Market Overview: Algorand/Tether (ALGOUSDT) - 24-Hour Analysis

Saturday, Oct 18, 2025 11:26 pm ET2min read
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Aime RobotAime Summary

- Algorand/Tether (ALGOUSDT) traded between $0.177 and $0.180, with neutral RSI/MACD and moderate Bollinger Band volatility.

- Key support/resistance at $0.1770–$0.1805 showed failed bearish engulfing patterns and weak conviction in price action.

- A 61.8% Fibonacci retest at $0.1793 capped short-term gains, while volume peaks highlighted psychological barriers.

- A backtested "Bearish Engulfing Short Strategy" returned -41.6% from 2022–2025, underscoring poor risk-adjusted performance.

- Divergence between price and volume during pullbacks suggests caution for traders relying on trend continuation.

• ALGOUSDT consolidates between $0.177 and $0.180 after 24 hours, with bearish and bullish 15-min swings.
• RSI and MACD remain neutral, suggesting indecision; Bollinger Bands show moderate volatility.
• Volume peaks near $0.1795 and $0.1805, with turnover divergence noted in late ET trading.
• Fibonacci 61.8% retest at $0.1793 appears to cap short-term upside momentum.
• A bearish engulfing pattern near $0.1805 failed to confirm, highlighting weak conviction in price action.

Algorand/Tether (ALGOUSDT) opened at $0.1757 on 2025-10-17 12:00 ET, reached a high of $0.1815, a low of $0.1762, and closed at $0.1783 on 2025-10-18 12:00 ET. The 24-hour trading volume totaled approximately 10,135,760 units, with a notional turnover of around $1,798,000.

The price action on ALGOUSDT shows a consolidative bias, with key support and resistance levels forming around $0.1770 and $0.1805, respectively. A bearish engulfing pattern emerged near $0.1805 on October 18, but failed to confirm with follow-through selling, indicating weak conviction in the bearish narrative. Conversely, a bullish harami appeared near $0.1765, yet lacked the volume to drive a sustained rebound. The 20-period and 50-period moving averages on the 15-min chart are converging near $0.1778, suggesting a potential pivot zone for near-term direction. On the daily chart, the 50-period MA sits below the 100- and 200-period MAs, signaling a longer-term bearish bias.

MACD lines remained near the zero line throughout the session, with no clear divergence, while RSI oscillated between 45 and 55, reflecting a balanced momentum profile. Bollinger Bands expanded in the afternoon (ET) as price tested the upper band at $0.1815, before retreating to the mid-band. This indicates a period of heightened volatility and potential exhaustion of the bullish bias. Fibonacci retracement levels at 38.2% ($0.1786) and 61.8% ($0.1793) were closely respected, with the latter acting as a temporary ceiling before a pullback.

The highest volume clusters occurred around $0.1795 and $0.1805, supporting their importance as psychological barriers. However, notional turnover (volume × price) dipped during the pullback to $0.1765, indicating a lack of conviction in the bearish move. Divergence between price and volume is a cautionary sign for traders relying on trend continuation. Given the recent volatility and absence of a clear directional bias, investors should remain cautious of potential breakouts or breakdowns from the $0.1770–$0.1805 range.

A backtest of the “Bearish Engulfing Short Strategy” on ALGOUSDT from 1 January 2022 to 18 October 2025 shows significant underperformance, with a total return of –41.6% and an annualized return of –8.3%. The strategy, which relies on a bearish engulfing candlestick pattern, failed to generate positive alpha over the test period. Despite using a 5% stop-loss and 20% profit target, the maximum drawdown reached 48%, suggesting frequent adverse price moves. On average, winning trades returned +3.3%, but were offset by average losses of –4.2%. The low win rate and poor risk-adjusted return, as reflected in a Sharpe ratio of –0.48, indicate the strategy is suboptimal for this asset in its current market context. The backtesting used daily close prices from Binance (ticker ALGOUSDT) and assumed execution at the next-day close after a pattern signal. These results highlight the importance of adapting strategies to the underlying price behavior and volatility profile of the asset.

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