 tokens, plus 119,978,149.53 unsold tokens (322.4% bonus), for a total of 157,195,116.81 tokens distributed over one year (9,824,694.80 tokens monthly after initial distribution; see schedule, below).

Purchaser TRS distribution schedule. Percentages refer to total of initial contribution plus bonus (For example, if a participant contributed 100 tokens, the bonus would be 322.4 tokens, and the total amount distributed through the TRS would be 422.4 tokens. The initial distribution would be 132 tokens and 26.4 tokens would be distributed per month thereafter through November 2018).

• Aion Founders contributed 184,913,811.66 tokens, plus 119,978,149.53 unsold tokens, for a total of 304,891,961.19 tokens distributed over three years (8,469,221.14 tokens, or 2.78% of the total, monthly through November 2020; distributions fall about a week after the purchaser distribution dates, above).

Graphs showing distributions over time. Same data set used for both graphs: First/Left is overlaid (comparison); Second/Right is stacked (added together).

The TRS distributions do not necessarily go directly to sale on the open market — in fact, it appears that the vast majority are being held.

All 2296 Purchaser TRS participant addresses and Aion Founders TRS addresses can be reviewed by the public.

When the author last checked the Purchaser TRS participant addresses on May 9, 2018, 78.83% of the total tokens distributed to Purchaser TRS participants by that date were still held in participant addresses (This was done manually with individual API calls and a spreadsheet. The author invites anyone with the technical know-how to automate the process so real-time statistics can be made available upon request).

Similarly, as of this writing on July 8, 2018, Aion Founders still hold 43,852,847.09 (72.14%) of the tokens distributed through its TRS. Founder Matt Spoke mentioned recently that, as Aion completes its transition to a not-for-profit foundation, additional accounting and financial reporting will be made available to the public.

The total number of addresses holding Aion ERC20 tokens as of this writing July 8, 2018 has grown significantly to 20,050 — over 13x the number of Aion addresses when the tokens were minted and nearly 9x the number of TRS participant addresses.

The future distribution of tokens between the public and Aion Founders will not remain as shown in the graphs, above.

Aion has already announced its bounty, grant, and AionVentures programs, which will incentivize building and development on the Aion main net by offering tokens from the Aion Founder’s reserves to ecosystem contributors. Additionally, the current monetary policy on Aion’s proof of work network has a 1% annual inflation rate paid out as block rewards to miners, and this may change when Aion’s hybrid consensus protocol (delegated proof of stake plus proof of intelligence) is released in 2019.

As an added twist, through Aion’s token bridge, the total supply will exist on and across both the Ethereum network as Aion ERC20 tokens and Aion’s main net as native Aion coins. It will be interesting to watch the token migration between the two networks after the bridge is released later this year. In the meantime, check out the Alpha version of the token bridge in action and try it for yourself.

Pundix snapshot airdrop (h) (3)

For those who are wondering how are we getting our airdrops every month.

The airdrop is every month and lasts for 3 years, up till 2021.

-> Link to Airdrop Picture: https://imgur.com/a/cdzEsVx

Rules to participate in the monthly airdrop:

Purchase any amount of Pundi X and leave it in your private wallet;

MetaMask, Myetherwallet, Ledger, Trezor, Enjin, MyCrypto, Eidoo & imToken and you’re set.

The snapshot of everyone’s wallet will be at the end of every month, the last day of every month at 11.59pm SGT.

It is automatic and no registrations or other action required.

-Do note that it takes about 1 week for the airdrop to arrive so be patient my fellow pundians!

Every month, we will get airdropped 7.316% of the total amount of tokens we’re holding.

-First 12 months — 7.316% ( We are currently in the first year with the highest % airdrop )

-Second 12 months — 2.116%

-Third 12 months — 0.881%

Certain Exchanges like CoinBene, Bancor and a few more support the airdrop. (Full List below)

But some DO NOT support like IDEX Exchange so remember to find out clearly which supports airdrop and which don’t!

Ask in Telegram if unsure!

IMPORTANT:

*It is highly not recommended to leave it on any exchange because of the risk of the exchanges getting hacked.

List of Exchanges that supports the Airdrop:(Will constantly update)

Binance

Bit-Z

CoinBene

Bancor Network

WarzirX

Hotbit

Coinnest

Cashierest

~And to clarify about the airdrop, the monthly airdrop are unlocked tokens that were already paid by pre-sale & public sale investors that will be unlocked every month. So it is not new money but locked tokens that will be slowly released every month.

Pre-sale & Public sale investors were given 30% of what they were paid and 70% of the tokens will be released overtime for 3 years.

So essentially, anyone who buys PundiX (NPXS) tokens are eligible for the airdrop.

Cheers, hope this clears everything up! Gogo pundi team!

-> Help me to up vote so that everyone will know about the airdrop clarifications. <-

Additional Information about Pundi X’s X Point-Of-Sale Device:

A quick summary

We are launching a POS device, called the XPOS that can accept cryptocurrencies for merchants to use to sell their product.

Token’s utility:

• a tiny portion is used for a gas fee
• the token is used to list other tokens in our XPOS ( for example, QTUM paid us a sum of NPXS to be listed later in our XPOS, this will include future coins that will be listed in our XPOS )
• loyalty programs are made & paid with NPXS
• Ads that run through our XPOS are also paid in NPXS
• future products will be paid with NPXS
• claim goods and services from merchants

as for our XPOS, there are 2 parts, 1 being the merchant, and 1 being the user:

For the merchants:

1. you get 1% extra as a fee ( you can set it up from 0–3%, but we reccomend 1%)
2. you can sell crypto (again with that 1% fee)
3. you can sell the XPASS cards
4. the POS can setup your inventory, loyalty programs, ads, print smart receipts as well
5. you can accept crypto (again the 1% fee)
6. you will be one of the first to change how the world use cryptos :)

For the XPASS holders:

1. they can liquidate their crypto assets through our merchants, hassle free
2. they get a special discount
3. if you lose the XPASS black card, we are able to recover it ( as long as you have the security card )

Attention, Pundians. It’s the time to prepare to get ready to receive the monthly unlocked tokens. The unlocked token “ownership” is tied to the token holders regardless where you get NPXS and PXS tokens.

During the swap period from March 20 to Sept 20, both NPXS and PXS token holders will get the unlocked tokens automatically. After Sept 20, only NPXS holders will get monthly unlocked tokens.

The rate of 7.316% applies to the monthly unlocked tokens will last from now till December 2018, followed by 2.11637% in 2019, and 0.88187% in 2020. There will be no unlocked token distribution after January 31, 2021. You can see the chart in full detail here.

Here is the detail of how we calculate and release the unlocked tokens:

• Snapshot time: 23:59:59 SGT (UTC/GMT+8), June 30, 2018
• Execute date: 1st week of July
• Amount: 7.316% of NPXS/PXS tokens you hold
• Method: Auto. The released token will be sent to the snapshotted wallet addresses that support receiving the NPXS tokens (see a list of supported wallets and exchanges below)

WARNING:

1. Please do NOT keep your NPXS/PXS in the wallet of the public exchanges, except NPXS holders using Bancor wallet, Binance, Bit-Z, Coinbene, Coinnest, Hotbit, Tokenomy, and WazirX because you will NOT get the unlocked tokens.
2. Bancor wallet, Binance, Bit-Z, Coinbene, Coinnest, Hotbit, Tokenomy, and WazirX support the distribution of the June unlocked NPXS tokens. However, please do NOT send your PXS tokens to these exchanges because you will lose all your PXS tokens.
3. For those has not swap for NPXS tokens, we recommend you to AVOID SWAPPING your PXS tokens from June 28 to July 10 as you may experience the delay of receiving NPXS tokens due to heavy traffic on the Ethereum network. If you swap PXS for NPXS between June 28–30, it is possible that you may not receive NPXS token in time and miss the snapshot.

Make sure you hold NPXS/PXS tokens in an ERC20 wallet that you own the private key, such as MyEtherWallet, Metamask, Nano, Trezor, Trust Wallet and Imtoken or hold NPXS token in supported exchanges, such as Bancor, Binance, Bit-Z, Coinbene, Coinnest, Hotbit, Tokenomy, and WazirX.

Keep your NPXS/PXS tokens three hours before 23:59:59 SGT (UTC/GMT+8) on June 30, 2018, and three hours after 00:00 SGT (UTC/GMT+8) on July 1, 2018. If you are not able to follow the timeline and the guidance above, you will not receive the unlocked tokens.

Pundi X team will distribute the unlocked tokens to Pundi X holders who hold their tokens in the private wallets (including Bancor wallet) in the first week of July.

Exchange partners (Binance, Bit-Z, Coinbene, Coinnest, Hotbit, Tokenomy, and WazirX) will distribute unlocked tokens to NPXS holders in the first week of July.

The distribution will last up to 10 days. We also prioritize distributing the unlocked token to the NPXS holders.

For NPXSXEM and PXSXEM holders, you can read the instructions of how to receive monthly unlocked tokens here.

FAQ

• Can I store my NPXS/PXS tokens in different wallets to get the monthly unlocked tokens?

Yes, you can. Make sure you hold the NPXS/PXS tokens in the wallets recommended above and follow the timeline.

• Will I get the unlock tokens if I have bought NPXS from the exchanges?

Unlocked token “ownership” is tied to the token holders. For example, if you buy the NPXS tokens on June 29, 2018, and transfer them to a wallet suggested above three hours before 23:59:59 SGT (UTC/GMT+8) on June 30, 2018, you will receive the unlocked token as we can take a snapshot to calculate your unlock tokens in time.

On the other hand, if you sold all NPXS/PXS tokens before June 30, 2018, you would not receive any unlock tokens in June and onwards.

• How long will it take to receive the monthly unlocked tokens after the snapshot taken?

We will execute the distribution in the first week of July. Due to the popularity of NPXS tokens, you will receive the unlocked tokens up to 10 days after the snapshot is taken.

• How many monthly unlocked tokens will I receive?

The amount of the monthly unlocked tokens is calculated based on how many NPXS/ PXS you hold in the supported wallets when the snapshot is taken.

*We are still confirming the exchanges whether they offer the support of our unlocked token snapshot and distribution. We will update this post if we get confirmation from them.

Transmining (h) 1

What is the difference between Transmining and Dividend?

Transmining (also known as trade-driven mining or trans-fee mining) was a new type of mining first introduced by FCoin in May 2018. The world has since caught on with the concept of Transmining and many exchanges had adopted similar models to boost the transaction volume.

Under the model, there are 2 concepts that are proving attractive to cryptocurrency investors:

1. Gaining Dividends by holding on the platform token
2. Mining platform token

Many cryptocurrency investors we encountered are usually confused with these two concepts when they first encounter Transmining model. Hence, this article seeks to explain the difference between these two concepts to investors new to the Transmining Model.

Gaining Dividends by holding on the platform token

For most transmining exchanges, the investors will typically gain dividends in the form of revenue earned by the platform daily. As a cryptocurrency exchange, the platform earns its revenue by taking transaction fee from its users. In the Transmining model, the users will pay the platform a transaction fee but the platform will reimburse the users its platform token equivalent in value. The transaction fee the platform collected will then be distributed to platform token holders in the form of dividends at the next day.

Example A

User A made a transaction to buy USDT $10,000 of BTC on CoinEx. Since CoinEx’s transaction fee is 0.1%, User A will be paying USDT $10 to CoinEx(platform revenue). User A will subsequently be reimbursed with USDT $10 worth of CET (platform token). Beside getting the reimbursement, since User A is holding on CET, this also entitles User A the right to the dividend for holding CET. The dividend comes from the USDT $10 that User A has paid to CoinEx. In CoinEx’s case, this particular transaction will be split by this formula: USDT$10 divided by Total Circulating CET multiply by 80%.

Mining Platform Token

Under Transmining Model, the platform token is meant to be mined by the users by trading vigorously. For this reason, platform introduce the concept of mining difficulty to control the rate at which tokens are mined. The difficulty usually controls the amount of platform token that can be mined over a period of time (usually one hour). A typical miner will mine the platform token by trading aggressively till the point where he met the quota for the mining period.

Example B

Following up from Example A, if the mining limit for CoinEx is 1000 CET/hour and assuming that the price for CET is USDT $0.10. To maximise profit, User A, User A will need to generate a transactional volume of USDT $100,000 to fully mined his quota for the hour. So instead of making a transaction of USDT $10,000, User A needs to make 10 transactions of USDT $10,000 to generate the required transactional volume. Since CoinEx’s transaction fee is 0.1%, User A will be paying USDT $100 to CoinEx(platform revenue) with a transactional volume of USDT $100,000. User A will subsequently be reimbursed with USDT $100 worth of CET (platform token).

There are two aspects to consider when we are analysing the Transmining Model: mining the platform tokens and gaining dividends. Usually, during genesis stage of mining, the mining profit will be significantly higher than dividends. When the platform has stabilised, the mining profit will be comparable to the dividends gained. As cryptocurrency investors, these are aspects we need to think carefully on to maximise our profits.

Staking (tiered) (b/h)

Hardforks (b/s) (3)

Secondary coin airdrop (b/s) (ONT) (2) gas token ,ftp, ftl

Gas generation (b/h) (1)

What is NEO, and what is GAS?

An introduction to the cryptocurrency formerly known as AntShares, and its friendly sidekick.

Where did it come from?

There’s a fair amount of confusion surrounding the Neo platform. Not surprising when you consider the project’s complicated history.

Neo began life as AntShares (ANS) in 2014. AntShares, founded by Da Hongfei and Erik Zhang, has been referred to as ‘China’s first blockchain platform’. In 2016, supposedly in response to growing interest in AntShares, and a need for blockchain solutions that meet the requirements of both government regulators and private companies, Da and Erik founded OnChain, a venture-backed company that provides blockchain-based financial services. In 2017, AntShares was rebranded as Neo.

Neo and OnChain are based in Shanghai. It’s certainly the case that Chinese regulation can have far-reaching effects on cryptocurrency markets and development. Neo is equal parts vulnerable to and well-positioned to inform and cooperate with Chinese oversight.

A Smart Economy

The Neo whitepaper is our key resource in understanding the platform. Unfortunately, aspects of Neo are still in development, and certain details are unclear. At times, the whitepaper reads more as an overview of smart contracts in general than a specific guide to Neo’s inner workings.

In concept, Neo is a smart contracts ecosystem, similar to Ethereum. It allows users to automate the storage and exchange of digital assets. In order to compete with more established smart contracts implementations, Neo takes advantage of evolving technology and cooperation with Chinese authorities towards the stated goal of a ‘smart economy’.

Digital Identity

In 2005, China’s ‘Digital Signature Act’ allowed digital signatures to be legally binding in theory. The trouble here is that a means of digital identification that meets the requirements of this regulation has been hard to come by. In 2016, partnering with Microsoft China, OnChain founded Legal Chain with the goal of providing this means of identification. Legal Chain intends to apply the immutability and transparency of blockchain systems to meet these requirements, with the aim of integrating face and voice recognition along the way.

This concept of digital identity is a key feature in Neo’s proposed smart economy. Maintaining a trusted link between digital and physical entities means that you should be able to follow abuse of the system right back to a legally-binding identity.

Consensus

Neo employs a consensus mechanism called Delegated Byzantine Fault Tolerance (dBFT). Participants in the system are able to designate certain nodes as bookkeepers. A bookkeeper node must maintain a minimum balance of NEO and meet certain performance requirements.

Bookkeepers are tasked with verifying the blocks that are written to the blockchain. If two-thirds of the nodes on the network can agree with a bookkeeper’s version of the blockchain, consensus is achieved and the proposed version of the blockchain is validated. If consensus fails, an alternate bookkeeper is called and the process is repeated.

Because this consensus only needs to be replicated across a subset of the network, it is said to be more efficient than classic Byzantine Fault Tolerance. The network as a whole consumes fewer resources and can handle higher transaction volumes.

With dBFT and some other key optimizations, Neo claims to be able to handle over 1,000 transactions per second, with a goal of optimizing to over 10,000 transactions per second. Compare that to Ethereum’s current rate of 15 transactions per second.

That’s a big advantage but it could be argued that these gains come at the cost of centralization. Digital Identification and dBFT may serve to limit control of the system to a select group.

NeoContracts

Neo’s smart contracts are called NeoContracts. One of the big obstacles to designing smart contracts is that their results need to be reproduced reliably across a network.

If a contract is referenced on a blockchain and it yields different results on different systems, the network can’t reliably agree on what the blockchain looks like and blocks will be stalled. But a smart contract can’t perform meaningful operations without accessing some variables.

Timestamps — Maybe you want to use smart contracts to automate weekly payments to an employee or settle an account with a distributor every 30 days. Your contract will need to know what time it is. To provide consistent access to time data, Neo registers a timestamp to every new block that is generated. A new block is added every 15 seconds, so contracts can access the current time to within 15 seconds.

Randomness — Also useful is the ability to generate random numbers. But how do you provide a random number while still ensuring that the same random number is identified across the network? To provide smart contracts with access to randomness, a random number is inserted into the Nonce field of every new block. Contracts can reference this Nonce field to access this random number.

Data Storage- Data in NeoContracts can be stored privately, accessible only to the contract with which it is associated. Data may also be stored in a global context, accessible to all of the contracts on the network. External data must be transferred to the Neo blockchain and passed on to these private or public data stores in order to be referenced by contracts.

The Tokens

The platform involves 2 different tokens. NEO and GAS are the cryptographic currencies that drive the Neo network. Both NEO and GAS are capped at 100 million tokens each.

The NEO token is representative of shares in the Neo market, and cannot be divided. NEO holders get voting rights in the NEO ecosystem as well as rights to dividends in the form of GAS. 50 million NEO were distributed through initial crowd funding. The remaining 50 million tokens are fixed with a 1-year lockout period, expiring October 16, 2017.

These lockout tokens are to be managed by the NEO Council (A group of the project’s founders) to support development and maintenance of the ecosystem. Specifically, 10 million tokens are earmarked to reward core developers and members of the NEO Council, another 10 million are to be used to stimulate the Neo development ecosystem, 15 million tokens are to be retained as a ‘contingency’, and the remaining 15 million are to be cross-invested in blockchain ecosystems supporting Neo.

Neo’s alternate token, GAS, is generated at a rate of 8 GAS per block with the construction of the blockchain. The rate of production is reduced by 1 token for every 2 million blocks generated. Sometime around 2039, GAS circulation will reach 100 million and production will cease. Unlike NEO, GAS can be divided.

GAS dividends also accumulate as fees to the network. Users pay in GAS to deploy and run smart contracts. Fees are proportional to the computing resources consumed by the contract. These fees are distributed to ‘bookkeepers’ as reward for their activity on the network.

Special Features

In addition to the core protocol, the Neo team champions a handful of side projects that bring various benefits to the Neo Ecosystem.

Superconducting Transactions

In a traditional currency exchange, orders are placed and matched in a centralized marketplace. The process is efficient but it requires that the user release control of their funds to the exchange.

By automating the placement and matching of orders across a consensus network, you can ensure that orders are matched and processed fairly and transparently, effectively creating a decentralized exchange. But this results in slow transactions as adjustments must to be validated across the network.

Neo proposes a system whereby exchange transactions are settled on the blockchain but order matching is handled off-chain by a central exchange. Neo calls these transactions ‘Superconducting Transactions’. This is intended to provide the efficiency of centralized exchanges with the security of a decentralized exchange.

NeoX

NeoX allows transactions to traverse blockchains. I can’t find much in detail about this protocol. Similar protocols involve generating smart contracts that serve to lock funds on one blockchain in return for access to funds on an alternate chain.

NeoFS

NeoFS allows large files to be divided and distributed across the network. Users can specify the level of reliability they expect of a file. Files with low reliability requirements can be stored and retrieved at minimal cost. For a higher fee, data can be stored on more reliable nodes.

NeoQS

Quantum computers threaten the security of certain cryptographic techniques. Neo uses a lattice-based cryptographic mechanism that it calls NeoQS (Quantum Safe) which is theoretically resistant to attacks from quantum computers. It’s not likely that quantum computing will affect cryptographic systems in the near future, but it does offer some peace of mind.

Token age (h) (1)

Dual token system

There are three types of cryptoassets: stores of value, security tokens, and utility tokens. General-purpose stores of value should be valued using the equation of exchange because these currencies are independent monetary bases. Examples include Bitcoin, Bitcoin Cash, Zcash, Dash, Monero, and Decred.

Although some may disagree, I also include the native tokens of smart contract platforms such as Ethereum, EOS, Dfinity, and Kadena in this category. Why? Because there’s a real chance that the native token of a smart contract platform that becomes sufficiently useful will emerge as an independent store of value.

I won’t touch on security tokens in this essay as traditional securities are widely understood. Moving securities onto a blockchain, while better than legacy systems in terms of settlement times and custodianship, doesn’t change anything about the nature of the security itself.

This essay will focus on utility tokens.

Background

The vast majority of ICOs that launched in 2016 and 2017 were utility tokens that also acted as proprietary payment currencies. These include many of the highest-profile projects: Filecoin, Golem, 0x, Civic, Raiden, Basic Attention Token, and more.

Each of these cryptocurrencies is presenting itself as a freestanding monetary base. Monetary bases should be valued using the equation of exchange: MV = PQ. Therefore M = PQ/V.

As I noted in Understanding Token Velocity, the V in the equation of exchange is a huge problem for basically all proprietary payment currencies. Proprietary payment currencies are, generally speaking, susceptible to the velocity problem, which will exert perpetual downwards price pressure. Due to this effect, I expect to see utility tokens that are just proprietary payment currencies exceed a velocity of 100. Velocities of 1,000 are even possible. As a point of reference, the USD M1 supply has a velocity of 5.5.

Below I’ll present two new token economic models that address the velocity problem for utility tokens. Both models are primarily designed to optimize for the following:

The price of the utility token should increase approximately linearly with usage of the network.

Of course, the corollary to this is that the price of the native token should decrease if usage of the network falls, or grows more slowly than previously forecast.

Work Tokens

Augur is the pioneer of the work token model. Keep is another example.

In the work token model, a service provider stakes (AKA bonding) the native token of the network to earn the right to perform work for the network. For services which are commodities such as Keep (off-chain private computation), Filecoin (distributed file storage), Livepeer (distributed video encoding), Truebit (off-chain verifiable computation), and even “decentralized mechanical Turk” powered by humans such as Gems, the probability that a given service provider is awarded the next job is proportional to the number of tokens staked as a fraction of total tokens staked by all service providers.

The beauty of the work token model is that, absent any speculators, increased usage of the network will cause an increase in the price of the token. As demand for the service grows, more revenue will flow to service providers. Given a fixed supply of tokens, service providers will rationally pay more per token for the right to earn part of a growing cash flow stream.

Most work tokens systems enforce some sort of mechanism to penalize workers who fail to perform their job to some pre-specified standard. For example, in Filecoin, service providers contractually commit to storing some data for a period of time. During the life of the contract, service providers must lock up some number of Filecoin, and the file must be available 24/7 with some minimum bandwidth guarantee. If the service provider does not adhere to this standard, she’s automatically penalized by the protocol, and some of her staked tokens are slashed (taken away).

The valuation model for work tokens is simple: net present value (NPV).

Relative to the traditional “tokens as money” model, the work token model completely changes the terminal value calculation of a utility token. Let’s consider Filecoin to highlight the magnitude of the discrepancy.

The Filecoin team has suggested that their target market is $110B (page 16) in 2021. These figures are based on the legacy model of buying hard drives with the express intent of renting them out, rather than leveraging what is otherwise unused capacity. Filecoin is likely to offer to substantially lower unit prices. Let’s be conservative and assume that Filecoin doesn’t reduce prices at all.

Filecoin, using the “token as money” model, will have a high velocity. The velocity will not approach infinity — there is an upper limit because storage providers in the Filecoin network must post a deposit before storing files. The exact mechanics of this staking system are not yet set. Regardless, this mechanism guarantees some upper bound on the velocity of Filecoin tokens (similarly, transaction fees also impose some upper bound; however, that upper bound is likely to be so high as to be irrelevant in the context of this essay).

The velocity of the USD M1 is about 5.5. Prior to the financial crisis (in which the Federal Reserve approximately doubled the money supply), the velocity was about 10. But 10 isn’t a realistic assumption for Filecoin. Given that Filecoin isn’t intended to be general-purpose money, and that there’s not a compelling motivation to hold Filecoin beyond the minimum staking requirements, I’ll assume 3–10x higher velocity than USD M1. This implies a velocity of 30–100.

The terminal value for Filecoin — assuming 100% market saturation — is therefore somewhere in the range of $1.1B-$3.6B ($110B/100 and $110B/30).

Now, let’s consider Filecoin’s potential terminal value in the work token model. Terminal value can be calculated as cash flow / discount rate. Assuming a discount rate of 40% and operating margins of 50%*, the potential terminal value of Filecoin is $110B x 50% / 40% = $137.5B.

The work token model captures ~100x more value than the proprietary payment currency model.

How is this possible?

Considering utility tokens as a proprietary payment currency, terminal value will trend towards a value that’s a fraction of transaction volume. Why? Because, per the equation of exchange, M = PQ/V, and assuming a V > 1, M must be less than PQ.

On the other hand, if you instead use a utility token as a right to perform work on behalf of the network, it becomes valued at a multiple of the operating cash flows that the system generates rather than as a fraction of revenues paid to service providers**. Moreover, in the work token model, as a network grows and matures, it will de-risk, decreasing the discount rate, and ultimately increasing the terminal value (this actually implies that total token value should grow super-linearly relative to transaction throughput).

The work token model only works if the service being provided is a pure commodity. If suppliers compete on other variables, such as marketing, customer service, go-to-market strategies, etc. then the work token model doesn’t work. The work-token model is predicated on assigning new jobs to service providers based on their staked tokens. This is not amenable to service providers who must actively compete for customers. In these types of networks, another model is necessary.

Burn-And-Mint Equilibrium

Factom is the pioneer of the burn-and-mint equilibrium (BME) model, and is to the best of my knowledge the only token with a substantial network value that implements this model. (Factom is providing a commodity service that could be implemented as a work token; however, they chose to implement BME instead.)

In the BME model, unlike the work token model, tokens are a proprietary payment currency. But unlike traditional proprietary payment currencies, users who want to use a service do not directly pay a counterparty to use the service. Rather, users burn tokens.

Yes, the customer burns the money.

When the customer burns the money, they do so in the name of the service provider. That is, the customer publicly acknowledges (on chain) that the service provider did the work for the money that was burned.

The amount of token burned to access the underlying service should be denominated in USD. For example, in Factom, the cost of committing an entry to the Factom blockchain is $.001, regardless of the price of Factoids (FCT) in USD.

Independently of the token burning process, the protocol should mint X new tokens per time period, and allocate those tokens to service providers ratably: If 1 of 50 tokens burned during a token minting period were in the name of Service Provider A, then Service Provider A should receive 2% of newly minted tokens.

Note that X does not have to be static. It can be variable, so long as X is not a function of burned tokens (this would create circular logic, and ultimately defeat the purpose of BME).

On the surface, it seems like this model could create scenarios in which service providers are under or overpaid. However, in practice, if the system is running near equilibrium state, then service providers will be paid the appropriate amount.

Also note that in the case of Factom, service providers and block producers are the same. For ERC20 tokens, this is by definition not true since the Ethereum network abstracts block production. However, the BME model can be adopted for ERC20 tokens.

Like the work token model, the BME model creates a model in which linear growth in usage of the network causes linear, non-speculative growth in the value of the token.

Let’s walk through an example that assumes no market speculators. I’ll assume the following:

Tokens minted per month: 10,000

Cost of token in USD: $10.00

Unit cost of service: $.001

The system will be in equilibrium — meaning that the number of tokens in circulation remains unchanged — if 10,000 tokens are burned per month. Since the cost of using the service is $.001, the system will be in equilibrium if the service is used (10,000 * 10)/.001 = 100,000,000 times per month. If usage grows and 15,000 tokens are burned in a month, then total supply will decrease, creating upwards price pressure. This upwards price pressure means fewer tokens need to be burned to purchase the same amount of service from the network, bringing the system back into equilibrium.

The same system works in reverse: If usage slows and more tokens are minted than burned in a given month, supply increases, creating downwards price pressure, meaning more tokens have to be burned for the same amount of service, bringing the system back to equilibrium.

This model assumes that both consumers and service providers never want to actually hold the proprietary payment currency. Rather, this model assumes that service providers only want to hold general purpose currencies.

Note that this model doesn’t require that the service being provided is a commodity. The ratable redistribution of newly minted tokens allows service providers to price their service however they see fit.

Given that there will always be excess supply floating in the market as Menger Goods, there isn’t a universal formula model that can be used to calculate non-speculative value. Regardless, the following can be generalized:

Price should increase if # of tokens burned > # of tokens of minted

Price should decrease if # of tokens burned < # of tokens of minted

When To Use Each Model

Given that work tokens capture far more value than BME tokens, teams should try to implement work tokens whenever possible. However, the work token is not universally applicable. Work tokens are applicable for most decentralized cloud services such as Filecoin, Keep, Truebit, and Livepeer. These services can use the work token model because they provide undifferentiated commodity services. Additionally, work tokens can be used for services that require human input such as Augur or Gems.

Even systems like Filecoin that offer different levels of service — e.g., amount of redundancy — can adopt the work token model.

Most other services should use the BME model: Civic, Golem, Raiden, Basic Attention Token (BAT), 0x, etc. In these models, service providers aren’t providing a pure commodity. They’re competing on variables that are out of band relative to the protocol itself. Service providers on the Civic network compete on business development and partnership development. 0x relayers compete on UX, quality of API, SLAs, tokens listed, and more. Web publishers compete on differentiated content in the BAT network.

ICOs and Token Distribution

For tokens that employ the work token model, development teams don’t really need to worry about token distribution. Why? Because end users don’t ever need to purchase the token. Service providers seeking yield on underutilized computing/storage/bandwidth resources will figure out how to make money on underutilized hardware relatively quickly. Services like AwesomeMiner will emerge for work token-based staking protocols that dynamically allocate one’s resources to the most profitable network. 1protocol is already working on this.

Unfortunately, the BME model doesn’t provide this same benefit. Systems that implement the BME model will still need to get their tokens in the hands of millions of people so that end users can use the service.

Pricing (Of Services)

In systems using work-tokens, the unit price of the service needs to be set at the network level. Individual service providers cannot set pricing. Relative to the free-market approach of Filecoin (every miner sets her own price in a hyper-competitive market), this sounds worse. However, in practice, there will be competition, not between providers in the same network, but among providers across different networks. This is similar to how Amazon and Google set prices for storing 1GB of data in their respective cloud offerings.

In systems implementing BME, every service provider can set her own price.

Governance

For tokens that implement the generic “tokens as money” model, many entrepreneurs assume that users will have a say in governance. This is unlikely to be true in practice. Because of the velocity problem, consumers won’t hold tokens, so they’re unlikely to vote in stake-based governance models. Why spend time voting on governance issues when you only intend to hold the token for ten seconds at a time?

The work token model embraces this truth by moving stake-based voting exclusively to the supply side of the market. This feels a lot more like decentralized equity in the sense that traditional equity holders vote on what the company (supply side) should do in the context of a competitive marketplace.

In the BME model, tokens are still acting as money. It’s unclear how the BME will impact stake-based voting governance, if at all, relative to the proprietary payment currencies that don’t implement BME.

Network Effects

Neither of these models should materially affect network effects relative to the generic “tokens as money” model. Network effects for utility tokens are not based on liquidity of the token itself. They’re based on the intrinsic nature of the protocol. For example, the network effect in 0x isn’t the liquidity between ETH and ZRX, but rather the network effect of the global liquidity pool of all trading pairs using the 0x protocol. If ZRX tokens adopt the BME model, the global liquidity pool will remain unchanged. Similarly, the network effect of Filecoin, which should be approximately log(n) (due to decreasing value per marginal miner as you approach global saturation), should not be materially different as a work token versus proprietary payment currency.

Scaling Work Token Networks

In the work token model, some interesting phenomena emerge as the network grows in usage and value.

Let’s say that at time of network launch, I own 1% of all Keep tokens, that the entire Keep network can be powered by 300 mid-range AWS servers, and that there are no market speculators. In order to perform this work, I need 3 mid-range AWS servers. Let’s then say that, over the next year, demand for Keep tokens grows 100x, and that I don’t sell any tokens. In order to service that demand I’ll need to manage 300 servers.

But I don’t want to manage 300 servers. That’s just too complicated for me.

What now? I can just sell my tokens on the open market. The market should rationally value the tokens at 100x what they were valued at a year ago, because the cash flows going through the network are 100x what they were a year ago.

If the network grows faster than I can grow as a service provider, that’s ok. I can just sell my tokens to someone else. I may even be able to lend out my tokens to someone else by using 1protocol or something similar.

Synthetic Tokens

Nothing about either of these models assumes that a given token exists on a single smart contract platform. Both the work token and BME models are compatible with synthetic tokens that live across chains as described in The Smart Contract Network Effect Fallacy.

Conclusion

For the first time, Ethereum provides a canvas for developers, service providers, and consumers to transact using programmable money. Work tokens and the BME model are just two examples of the opportunities created by programmable money. The design space for programmable money is wide open and totally unexplored. New models and mechanics will emerge.

As the crypto ecosystem matures, developers will experiment, tweaking and building on the ideas presented in this essay. As they do, they’ll find new and creative ways to capture value in the native tokens of their networks without degrading user experience.

Lastly, I welcome your feedback. Please email research@multicoin.capital with questions and ideas. I presented a tremendous amount of material in this essay. I look forward to learning from the public and iterating on the ideas and designs presented in this essay.

Thanks to Matt Luongo and James Prestwich (Keep), Doug Petkanics and Eric Tang (Livepeer), Jon Choi (Ethereum Foundation), Will Peets (Passport Capital), Matt Huang (Sequoia), Gustav Simonsson (Orchid), and the others who provided input on this essay.

Update — April 18th, 2018

Doug Petkanics of Livepeer has proposed a solution to adding price discovery to the work token model:

1. Protocol progresses in rounds.

2. Worker nodes advertise their price for some unit of work, which will get locked in during the next round.

3. During the final X% of a round (say 10%), the minimum price offered by any worker node is locked in, and the only price change allowed for other worker nodes is downward adjustment in price up to this minimum amount. The effect of this is that all nodes have the option of matching the minimum offered price.

4. Users offer the maximum price they’re willing to pay. All worker nodes who have offered a price <= this offered price are considered for the job, and work is distributed to them in proportion to stake.

Since nodes had the option of matching the minimum price, they are essentially opting in to work distributed in proportion to stake. But if that price is too low for them to operate profitably, then they’ll likely converge on the 2nd lowest, or 3rd lowest price. At this point the network risks capacity planning issues…where users may all offer only the lowest possible price…except a single or very few nodes at that price won’t be able to handle the full capacity. This is a different problem which is also solve-able but a little complex to implement. The capacity issues could just be puntable to the users…who will determine through observation that they need to offer a higher price for their job to be picked up and completed in short order.

End Notes

* Although 50% operating margins are high for a hardware business, Filecoin differs in that there is no hardware cost since the hardware was otherwise going to generate $0 revenue. Also, most service providers in the Filecoin network are unlikely to have any overhead (no rent, no employees, etc.)

** Note that this is not a “like-to-like” comparison. It’s comparing apples-to-oranges. “Tokens as money” are valued as a fraction of revenue paid to service providers, whereas work tokens are valued as a multiple of cash flows. Cash flows are inclusive of operating expenses. Revenues paid to service provider are not.

A bug in BME: There is one problem with the BME model: arbitrageurs. This problem is best understood using a simple example. Let’s say that a protocol implementing BME mints 100 tokens per 24 hour period. If, at 23 hours and 50 minutes, only 50 tokens have been organically burned, arbitrageurs are incentivized to arbitrarily burn up to 49 additional tokens in their own name, as they’re guaranteed a positive ROI.

This is problematic because this means that the tokens implementing BME will be perpetually deflationary. Arbitrageurs guarantee that the supply will never inflate, even if organic demand for usage of the service decreases.

You can reduce the scope of this problem by reducing the time interval to a single block, which is about 15 seconds in Ethereum. Using a time period of a single block, arbitrageurs have nothing to arbitrage. However, with a minting schedule this short, miners are incentivized to act as arbitrageurs as described above by manipulating transaction ordering in blocks.

A solution to this problem is to use a commit/reveal scheme. Will Warren of 0x describes commit-reveal schemes in this essay. In the future, this may be addressable using zk-SNARKs.

Factom doesn’t have to deal with this problem because Factom uses a federated network model in which there are a fixed number of known service providers. Also, each federated server is guaranteed equal payment.

Mainnet Swap

VeChain (VEN) is set to officially depart the Ethereum network in the next few days, as Binance readies for the token swap which will see VEN tokens become VET (VeChain Thor) coins.

VeChain’s price has grown in the lead up to the swap, gaining 12% over the last 24 hours and breaking into the $1 billion section of the market cap high-flyers club. Beginning the day at a price of $1.62, VEN raced to $1.86 — marking 15% growth in a day when most of the market was somewhat stagnant.

That peak for the day has since settled down at around $1.81 at the time of writing, marking 12% net gains over the day.

Many VeChain holders thought the gig was up following 23% losses between July 17th and July 20th, and while VEN’s price hasn’t recovered to its former high, its reversal over the last 24 hours has been sudden and stark.

Hold

Masternodes

Personality / Thought leaders (Sunny, Justin, Jack, Matt, Charles)

Partnerships

Guaranteed returns

Optics

Buy

TA

Palmbeach

Sell

Bonus unlock

Any supply increase

FUD

TA & Panic

Missed deadline (non-delivery)