MIRA -7297.23% in 1 Year Amid Market Turmoil

On OCT 11 2025, MIRA dropped by 87.14% within 24 hours to reach $0.329, MIRA dropped by 4549.81% within 7 days, dropped by 4584.7% within 1 month, and dropped by 7297.23% within 1 year.

The recent performance of MIRA has been marked by a sharp and unprecedented decline, drawing attention from both retail and institutional investors. The token, which once saw relatively stable market participation, has now experienced a dramatic downturn. Within a single 24-hour window, its value plummeted by nearly 87.14%. This rapid depreciation continued over the following weeks and months, with cumulative losses reaching 4549.81% in seven days and 4584.7% in one month. Over the span of a year, the price erosion has reached 7297.23%, indicating a near-complete loss of value compared to its historical high.

The technical indicators used to analyze MIRA’s price movements have largely confirmed the depth of the correction. A prolonged bearish trend has been reflected in key charting tools, with MIRA failing to hold critical support levels. A consistent lack of buying pressure has led to a widening divergence in momentum indicators, further reinforcing the bearish sentiment. These readings have been corroborated by the price action itself, which has shown little to no sign of reversal over the past several months.

Analysts have noted that the market behavior surrounding MIRA appears to be indicative of a structural decline, rather than a short-term correction. Several factors have been cited as contributing to this shift, including reduced liquidity, lack of strategic development updates, and broader market conditions that have led to a reevaluation of speculative assets. No major institutional or developer activity has been reported to counteract the downward spiral.

Backtest Hypothesis

The backtesting strategy proposed aims to model potential trade outcomes based on the technical indicators used in the above analysis. This approach involves simulating a position that would have been triggered at key inflection points, with stop-loss and take-profit levels aligned with the identified support and resistance levels. The hypothesis tests whether early exits at these levels would have mitigated the overall losses experienced by investors.

The strategy relies on a combination of moving averages and momentum oscillators to identify potential turning points. A cross of short-term and long-term moving averages is used to signal potential exits, while overbought or oversold conditions in the oscillator are used to time the trades. Historical data is applied to the model to evaluate the strategy’s effectiveness in curbing losses.