Reconciling the financial statements of cryptocurrencies exchanges proves particularly challenging as data across the internet is scarce and lacks consistency.
However, we managed to estimate key financial aggregates by retrieving all the historical disclosed data, filling the gaps with assumptions derived from industry peers, and combining a bottom-up and top-down approach to adjust the model.
This is information is reflecting all the available public data as of 20th January 2020. To find out the most recent estimates visit bqintel.com/crypto-exchnages.
According to a document reviewed by Bloomberg, Coinbase generated approximately $17m in revenue in 2016 and $923m in 2017 - an impressive 5329% growth rate mainly explained by the 2017 crypto bull market and ICO boom.
This same source projected $1.29bn in revenue and $456m in profit in 2018 despite bearish market conditions. Our estimates however are more conservative and land on $530m in revenue and $160m in profit. These figures are based on Coinbase UK Ltd fillings and its CEO Zeeshan Feroz’s, statement that the UK entity only accounts for non-US business which is approximately a third of the company’s global revenue.
The UK entity reported €153m ($173m) in revenue in 2018 and €128m ($154m) in 2017. Total turnover for non-US business increased by 20%, « largely driven by the increase in trade volumes facilitated by the addition of new digital assets available for trading » company said.
These figures suggest that Coinbase’s US business decreased by 60% in 2018. A slump that is explained by a significant drop in Bitcoin price in 2018 and a shrinkage of its active customer base. According to data collected by Tribe Capital, the number of monthly US active customers in September declined to about 80% from December.
This downward trend is confirmed in 2019 as trading volumes (BTC/USD) on the platform fell by 3% according to data retrieved from bitcoinity.org. Our estimates show that Coinbase made a total turnover of $488m and a profit of $146m in 2019.
Sticking to the analysis above, Coinbase made at least a 30% profit margin over the last 3 years, which is in line with the industry’s top players. However, in 2018, Coinbase UK Ltd reported a turnover of €153m ($173m) and a cost of sales of €139m ($159m) for the non-US business, hence a 9% operating profit margin. Given that, the company seems to tie to its UK entity costs that are not only attributable to the non-US business.
An essential component of the total cost is almost 800 people employed at Coinbase. It showed a rapid evolution since 160 people in 2015.
Coinbase has raised a total amount of $547.3m in 9 rounds according to Crunchbase. The San Francisco-based exchange was officially valued in 2018 at $8bn after it was valued in August 2017 at $1.6bn. An astonishing 400% jump marked by a $300m series E round led by Tiger Global Management. Coinbase managed to weather the storm of 2018 thanks to the support and confidence of notable investors in the crypto industry.
Assuming relatively small leverage, Coinbase traded at a record 40+ EV/EBITDA multiple in October 2018 which is, by far, outperforming all industries at the time of writing. However, it seems that Kraken also reached multiples in the same range in its last funding round in 2019, according to people familiar with the matter.
Despite unfavorable market conditions, Coinbase posts reliable financial results and an all-time high valuation. However, the platform seems to be losing ground in the US which may jeopardize its financial health and its positioning as a leading global exchange in the future.
Analysis and methodology
Crypto exchanges are a very opaque organization. We estimate their performance based on BQ Intel internal models that are calibrated to publicly available data and peer group averages. The modeling is conducted in three steps:
Step 1: We set up an initial model starting with the daily volumes multiplied by the estimated median fees.
Step 2: We conduct a multi-step iteration adjusting the fee distribution and adding non-fees revenue streams.
Step 3: The model stops iterating when we calibrate for all reference data points captured in the public and non-public sources.
Find out more about the modeling approach here.