Market Overview for MultiversX/Tether (EGLDUSDT): 24-Hour Technical Summary
• Price declined from $10.15 to $9.76, breaking below $9.91 support before a late-day rebound.
• A key Bullish Engulfing pattern formed after the $9.85 test, signaling potential recovery.
• RSI overbought at 76 post-breakout, but failed to retrace to oversold, suggesting mixed momentum.
• Volatility expanded in the 12-hour window, with $10.08 becoming a psychological resistance.
• Volume surged 6x above average during the $9.91–$10.08 rebound, confirming strength in recovery.
Opening Narratives and 24-Hour Snapshot
MultiversX/Tether (EGLDUSDT) opened at $9.96 at 12:00 ET–1 and traded between $9.76 and $10.15 over the 24-hour period, closing at $9.8 at 12:00 ET. Total trading volume reached 132,398.98, with notional turnover of ~$1,300,000, showing moderate liquidity and active price movement across the day.
Structure & Formations
The price formed a key Bullish Engulfing pattern at $9.83–$9.85, confirming a potential short-term reversal after a test of the $9.91–$9.93 support zone. The $9.85 level appears to have acted as a pivot, with price rebounding from there. A Doji formed near $10.08 during the early morning, indicating indecision at the resistance zone. The $9.91 support appears critical, and any retest could offer a defined entry opportunity for short-term traders.
Moving Averages and Volatility
On the 15-minute chart, the 20-period and 50-period moving averages trended upward during the late-night rebound, suggesting accumulation pressure. The 20-period MA crossed above the 50-period at $9.92, indicating a possible short-term bullish bias. Bollinger Bands showed a modest expansion in the 12-hour window, with price breaking out to the upper band during the $10.06–$10.09 surge. The volatility contraction earlier in the day preceded the breakout, aligning with a classic pre-breakout pattern.
Momentum Indicators and Fibonacci Levels
RSI peaked at 76 during the late-night rally, signaling overbought conditions, but failed to trigger a meaningful pullback to oversold territory. This suggests ongoing buyer control, albeit with potential for consolidation. MACD showed positive divergence in the $9.85–$9.90 range, reinforcing the idea that the sell-off was losing steam.
Fibonacci retracements applied to the $9.76–$10.15 swing identified key levels such as $9.92 (38.2%), $9.85 (61.8%), and $9.80 (78.6%) as probable areas of interest. A bounce from 61.8% appears to have confirmed its role as a near-term pivot.
Volume and Turnover Signals
Volume spiked sharply during the $9.85–$10.08 rally, with the largest candle (10:30–11:45 PM ET) showing 2152.11 volume and $21,140 notional turnover, confirming strength in the rebound. A volume divergence was noted at the $9.76 low, where volume dropped despite the price test. This suggests weak conviction in the bearish move. The $9.85–$9.90 range saw consistent volume buildup, aligning with the RSI divergence and indicating strong accumulation.
Backtest Hypothesis
For a rules-based backtest on "buying at support-level breakouts and holding 14 calendar days," I recommend using Candle Close Above the 50-Period Low as the breakout signal. This rule is repeatable, data-driven, and can be implemented algorithmically by checking if a candle's close is higher than the lowest close over the past 50 days. A look-back window of 50 days provides enough historical context to avoid false signals from short-term noise.
To refine the strategy, I suggest including stop-loss at 5% below entry and a take-profit at 10% above entry, in addition to the fixed 14-day holding period. These risk controls help manage downside while still allowing the trade to play out over a defined time horizon.
Once the breakout signal is triggered (e.g., on the 15-minute or 1-hour chart), the strategy would open a position and exit 14 days later or upon hitting the stop-loss/take-profit. This approach allows the trader to capture both trend continuation and short-term volatility. The backtest could be implemented using a tool like PyAlgoTrade or Backtrader, and we can later evaluate key metrics such as win rate, Sharpe ratio, and maximum drawdown.



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