Introduction

In this dashboard, we’ll be looking at what the distribution of swap amounts in rounded-up sizes looks like, in both $ and $RUNE. We’ll then filter down the distribution to the highest count range (via inspection) and precisely determine the highest count by bin_size and $ and $RUNE upper limits.

Agenda

1. Swap Volume

2. Distribution of Swap sizes

   1. Binned Swap Size Distribution w/ dashboard parameters

3. Conclusion and Evaluation

Dashboard

• REFRESH: Updates Daily
• PARAMETERS (Only last section):
  • rune_celing → Upper limit for Rune swap size
  • usd_ceiling → Upper limit for $ swap size
  • bin_size_usd → Bin sizes for $
  • bin_size_rune → Bine sizes for Rune

1. Swap Volume

In this section, we’ll investigate the pool's swap volume in $ and $RUNE terms. We will also look at pool market share regarding swap volume in both $ and $RUNE.

2. Distribution of Swap sizes

In this section, we will investigate the distribution of swap sizes. In this case, there is rounding enabled to 3 and 2 significant figures, respectively for $ and $RUNE, in order to speed up the dashboard load and reduce the size of the data that needs to be downloaded upon the first load.

a. Binend Distribution for Swap Size

In this section, we’ll be looking at the binned distributions for swap sizes in $ and $RUNE respectively, by the pool name and given the dashboard parameters.

3. Conclusion and Evaluation

The majority of Swap Volume, in both the $ and $RUNE distribution, is distributed around BNB-BUSD and RUNE pair, which is expected as it’s also the one most traded in/out with on Thorswap, followed by the BTC and ETH pairs. I expect this will remain the same for quite a long time. The only exception we see between the $ and $RUNE distributions of swap volumes is that USDC from ETH the network is higher on the RUNE one compared to the $ one. What is also interesting to see, is that even though UST and LUNA pools were incorporated very close to the collapse of Terra, they have had a lot of swap volume through them.

The Swap Distribution confirms our assumption that the distribution is left-skewed as the majority of people using Thorswap, Rango or others are “small fish” (normal people) and not “whales”. We also see that on a log scale it sort of almost looks like an exp(-x) function, which is quite interesting and also expected as it’s supposed to mirror a left-skewed gaussian distribution.

In the Binned Swap Distribution, we can really dig into the different bins and look at which pools are prevalent and determine which bin range in $ and $RUNE has the highest Swap Frequency/Count. What we see, is that for $ Swap Size the 400 =< x < 500 $ range seems to have the highest swap frequency/count. Whereas for $RUNE what we see is that most users swap between the 0 =< x < 50 bin range in $RUNE. with the next lowest being around the 350 =< x < 400 bin range in $RUNE, which is interesting as it differs w.r.t to the $ value. It could be that when $RUNE was closer to 1 $ a lot of the swaps took place there. In terms of pools for both the $ and $RUNE Distributions, we can see that the BNB-BUSD - RUNE pool dominates across.

In conclusion, we can see that most people swapping are “small fish” level and that even though there are some whales, they are very few. What we can also see is that people love using the BNB-BUSD-RUNE pool, which also makes sense as ThorChain is in partnership with Binance and they are offering yield on both RUNE itself as well as a BUSD-RUNE and BNB-RUNE pools within their ‘Yield’ programme.