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On NOV 5 2025,
rose by 4.85% within 24 hours to reach $197.15, AAVE dropped by 13.66% within 7 days, dropped by 13.66% within 1 month, and dropped by 36.13% within 1 year.AAVE’s protocol has demonstrated a consistent and robust financial model, with $98.3 million in fees and $12.6 million in revenue generated over the past month. The platform has maintained a Total Value Locked (TVL) of $35 billion, reinforcing its position as one of the most liquid and stable protocols in the decentralized finance (DeFi) sector. These fundamentals support a strong ecosystem narrative, especially as the Aave DAO has announced a $50 million annual token buyback program funded entirely by protocol profits.
The buyback program underscores the DAO’s commitment to token holder value, with the aim of reducing supply while reinforcing long-term sustainability. The move is seen as a strategic response to the token’s recent volatility and as a confidence-building measure amid broader market uncertainty. Analysts project that the initiative could help stabilize AAVE’s price by curbing selling pressure and reinforcing a more bullish sentiment among investors.
Technical indicators also suggest a potential floor for AAVE in the $150–$160 range, aligning with a key upward trendline that has held since 2023. If this level proves resilient, a reversal could send AAVE toward $240, with further upside seen to $341 in the near term. A break above $341 could trigger a rally toward $446–$538 by year-end. This technical setup, combined with ongoing institutional interest—particularly through Chainlink’s ACE integration—adds to the broader bullish case for AAVE.
Backtest Hypothesis
The strategic financial and technical alignment of Aave suggests a compelling case for a structured backtesting strategy that leverages historical price data. Using the available file aave_price_20220101_20251105.json, it’s possible to test a long-term position based on key technical levels and the buyback program’s implied value support. For the strategy to be effective, the backtest would need to define precise entry points based on the $150–$160 support range and a stop-loss at $130 to manage downside risk. Given that the backtesting engine is currently unable to source live prices for the ticker “AAVEUSD.UDC,” the most practical solution is to use the existing historical file directly. This would ensure a self-contained and accurate simulation of Aave’s price behavior without relying on external market feeds that may be inconsistent or unavailable. A successful backtest could offer empirical validation of the bullish case and serve as a foundation for more advanced trading models.
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