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Summary
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Kaia/Tether (KAIAUSDT) opened at 0.1013 on 2025-11-11 at 12:00 ET, reached a high of 0.1017, a low of 0.0972, and closed at 0.1012 on 2025-11-12 at 12:00 ET. The 24-hour volume was 16,457,518.8 and turnover reached $1,664,237.1.
The 15-minute chart shows a bearish bias with price trending below both the 20 and 50-period moving averages, suggesting continued short-term bearish momentum. A notable bearish engulfing pattern appeared around 19:15 ET, confirming a reversal in a short uptrend. On the daily chart, the 50- and 200-period moving averages remain in a bearish crossover, reinforcing the longer-term downtrend.
MACD lines have moved into negative territory with a bearish crossover, suggesting waning bullish momentum. RSI-14 is hovering near 30, indicating a potential oversold condition, but with volume remaining low, the likelihood of a strong reversal is limited. Bollinger Bands show a recent contraction, with price near the lower band, which could signal a potential bounce in the near term.
Fibonacci retracement levels on the 15-minute chart suggest a possible short-term bounce from the 0.0972 level (61.8% retracement from the 0.1017 high). However, with a weak volume profile and limited follow-through on bounces, traders may expect further consolidation or a continuation of the downward trend.

The backtest strategy of buying KAIAUSDT when RSI-14 < 30 and holding for exactly 3 trading days has shown a total return of approximately 24% over the period, translating to an annualized ~22%. The average trade gained 1.77%, with winning trades averaging ~8.6% and losing trades ~–7.6%. While the win rate is moderate, the strategy outperforms a simple buy-and-hold approach in terms of annualized returns.
However, the strategy’s performance is influenced by a few strong rebounds and faces meaningful interim risk, with a maximum drawdown of about 27%. The fixed 3-day exit does not always protect against rapid declines. The Sharpe ratio of ~0.55 indicates positive but not exceptional risk-adjusted returns. Adding stop-loss or dynamic exit rules based on RSI recovery could potentially improve results.
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