Bitcoin's volatility has surged beyond the levels observed on the day of its all-time high in March, which may indicate a potential end to its extended consolidation phase. This heightened volatility is seen as a possible precursor to a significant price movement for Bitcoin.
As of August 21, Bitcoin's Historical Volatility chart showed a level of 3.42%, surpassing the 3.00% recorded on March 13, when Bitcoin reached its peak price. The highest volatility of 2024 was observed on March 26, reaching 4.28%. Increased volatility suggests that Bitcoin’s price might experience substantial fluctuations, although it does not inherently signal a bullish trend.
Traders have highlighted the importance of Bitcoin (BTC) maintaining its position above $61,000 and successfully retesting the $62,000 mark, a level it has not reached since August 9. Pseudonymous crypto trader Daan Crypto Trades noted that the current rise in volatility is approaching levels seen earlier in the year, which could be crucial for ending the ongoing consolidation phase.
Despite the current volatility not being a bullish signal by itself, it could attract increased trader interest and present more opportunities for trading based on Bitcoin’s price movements. However, it also carries the risk of significant price swings in either direction.
According to historical data, September has a high probability of marking cycle lows based on past trends. Bitcoin has been consolidating within a range from approximately $49,842 to $72,000 since the April 20 halving.
The put-to-call volume ratio, which measures the demand for put versus call options, currently stands at 66.18% calls and 33.82% puts, resulting in a put-to-call ratio of 0.51. This ratio reflects a generally bullish sentiment among future traders.
At the time of this report, Bitcoin was trading around $60,875. It attempted to breach the $62,000 level but fell short, reaching a high of $61,552. Trader Matthew Hyland pointed out that Bitcoin is “testing the neckline,” a trading pattern used to confirm support levels by analyzing high points within a specified period.