Since the last price prediction set on September 6 for Terra Classic (LUNC) to the end of this month, the machine learning algorithm has updated its projections for a more bearish scenario for this cryptocurrency’s holders.
As Terra Classic network continues to lose value in the crypto market, the new forecast gathered by Finbold on September 21 from PricePredictions.com algorithms, sets LUNC’s price at $0.000057 for the first day of October.
Notably, this new price prediction is 5% lower than what was set three weeks ago for one day earlier ($0.000060), evidencing the negative sentiment surrounding Terra Classic investors, technical analysis (TA) indicators, and other data used by this machine learning algorithm, which are foreseeing a bear market for the next 30 days.
However, things can change quickly according to future developments (or the lack of them), as they already have changed in the past for what was one of the most popular DeFi projects in the cryptocurrency market.
On April 5, 2022, Terra Classic (former Terra LUNA) had a market capitalization of $41 billion. Considering a circulating supply of around 5.82 trillion tokens, one LUNC would be worth close to $0.0070446 at this all-time high evaluation.
LUNC price analysis
Meanwhile, LUNC is trading at $0.00005708 by press time. With the monthly trend showing a similar conclusion to the current forecast, that suggests Terra Classic is already priced in for October 1.
Although the hypothetical surge of over 10,000% in comparison to the all-time high market cap and today’s price could sound appealing to Terra Classic’s holders, this dream could still be far away from reach, as LUNC has already dipped over 12% in price in the last 30 days from publication time, and shows even bigger accumulated losses in higher timeframes.
Disclaimer: The content on this site should not be considered investment advice. Investing is speculative. When investing, your capital is at risk.
The post Machine learning algorithm sets Terra Classic price for October 1, 2023 appeared first on Finbold.
