Market Manipulation Investigation

Using Nakamoto Terminal (NTerminal) in Splunk Enterprise, we can analyze financial data surrounding KICK. Because the unsolicited token have been airdropped to so many users (inflating the current supply to over 750,000,000,000 tokens), the marketcap has also shot up (because the tokens cannot actually be sold, which would in turn plummet the listed price). There is essentially no way that users can actually short the token even if they have almost a million tokens. The whole ploy acts as free advertising for unsuspecting retail investors who will notice a large balance increase on their wallet software which steadily increases in (fake) market value.

Now I will look a little bit closer at the reported trading of this token going on, because we know it isn’t related any of the frozen tokens from the airdrop. There might be a small concentration of accounts affiliated with the “KICK ecosystem” manually trading the token up on these exchanges. Another possible scenario I see is that the exchanges are actually involved in (or at least allowing of) the market activity.

We can see that reported trading volumes seem to be coming from just a few markets, and are highly centralized on KUCOIN, and the other exchanges (with much lower volumes) are not very well known.

Comparing Trade Volumes for KICK (Feb 8th 2020, -30d)

Next, we see high price deviations between these markets, which widens as the price continues to explode.

KUCOIN and HITBTC Price/Volume for KICK:BTC Pair (Feb 8th 2020, -30d)

Already these do not appear to be normal market behaviors, but we can use more sophisticated methods of analyzing the data to look for further anomalies:

Here, I generated trade size distributions from the last 30 days for KICK. Normally, these should all be close to normal distributions, with only slight variations between exchange. Also note the scale differences by exchange.

KICK Trade Size Distributions by Exchange (Feb 8th 2020, -30d)

BTC distributions over the same time period, for comparison (including some of the same exchanges and some larger ones for reference):

BTC Trade Size Distributions by Exchange (Feb 8th 2020, -30d)

The differences in trade distributions can be explained by a variety of factors including exchange policies (such as maker/taker fees and platform trading tiers), different user demographics, fiat or stablecoin options available, trading API availability, and deposit + withdrawal fees/incentives. While the above factors suggest that trading activity should not be identical across market venues, analyzing trade data via multiple methodologies can certainly direct our attention to abnormalities worthy of further investigation.

ACFE​ published this article​ for how to discern naturally occurring statistical deviations from fraud. ​Benford’s Law​ is an observation of numerical data sets that states that the leading significant digits do not occur in an even distribution (~​11% ​for leading digits 1–9). We can look at the leading digits of bids and asks for KICK to see how they compare to the Benford model:

Benford Comparison — KICK asks Leading Digit Frequencies by Exchange (Feb 8th 2020, -30d)

All of these components together gives us a fuller picture of what might be going on with regards to the KICK ERC-20 token.