As of October 25, 2025,
YFI’s latest trajectory mirrors the general market environment, where extended downturns are frequently linked to overarching issues like economic pressures or regulatory changes. The lack of immediate positive news—such as significant strategic moves or encouraging economic indicators—has contributed to investor wariness. The pronounced decline over the past month, which has intensified since the beginning of October, points to heightened selling activity and waning confidence. Although the 24-hour loss is relatively minor, it may be a sign that the overall downward pattern is likely to persist rather than reverse.
Several technical signals currently support the ongoing bearish sentiment. Short-term moving averages remain below their longer-term counterparts, indicating continued downward pressure. The Relative Strength Index (RSI) has fallen into oversold levels, which could suggest a short-lived rebound. However, this indicator alone does not guarantee a turnaround, as oversold conditions in volatile assets can last for some time without a recovery. The MACD has also shifted into negative territory, further confirming the pessimistic outlook.
Backtest Hypothesis
Considering the recent price action and technical signals, a backtest is being planned to explore the potential for either a mean-reversion or trend-following approach based on YFI’s price behavior. The backtest will investigate whether days with a 10% or greater drop from the previous close (termed “-10% down-days”) typically lead to a rebound or continued losses. By analyzing how prices behave after such significant declines, the strategy aims to uncover any repeatable patterns that could inform present trading tactics.
To carry out this backtest, detailed historical price records are necessary. The specific ticker and trading platform for YFI must be confirmed—options include “YFI-USD” or “YFIUSDT” on leading exchanges like Coinbase, Binance, or Kraken. The analysis will cover daily price movements from January 1, 2022, up to now, focusing on identifying down-days and tracking subsequent performance over various periods (such as 3, 7, and 14 days). The findings will feature graphical representations of price reactions to down-days and statistical breakdowns of average and median results.