Three Strategies for Avoiding Tokens with Manipulated Volumes

Manipulated trading volumes are common on some crypto exchanges. Here are three ways traders can use data to steer clear of these pitfalls.

Understanding Market Makers and Order Book Mechanics

Identifying fake liquidity in Bitcoin and cryptocurrencies is crucial for traders to avoid unexpected sharp declines in low volume. These declines can make it difficult to execute stop losses and often lead to undesirable outcomes. By examining the organization of market makers, the mechanics of order books, and specific indicators that detect artificial volume, traders can spot red flags and avoid negative consequences.

Market makers provide liquidity by placing multiple buy and sell orders in the market. However, their actions are not always benign. They might manipulate the market by placing large orders near current prices to create a false impression of demand or supply, known as spoofing. They might also engage in wash trading, where they simultaneously buy and sell the same assets to inflate volume figures. These entities often benefit from reduced trading fees or access to tokens not available to the public, allowing them to manipulate market conditions to their advantage. Despite their deceitful tactics, three solid indicators can help experienced traders detect anomalies and avoid getting caught in tokens that may crash when a significant sell order enters the market.

Comparing Traded Volume with Order Book Depth and Free Market Capitalization

When analyzing a crypto pair, compare the order book depth with the reported daily trading volume. A disproportionate relationship, where the order book depth is shallow but the trading volume is high, suggests possible manipulation. For example, if a crypto pair has a depth of $50,000 at a 5% level but reports a daily volume of $2 million, it could indicate that the volume is artificially inflated rather than supported by actual trading interest.

For instance, Akash (AKT) volumes significantly surpass the 2% order book depth, even on exchanges typically considered safe from market manipulation. In comparison, the DYDX token, which has a similar market capitalization, showed $457,900 in bids 2% below market price at Binance, $209,000 at OKX, and $64,700 at Crypto.com, nearly 3.5 times higher than AKT’s average on the top three exchanges.

It’s also important to assess trading volumes in relation to the free market capitalization, which represents the total tokens available for trading. When daily volumes consistently exceed 30% of the token’s free market cap, it indicates unusual activity. This alert should be disregarded in the first two trading days after a new listing, as it typically reflects hype and genuine interest, especially when listed for the first time on major exchanges.

Identifying Gaps and Inconsistencies in Trading Volume

Watch for sudden and unexplained gaps in trading volumes. These gaps, where a significant percentage of the cryptocurrency’s volume disappears and reappears intermittently, can result from various factors, such as server downtime, market makers withdrawing their liquidity, or exchanges engaging in wash trading to create the illusion of activity. Such patterns are unnatural and usually indicate attempts to manipulate market perceptions.

For example, APENT (NFT) trading volume showed a clear gap, according to TokenInsight data. The token, listed on KuCoin, Bitget, Bybit, and Gate.io, typically had a 24-hour trading volume between $1.7 million and $2.9 million over two weeks. However, during a six-hour period on June 22, the rolling average volume dropped to merely $250,000, indicating potential fake volume.

Tools for Detecting Fake Liquidity

To effectively detect fake liquidity, traders should use analytical tools to scrutinize order book depth. Websites like CoinMarketCap, CryptoCompare, and CoinGecko provide comprehensive data on trading volumes and token availability, including details on locked tokens. Similarly, order book depth analysis can be found at Okotoki, TensorCharts, and TRDR, among others.