Slides from Clay Collins' presentation at Consensus: Distributed – Weds May 13, 2020 1. Quote currency dominance & why it's important 2. Why most aggregators end up doubling their volume data 3. How candles are made

1. @nomicsfinance
Storytelling Through Charts
Clay Collins, CEO, nomics.com
1. Quote currency dominance (& why it’s important)
2. Most aggregators are 2xing volume
3. How candles are made

2. About nomics.com
• nomics.com is a crypto data aggregator, going head
to head with sketchy market cap websites. We offer
transparent volume statistics for nearly every
cryptocurrency (see our ETH page) and crypto
exchange in the space, and I believe we have the
only credible crypto exchange index in the space as
of the time of this reading. We don’t do scammy ads,
bad design, and manipulated data provided by
companies whose founders hide from public view.
• Over 9 billion trades logged
• Ingesting over 5K trades/ticks per minute

3. 1. Quote currency dominance and why it’s important
2. How most aggregators are doubling volume
3. How candles are made
This Presentation Is Divided Into Three Parts

4. Chart Set #1:
Quote Currency Dominance (& Why It’s
Important)

5. What Is Quote Currency
Dominance?

6. • For a trading pair (e.g. ETH/BTC), the quote currency is the currency that is used as the
price reference.
• The price of a trading pair is always displayed in the quote currency.
• It is always the second currency quoted in a currency pair (i.e. base/quote or ETH/BTC).
• On cryptocurrency exchanges, the quote currency is almost always Bitcoin, Ethereum, a
fiat/governmental currency, a stablecoin (such as Tether or USDC), or an exchange coin.
• The quote currency is often referred to as the "secondary currency" or "counter currency."
1st, What Is A Quote Currency (QCD)?

7. What Is Quote Currency Dominance?
• The % of total global trade volume that can be attributed to the sum of all trading pairs where a
given currency is the quote currency.
• For example, BTC quote currency dominance is the % of total trading volume for a given period that
comes from trading pairs where BTC is the quote currency.
✦ % of total global vol. from all XXX/BTC trading pairs
• And ETH quote currency dominance is the % of total trading volume for a given period that come
from trading pairs where ETH is the quote currency.
✦ % of total global vol. from all XXX/ETH trading pairs
About Quote Currency Dominance (QCD)?

8. Why Is Quote Currency Dominance Important?
• Money is commonly accepted to be a Store of Value (SoV), Unit of Account (UoA), and
Means of Exchange (MoE).
• Quote currency dominance is important because it is the best method available right now
for measuring a given cryptoasset's use as a Means of Exchange (MoE) … at least on crypto
exchanges.
• Market cap is perhaps the best way to quantify SoV, MoE is tricky but can be somewhat
correlated with on-chain transaction volume, and UoA is perhaps best quantified by quote
currency dominance.
Why Is Quote Currency Dominance Important?

9. Why Is This Important?
Trading across tether & BTC pairs means market cap ⬇. USD pairs means market 🔼

10. Fiat vs. Crypto QCD
Fiat dominated as quote currency for most of crypto history.

11. Fiat vs. Crypto QCD
Crypto/crypto trades trumping crypto/fiat trades.

12. Asset Type vs. Crypto QCD
Stablecoins and crypto leading the pack.

13. Asset Type vs. Crypto QCD
Stablecoins and crypto leading the pack.

14. Asset vs. Crypto QCD
USDT, BTC, then everything else.

15. Asset vs. Crypto QCD
USDT, BTC, then everything else.

16. Chart Set #2:
Why Most Aggregators Are Doubling
Volume

17. Methodology
When we count volume, we believe the following to be the correct methodology:
1.A trade execution on a market (i.e. Binance:ETH/BTC or Coinbase:LTC/BTC), whether it is a buy or a sell,
should be counted as the volume of the trade execution once when counting the total volume of the market
2.The total volume of the space should be the sum of all volume on all markets
To show that “biggest player” is double-counting markets, we attempt to prove the following:
1.“biggest player” counts currency volume by summing all markets for the currency
2.“biggest player” counts a market towards its base and quote currency
3.“biggest player” counts total volume by summing the volume of all currencies
Methodology

19. Chart Set #3:
How Candles Are Created

20. How We Do Data
Calculating
Cryptoasset Prices

21. Tickers normally have the following data at a minimum:
• Market Symbol (i.e. ETH/BTC)
• Timestamp the ticker was computed
• Open price for the 24 hour period (price 24 hours ago)
• Close price for the 24 hour period (most recent price)
• Highest price in the past 24 hour period
• Lowest price in the past 24 hour period
• Volume total for the past 24 hours
Sometimes tickers also have additional information, like current bid and ask, price change
percent, volume weighted average price, and more.
What Is Ticker Data

22. 1. Individual trade data
• Every single trade (on every single trading pair) on an exchange
2. Candle data
• Open, close, high, low, and volume (OHLCV) for a given time frame
3. Ticker data
• Sh*t show … see next slide
The Three Kinds of Pricing Data
(Ranked from Best To Worst)

23. Trade
Data Candle
Data Ticker
Data
>
>
👍
🤨
💩

24. • Granularity is 24 hours
• You can hide tons of fraud and wash trading in them
• Updated whenever the exchanges feel like it
• Often carry forward bad data
• Aren’t computed on perfect barriers (i.e. at the end of every hour)
The Problem With Tickers

25. • The vast majority of aggregators are collecting live ticker data ONLY
• In the cases that they are collecting candle data, they are usually only collecting it to sell
this data (and aren’t using it to calculate prices)
• No public aggregators other than us (that we know of) are collecting trade level data
Why This Is A Problem

26. Huge Problem:
Most (All?) Pricing Sites Are
Calculating Candles/Prices
Based on Tickers

27. Example: Sparse Tickers Minute Candles
You should not calculate more granular data
from less granular data

28. Example: Daily Candles
The oldest ticker is the “Close Ticker”
and is used for HLCV. The youngest
ticker is the “open ticker” and is only
used for the O.
It’s almost impossible to price assets at
specific points in time

29. Example: Minute Candles
This assumes you can even
get a number of samples
during this time…
The problem gets worse at higher
levels of granularity

30. Example: Daily Candles
The oldest ticker is the “Close Ticker”
and is used for HLCV. The youngest
ticker is the “open ticker” and is only
used for the O.
It’s almost impossible to price assets at
specific points in time

31. Example: Minutes Candles w/ Volume
It’s impossible to accurately compute
volume based on tickers

32. We Can Price To The Microsecond With This Model

33. 1. You should not calculate more granular data from less granular data
2. It’s almost impossible to price assets at specific points in time
3. The problem gets worse at higher levels of granularity
4. It’s almost impossible to price assets at specific points in time
5. It’s impossible to accurately compute volume based on tickers
The Problems Keep On Coming

34. The End
@nomicsfinance

35. nomics.com
Q&A
@nomicsfinance