Our quantitative trading strategy has just completed a full backtest, and the results are quite good. Here's a brief share of the core performance:
**Return Data** The cumulative return of this strategy reached 11,188.78% — compared to the benchmark return of 16.00%, the gap is quite obvious. The maximum drawdown is controlled at 11.32%, indicating that even in extreme market conditions, there was no significant plunge. A win rate of 68.78% means most trading days are profitable. The profit-to-loss ratio is 306.08%, which translates to the average profit when winning far exceeding the average loss when losing.
**Risk Management Indicators** An Alpha ratio of 100.00 indicates a strong ability to generate excess returns. A Beta ratio of 1.19 suggests the strategy is slightly more sensitive to market fluctuations than the average. The Sharpe ratio of 305.49 is quite high, reflecting a considerable return per unit of risk. The Sortino ratio of 451.12 further confirms the level of downside risk control.
**Trade Execution Details** The average daily trading volume is around 150 million (buying 149,573,856.00, selling -149,604,351.80), indicating sufficient liquidity and active trading frequency. The current position market value is close to 113 million, showing the strategy has substantial capital.
Overall, this strategy strikes a good balance between returns and risk control. If you're interested in this type of quantitative trading, the copy trading mode allows you to directly replicate the trading logic, ensuring stability. Friends with ideas can consider participating.
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DoomCanister
· 12-17 07:08
11,000% backtest data? Bro, you gotta see how it performs in real trading; theoretical data can be misleading.
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VitalikFanboy42
· 12-15 16:10
11,000% backtest performance? Wait, isn't that number from a bull market? Can this be reproduced in the current market?
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AirdropGrandpa
· 12-15 16:08
The backtest data looks quite impressive, but I don't know how it will perform once it's live.
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0xLuckbox
· 12-15 16:08
11,000% backtest performance? That said, while the backtest data looks impressive, it's already good if it can be reproduced in real market conditions.
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GasOptimizer
· 12-15 15:54
I don't believe in 11000% backtest data; overfitting historical data has been played out so many times...
#BinanceABCs $BTC $ETH $BNB
Our quantitative trading strategy has just completed a full backtest, and the results are quite good. Here's a brief share of the core performance:
**Return Data**
The cumulative return of this strategy reached 11,188.78% — compared to the benchmark return of 16.00%, the gap is quite obvious. The maximum drawdown is controlled at 11.32%, indicating that even in extreme market conditions, there was no significant plunge. A win rate of 68.78% means most trading days are profitable. The profit-to-loss ratio is 306.08%, which translates to the average profit when winning far exceeding the average loss when losing.
**Risk Management Indicators**
An Alpha ratio of 100.00 indicates a strong ability to generate excess returns. A Beta ratio of 1.19 suggests the strategy is slightly more sensitive to market fluctuations than the average. The Sharpe ratio of 305.49 is quite high, reflecting a considerable return per unit of risk. The Sortino ratio of 451.12 further confirms the level of downside risk control.
**Trade Execution Details**
The average daily trading volume is around 150 million (buying 149,573,856.00, selling -149,604,351.80), indicating sufficient liquidity and active trading frequency. The current position market value is close to 113 million, showing the strategy has substantial capital.
Overall, this strategy strikes a good balance between returns and risk control. If you're interested in this type of quantitative trading, the copy trading mode allows you to directly replicate the trading logic, ensuring stability. Friends with ideas can consider participating.