说明
线性梯度(或一般梯度)是微积分和线性代数中的一个基本概念,用于描述函数的方向和最快变化率。在这种情况下,金融市场采用的方法是定义在一定范围内波动性增加时的更大收益。我们知道在外汇市场中,价格变化是恒定的。为从外汇市场的这种不稳定性中获利,设计了一种解决方案。Gradient UMl pro 机器人特别适配了多种方法和过滤器,旨在最大化收益。该算法通过已实现的过滤器不断监控价格,以根据波动水平在目标范围内设置适应的挂单。机器学习功能根据市场进展进行监控和演变,通过根据价格走势调整止损和目标来降低风险。该算法的唯一缺点是强烈的趋势市场,这可能影响风险。然而,如果您了解市场周期并识别趋势结束、积累和分配期开始的时间,您可以通过连接这些时期来最大化算法的表现。
时间图表 m5 usdjpy,gbpusd,eurusd,已优化和配置,低风险时保持 adx 过滤器开启,关闭则开仓更多但风险更大。
预期结果
风格:混合剥头皮和波段交易
平均月收入:可变(根据条件从 2% 到 14%)
交易时间:在选定时间内活跃
为了更好的表现,请在每月1日至15日将参数 length 调整为 20。16日至30日,length = 12。length = 0 保持自动激进的机器学习模式,推荐用于区间市场。
摘要
AI 摘要
Gradiente Free Bots is an automated trading system designed for the Forex market, specifically optimized for the USDJPY, GBPUSD, and EURUSD currency pairs on the 5-minute (M5) timeframe. The system employs a hybrid scalping and swing trading style, leveraging a linear gradient approach to capitalize on price volatility within defined ranges. It uses multiple methods and filters to monitor price movements and place pending orders adapted to current market volatility.
The bot incorporates a machine learning function that continuously adjusts stop-loss and target levels based on evolving market conditions to manage risk. Users can enable an ADX filter to reduce risk by limiting trade openings, or disable it to increase position frequency with higher risk. Parameter adjustments are recommended monthly to optimize performance: setting the length parameter to 20 during the first half of the month and 12 during the second half, or using an automatic aggressive machine learning mode for range-bound markets.
Trading activity is active during selected times, with expected average monthly returns varying between 2% and 14%, depending on market conditions. The system is best suited for markets exhibiting cyclical behavior, where trend endings and accumulation/distribution phases can be identified to maximize effectiveness.
The bot incorporates a machine learning function that continuously adjusts stop-loss and target levels based on evolving market conditions to manage risk. Users can enable an ADX filter to reduce risk by limiting trade openings, or disable it to increase position frequency with higher risk. Parameter adjustments are recommended monthly to optimize performance: setting the length parameter to 20 during the first half of the month and 12 during the second half, or using an automatic aggressive machine learning mode for range-bound markets.
Trading activity is active during selected times, with expected average monthly returns varying between 2% and 14%, depending on market conditions. The system is best suited for markets exhibiting cyclical behavior, where trend endings and accumulation/distribution phases can be identified to maximize effectiveness.
交易概览
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价格
137
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16.05K
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