What patterns can be observed in DWF Labs' market making?

Author: JZ, Founder of JZ Invest

Today, let's review the six tokens that DWF Labs has been market-making over the past two months and identify any patterns in their price movements.

In a bear market with insufficient liquidity, market makers have become an indispensable role, such as providing liquidity for projects, increasing market depth, and stimulating the market.

Although DWF Labs, which acts as both a market maker and a VC, achieves the goals of stimulating the market and increasing liquidity, its aggressive buying and selling style has also sparked controversy.

Due to its distinctly different style from other market makers, it has even been suspected of market manipulation. The impact of the tokens that DWF has participated in market-making is categorized into two types:

1. The impact of DWF's on-chain wallet transferring tokens to exchanges on prices.
2. The impact of announcing cooperation news to assist projects in market-making on prices.

Type One

Type One (1)

Taking the following chart along with on-chain transfer records as an example:

After DWF Labs transferred tokens to Binance following the second wave of price increases for DODO and PERP, the price subsequently fell, erasing most of the previous gains.

Type One (2)

The price movements of YGG and Cyber are similar.

However, the difference is that after the first price surge of YGG and Cyber, DWF Labs transferred the tokens to Binance.

After reaching a new high again, the price significantly retraced.

Type Two

Next, let's look at the price movements after the announcement of cooperation news.

From the chart below, the price movements of MASK and APRA are completely different. This shows that the price movements brought by positive news are less regular than transferring tokens to exchanges.

How to Apply?

After discovering these patterns, one can observe which large tokens are held in the DWF Labs wallet. When these tokens are transferred from on-chain to exchanges, combined with data such as OI, spot, and contract trading volumes, one can roughly predict the possible future trends.

However, it is important to note that while history tends to repeat itself, past events do not guarantee a 100% replication in the future. DWF may also exploit human weaknesses, and when you think the same event is about to happen again, it might cut you off instead.

Therefore, once DWF Labs shows significant on-chain transfers again, trading strategies can be formulated based on price movements and data, along with proper risk management.