The Switcheo token (SWTH) was launched alongside Switcheo Exchange, as a mechanism for paying commissions (trading fees) on trades matched by Switcheo. As stated in our whitepaper, paying trading fees using this token allows traders to enjoy a discount.

At present, the Switcheo team feels that the token’s utility has met expectations, with over 7,531,963 tokens used to pay as fees. Currently the SWTH 30-day burn rate (incl. ETH, EOS) approximately amounts to $8,014, representing a 30-day burn-trade volume of $5,342,667 at the current market rate of $0.0044 (19 June 2019). This represents a 2.20% (21.86M / 993.49M) annualized deflation in token supply. This is in line with other deflationary tokens such as LEO (1.90%). Hyper-deflationary experimental tokens such as BOMB can have an annualized deflation of about 6%. The deflationary rate of SWTH has fluctuated over time from as low as 1% to as high as 5%, depending on token market price and exchange trading volume.

Compared to the average token, the token velocity of SWTH is considered low, as per intention.

In March, the team introduced Switcheo Chest, a concept where tokens were locked up for a reward of more tokens of the same type in the future. In effect, this was an experiment in “staking” of SWTH, and the objectives were two-fold. First off, we wanted to better understand the economics of token staking specific to SWTH (e.g. expected participation ratio). Secondly, we wanted to understand how such gamification affects token velocity for SWTH. With this knowledge we could better architect any future changes in token economics.

The results so far are in line with our expectations. Before going into details of how we intend to improve the Switcheo token based on our findings however, we would like to point out some differences between the staking and deflationary (burning) economic models.

Staking versus Burning

Mathematically, any benefits enjoyed by token holders when a set number of tokens is evenly distributed (staking) is identical to simply burning them.

To demonstrate, let us assume a supply of 100 tokens valued at $1 for a market capitalization of $100. By burning 20 tokens, the supply of tokens is now 80. Assuming the market capitalization does not change, the value of each token is now $100 / 80 = $1.25. We can see that this is identical on a per-token basis to rewarding each of the remaining holders an even share of these 20 tokens. In this reward-based (staking) model, each of the 80 remaining tokens would split the pool of 20 tokens, and be awarded 20 / 80 = 0.25 additional tokens each. Assuming the value of each token does not change, each original token holder now has 1 + 0.25 = 1.25 tokens for a total value of $1 x 1.25 = $1.25.

However, we must note that these assumptions only hold true under perfectly ideal conditions. There are externalities that must be considered in the real-world.

First of all, the deflationary model requires the market to observe changes in supply vis-a-vis market capitalization. As such, changes in supply need to be actively reported and propagated to market participants constantly. This causes inefficiencies in the discovery of the token’s fair value as the market is unable to get perfect information.

We can see that even if the market is able to easily acquire such information, there will still be an intrinsic non-zero latency in the realization of value due to the delay in propagation of said information, as well as the delay in achieving the new market equilibrium, which depends on the speed at which participants can take action on the market.

These inefficiencies may be considered inferior to distributing tokens which can be automated and therefore immediately realized without any action from market participants.

Secondly, proper liquidation of tokens is difficult for users in the deflationary model. As mentioned previously, it requires users to wait for market bids to exceed fair value before a rational token holder can sell tokens and extract any additional value. This is difficult to gauge and time consuming for users who want to continually hold only a constant token value.

Finally, the most significant and also obvious difference in the two models is that, not everyone will participate in staking — whereas in the deflationary model, all tokens enjoy the same benefits.

For example, from the Switcheo Chest experiment, a yield of 2.08% attracts only 9.7% of the supply to lock their tokens.

Additionally, it is notable that bonding and un-bonding periods in most staking models give rise to “dead” tokens — transitionary tokens in flux that are neither in the market (“circulating supply”), nor earning rewards for validating transactions, thereby further concentrating token value.

On the other hand, it is also of note that the deflationary model has a side-effect where speculators can actually capture the most value by being the first to sell on market information updates like “burn reports”. This speculative effect can also create higher price volatility.

Overall, staking more directly benefits users interested in the ecosystem instead of passive token holders or speculators. The staking model thus makes a lot of sense for a system where there are active participants such as validators securing a network, as increases in value will be captured only by those who do this work.

More importantly, it does not put deflationary pressure on the individual token price, which benefits actual users of the network (traders), and is important for a utility token.