Ethereum/Dai Market Overview

• Price surged to a 24-hour high of 4,215.77 before pulling back, ending near 4,082.62 at 12:00 ET.
• Strong bullish momentum emerged in the early morning, followed by a sharp reversal in the afternoon.
• Volume spiked during key breakouts but trailed off during consolidation phases.
• RSI signaled overbought conditions in the morning, later moving into neutral territory.
• Bollinger Bands showed a volatile expansion early, then narrowed during the midday decline.

Ethereum/Dai (ETHDAI) opened at 4,001.30 on 2025-10-12 at 12:00 ET, surged to a high of 4,215.77, and closed at 4,082.62 at 12:00 ET on 2025-10-13. Total volume reached 152.92 ETH, while turnover amounted to 636,919.57 DAI. Price action displayed strong bullish momentum early, followed by a reversal, indicating a mixed sentiment.

Structure & Formations

The 15-minute chart showed several key turning points, including a strong bullish engulfing pattern between 19:15 and 19:30 ET as price surged from 4,111.35 to 4,130.42. A morning high near 4,215.77 was followed by a bearish reversal pattern, with a long upper shadow on the 10:15 ET candle. Key support levels appeared at 4,100 and 4,050, while resistance held near 4,200. A morning session high at 4,215.77 acted as a psychological ceiling, with price struggling to reclaim that level after a sharp sell-off in the afternoon.

Moving Averages

On the 15-minute chart, the 20-period moving average crossed above the 50-period line early in the morning, suggesting a bullish bias. However, the 50-period line remained above price by the afternoon, signaling a bearish shift. On the daily chart, the 50-period moving average hovered just below the 100-period line, with no clear directional bias. The 200-period MA served as a key psychological floor near 4,050, which held through much of the afternoon.

MACD & RSI

The MACD line showed a strong bullish crossover in the morning, with the histogram expanding rapidly as price surged above 4,200. However, by midday, the histogram collapsed, and the MACD line crossed below the signal line, signaling a bearish reversal. The RSI peaked near 75 in the morning, suggesting overbought conditions, and fell below 50 by 12:00 ET. This confirmed the afternoon sell-off and indicated that short-term momentum had shifted.

Bollinger Bands

Volatility expanded sharply during the morning rally, with price reaching the upper band near 4,215.77. This signaled a high-risk environment and potential overbought conditions. In the afternoon, volatility contracted, with price trading near the middle band and a narrowing range, suggesting indecision. A break below the lower band at 4,050 would likely trigger further downward momentum, testing key Fibonacci levels.

Volume & Turnover

Volume spiked during the morning breakout and again during the afternoon sell-off, with the largest single 15-minute volume occurring around 10:15 ET. Turnover was concentrated in the 10:15–10:45 ET period, with a total of 43.3276 ETH traded in a single candle. The divergence between price and volume during the final hour suggested weakening momentum, with smaller candles and lower participation in the downward move.

Fibonacci Retracements

Applying Fibonacci levels to the morning high of 4,215.77 and the afternoon low of 4,050, the 38.2% retracement level is at 4,153.21, which held briefly in the midday session. The 61.8% retracement level is at 4,095.34, which may serve as the next key support level if the downward move continues. A failure to hold above this level could indicate a deeper correction into the 4,050 zone.

Backtest Hypothesis

The backtest strategy hinges on identifying precise price series for the ETH-to-DAI pair. The OHLCV data provided aligns with the structure expected for the symbol ETHDAI, but the backtesting engine requires confirmation of the exact ticker code used by the data vendor. Among the suggested codes, ETHDAI appears to be the correct identifier given the context and format of the input data. Once confirmed, the strategy can be re-run with the correct price source, leveraging the current technical framework (e.g., RSI, MACD, Fibonacci retracements) for predictive modeling. This will allow for a more accurate assessment of the pair's behavior under similar conditions.