- Captain Faibik has confirmed a bullish breakout on FET, the native coin of the Fetch.ai.
- Faibik projected FET to rally to $0.9 from the current price level.
- FET has trended sideways since reaching a yearly high of $0.6 in February 2023.
A Twitter personality with the identity Captain Faibik has confirmed a bullish breakout on FET, the native coin of the Fetch.ai network. He illustrated the trend using the daily chart, where the price displayed an upside breakout and retest. From his analysis, Faibik projected FET to rally to $0.9 from the current price level.
$FET Bullish Pennant Upside Breakout & Retest has Confirmed..!!Send it #Crypto #FET #FetchAI #FETUSDT pic.twitter.com/iEqn3LJ3jw— Captain Faibik (@CryptoFaibik) April 17, 2023
FET has trended sideways since reaching a yearly high of $0.6 in February 2023. The rally that pushed the FET price to $0.6 started at the beginning of the year, when FET traded around $0.09. By rallying to $0.6, FET gained over 580%, representing one of the most profitable cryptos in the market this year.
The FET price retraced and has remained in consolidation for the past 10 weeks, trading between $0.29 and $0.5, according to data from TradingView. In the process, the FET price developed one of the recognizable patterns in technical analysis, the Bullish Pennant.
By confirming the upside breakout of the Pennant, Faibik asked his followers to send the FET price higher. In other words, he issued a buy signal with an illustrated target of more than 100% gain from the price as of the time of the analysis.
FET is the native crypto of the Fetch.ai network, a blockchain platform that uses artificial intelligence to facilitate everyday tasks. It promotes the decentralization of transactions on the internet and executes tasks on behalf of users based on preset parameters.
Recently, Fetch.ai raised $40 million to support the development of tools that facilitate communication and actions among AI-powered tools. The network claimed the tools would focus on autonomous agents, networking equipment, and decentralized machine learning.
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