Bitcoin (BTC) Analysis: Understanding the Hurdles to $70,000

Monday, 7 October 2024, 11:00

Bitcoin (BTC) analysis indicates that reaching the $70,000 mark may be challenging. Despite a recent price surge, key indicators highlight significant hurdles ahead, warranting caution among investors. This article delves into crucial market signals and what they mean for Bitcoin’s trajectory this month.
Beincrypto
Bitcoin (BTC) Analysis: Understanding the Hurdles to $70,000

On-Chain Metrics Flash Warning Signs for Bitcoin

One key metric supporting a Bitcoin price retracement is the Network Value to Transactions (NVT) ratio. The NVT ratio shows if the market cap is growing faster than a cryptocurrency's transaction volume.

When the NVT ratio decreases, transaction volume is growing higher than the market cap. In most cases, this is bullish for price. Conversely, a rising NVT ratio indicates that the Bitcoin network is overvalued as the market cap outpaces volume.

Current NVT Analysis

As of this writing, Glassnode data shows that the ratio has increased recently, suggesting potential overvaluation and a possible short-term price correction for Bitcoin.

Bitcoin Price Prediction: Margins for Decline Below $60,000

Currently, Bitcoin's price stands at $62,856. However, the Money Flow Index (MFI) indicates a decrease in capital inflow into the cryptocurrency.

The MFI uses price and volume to gauge buying and selling pressure. An increased MFI typically signals more liquidity flowing into the market, supporting potential price increases.

Since MFI’s reading has dropped, it suggests that investors are cashing out on recent gains, which could pause Bitcoin's price rise. If this trend continues, BTC's price might drop to around $59,978.

Nevertheless, if investors shift from selling to accumulating, Bitcoin could rally toward $66,527 and possibly toward the $70,000 target.


This article was prepared using information from open sources in accordance with the principles of Ethical Policy. The editorial team is not responsible for absolute accuracy, as it relies on data from the sources referenced.


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