Chasing fake volume: a crypto-plague

OKex is a ghost town

A bit of wash trading and artificial volume inflation is to be expected in a thoroughly unregulated market. What I did not expect was the magnitude of the fraud. Consider the following chart:

Slippage = f(Volume), OKex, Kraken, Bitfinex, GDAX
Slippage = f(Volume), OKex, Kraken, Bitfinex, GDAX — log scale
Volume = $1b * sin ( epoch )
Poloniex is generally quite liquid across all pairs, in spite of diminished volumes since August 2017

How bad is it?

As obvious as it is that most of OKex’s volume is doctored, how do we go about estimating whether it’s 90%, 95%, or 99% fake? I propose the following method:

  • Gather a list of trustworthy exchanges that all behave consistently on that regard
  • Perform a regression on their combined datasets, so as to be able to predict a trading pair volume from an observed slippage
  • Compare OKex claimed volume numbers vs estimated volume numbers as predicted by our model.
Volume = 4.4/slippage — 5.5
Pretty though
OKex data, and estimated % fake volume

Huobi, a close runner-up

Similar to OKex, Huobi shut down following China regulatory crackdown, to better re-open later under the Huobi.pro licence. Following the same methodology, here are the results:

Huobi data, and estimated % fake volume
Legit volumes *do not* maintain any kind of constant baseline

The Chinese rip-offs armada

You may or may not have noticed, but CoinMarketCap has quite recently listed a host of Chinese trading exchanges that all boast rather high trading volumes but somehow, no one has ever heard about. Most of them obviously share the same User Interface and trading engine.

HitBTC and Binance

For a variety of reasons, I had suspicions about two leaders in the altcoin space, HitBTC and Binance. Here’s how they fare against our set of “respectable” exchanges:

HitBTC & Binance vs reference
HitBTC data, and predicted volume discrepancy
Binance data, and predicted volume discrepancy

Caveat

While I have virtually no doubt about my claims, the numbers should not be taken at face value. Here are a few reasons why:

  • Like I mentioned about Binance, API conditions matter. I could easily see a better API improving liquidity on a given exchange.
  • Fees may matter as well. Higher fees mean market makers have less incentive to outbid themselves and reduce spreads.
  • I have only gathered one 24h averaged sample and did not bother controlling for variance. I am no academic or stats buff, but it does look like most of the results should be rather robust. Feel free to argue differently.
  • Iceberg and hidden orders. Some of the inspected exchanges may offer their users to hide their limit orders. However, since Bitfinex also offers these features and yet behaves very much in line with the rest of my “reference exchanges”, I believe it is safe to mostly discard the effect on observed liquidity.
  • Different consumer-bases may behave differently across different exchanges, although from my personal algo-trading experience, that tends to be anecdotal at best.

Why should you care?

One may argue that “since it’s not a regulated market it’s not even illegal, why shouldn’t they do what they want?”, and one would be wrong. Precisely because the market is not regulated the responsibility behooves the market actors themselves. Spreading awareness and boycotting exchanges that endorse this practice is the least we can do.

The state of the Bitcoin Cash Markets, on the day of its latest pump

Conclusion

By my reckoning, over $3 billion dollars of daily volume is nonexistent. Possibly more. Yet somehow, the practice is, if not encouraged, at least thoroughly ignored by popular data aggregators and most of their users, when all anybody really has to do is have a look to figure out that something is amiss.

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Sylvain Ribes

Sylvain Ribes

Ancien trader, ancien joueur de poker , sur Twitter @ArtPlaie