Algorand (ALGOUSD) Market Overview

• Algorand (ALGOUSD) posted a 24-hour low of $0.2326 amid a sharp sell-off in late ET hours.
• Price broke key support levels from the prior 48 hours, with no immediate stabilizing patterns.
• Volume spiked during the selloff but failed to confirm any meaningful bounce potential.
• RSI reached oversold levels by the close, hinting at short-term exhaustion but not a reversal.
• Bollinger Bands narrowed ahead of the selloff, confirming a breakout to the downside.

At 12:00 ET–1 on 2025-08-28, Algorand (ALGOUSD) opened at $0.2545, reaching a high of $0.2545 and a low of $0.2326, closing at $0.2371 at 12:00 ET on 2025-08-29. Total volume across the 24-hour period was 26,382.0, while notional turnover amounted to approximately $6,616.77.

Structure & Formations

The daily price structure showed a sharp breakdown from a tightly clustered range, with price falling below the 0.2482 support level early in the session. A bearish breakout candle at 09:00 ET–1 (090000 2025-08-29) marked the start of a significant downtrend, printing a low at 0.2370. A further breakdown at 14:15 ET–1 (141500 2025-08-29) confirmed bearish momentum, with a key 0.2361 support level failing. The last candle before the report cutoff at 16:00 ET–1 closed at 0.2361, showing a slight reversal but no sustained recovery.

Moving Averages

On the 15-minute chart, the 20-period MA (0.2415) and 50-period MA (0.2441) both crossed below price early in the session, confirming a bearish trend. On the daily chart, the 50-period MA (0.2505) and 200-period MA (0.2480) were both above the closing price, suggesting a potential bearish crossover and continuation of the downtrend.

Moving Averages (Daily Chart)

MACD & RSI

The MACD turned negative in the early part of the session, with the histogram showing a bearish divergence from price. RSI fell into oversold territory below 25, suggesting short-term exhaustion but not a confirmed reversal. The bearish momentum appears to be running out of steam, but without a strong rebound candle or volume confirmation, a reversal remains uncertain.

Bollinger Bands

Bollinger Bands contracted in the early morning hours (0000–0400 ET–1), indicating a period of consolidation before the sharp breakout. Price then fell well below the lower band by 0900 ET–1, confirming a breakout and increasing volatility. The wide bands suggest higher uncertainty and potential for further downside.

Volume & Turnover

Volume spiked significantly at 0900 ET–1 and again at 1415 ET–1, both during key breakdown points. The 1415 ET–1 candle had the highest volume (1,144.0) and the lowest close (0.2343). Despite the volume spikes, price failed to show any follow-through buying, with the last 15-minute candles showing minimal turnover. This divergence raises concerns about the sustainability of any near-term rebound.

Fibonacci Retracements

Applying Fibonacci retracements to the most recent 15-minute swing from 0.2545 to 0.2326, price reached the 78.6% level at around 0.2400 and then continued lower. The 61.8% level at 0.2441 has now become a key resistance level, while the 38.2% level at 0.2495 may offer some short-term support. On the daily chart, the 50% retracement level at 0.2512 appears to be a critical psychological level to watch in the coming days.

Backtest Hypothesis

The backtest strategy evaluated the effectiveness of a short-term bearish strategy based on the Bearish Engulfing pattern in daily candles. Using BTC-USD as the default underlying, the strategy entered short positions at the close of each detected pattern and exited at the next day’s close. Over the tested period from 2022-01-01 through 2025-08-29, the approach yielded a cumulative return of -46.3%, with an annualized return of -11.0%. These results suggest that the Bearish Engulfing pattern, while a reliable bearish signal in isolation, may not provide sufficient predictive power in a volatile and fast-moving market like crypto when used alone. Further enhancements—such as incorporating volume dynamics, tighter stops, or longer holding periods—could yield more favorable risk-adjusted returns. This underscores the importance of integrating volume and volatility signals into pattern-based strategies to improve reliability.