An increase in trading volume is one of the key components of a healthy digital asset market outlook. This indicates increased liquidity and increased enthusiasm of other traders for the token. The relationship between an asset’s price and trading volume is subtle, as peaks in volume often follow spikes as more and more traders jump on the bandwagon hoping to head to the moon.
However, in some cases, an increase in trading volume leads to higher prices. In such a scenario, warning of abnormal trading activity around the token could help crypto investors spot early signs of an impending rally. Whether they are triggering batches of trading volume or tracking price action, assets that exhibit unusual behavior in this key account deserve closer attention.
The five assets below experienced the largest week-to-week growth in trading volume last week and are featured in the Abnormal Volume section of the Cointelegraph Markets Pro dashboard. In three out of five cases, an abnormal increase in trading volume indicated a significant increase in prices.
Front: Explosion of trading volume after the IPO
FRONT, the token representing the decentralized finance (DeFi) aggregator Frontier, topped the chart on trading volume last week with a 3041% increase in heels on Korean crypto exchange Bithumb. As the chart shows, the January 26 listing announcement only caused the price to rise when the coin nearly doubled in value, from $0.41 to $0.78 in less than six hours. Volume followed price action closely, and peaked the day after the announcement.
QKC: A smaller price pump is waiting for the price peak
QKC price (in blue) and volume (small), January 22-29. Source: TradingView / TIE
QuarkChain (QKC) saw two surges in trading volume last week, the largest of which (+2862%) occurred in the past and followed a weekly increase in the coin’s price. In a strange twist of the story, there was another short-lived increase in trading volume that occurred on January 25th and occurred about 18 hours before the price hike.
Waves: the first wave of price, the second wave of volume
WAVES price (in blue) and volume (small), January 22-29. Source: TradingView / TIE
At the peak of its volume momentum on January 27, WAVES posted an 860% increase over the previous week. A volume pump followed a price hike as the token rose from $8.39 to $11.38 in about five hours. Trading activity remained high even though the price started correcting.
LOOM: The short volume trading pump is waiting for the price peak
LOOM price (in blue) and trading volume (small), January 22-29. Source: TradingView / TIE
The trading volume and price chart on Loom Networks (LOOM) is similar to the QKC chart above, with a sudden, short-term increase in trading volume occurring a few hours before the week’s price peak. One can only guess why LOOM’s trading volume exploded on January 25 from around $5 million to over $34 million (an increase of 520% from last week). What is certain is that LOOM price rose by 14% over the next day to reach a weekly high of $0.062.
OXY: Price and volume go up together
OXY price (in blue) and volume (small), January 22-29. Source: TradingView / TIE
In the case of Oxygen (OXY), the price and volume lines started on the afternoon of January 24th on the bullish lines and moved hand in hand. The maximum trading volume of $3.8 million recorded on January 26 represents a 421% increase over the previous week. A weekly price peak near $0.49 followed 12 hours later.
Comprehensive encryption data analysis
In addition to raw skew data that can be found in a dedicated section of the CT Markets Pro website, trading volume is also a key component of VORTECS ore Score, an algorithm that compares historical and current market conditions around digital assets to learn about the past. A bullish, bearish or neutral view.
CT Markets Pro Dashboard for Extraordinary Volume, February 3rd. Source: Cointelegraph Markets Pro.
Any single calculation that makes up the market forecast for an asset may not be useful on its own, but becomes more useful when it is contextualized in the context of a number of other variables that the VORTECS algorithm takes into account, such as price action, social sentiment, and number of tweets.
