该策略是一个基于机构订单流的智能交易系统,通过识别市场中的订单区块(Order Blocks)来预测潜在的价格反转点。系统采用动态分仓管理方案,通过三层目标位来优化头寸管理,实现收益最大化。策略的核心在于捕捉机构交易行为所产生的价格痕迹,通过对高低点的统计分析来识别重要的价格水平。
策略基于以下几个关键要素: 1. 订单区块识别 - 利用20个周期的回溯窗口,通过分析蜡烛图形态识别买卖订单区块。买入区块在前一根看跌蜡烛和当前看涨蜡烛的配合下确认,卖出区块则相反。 2. 交易时间控制 - 将交易限制在09:30-16:00的主要交易时段内,避开波动性较大的开盘和收盘时段。 3. 入场逻辑 - 当价格突破买入订单区块且在交易时段内时开仓做多,突破卖出订单区块时开仓做空。 4. 分仓管理 - 采用50%-30%-20%的三层分仓方案,分别对应0.5%、1.0%和1.5%的目标位。
该策略通过机构订单流分析和动态分仓管理,构建了一个完整的交易系统。通过订单区块的识别和多层次止盈设置,既捕捉了大资金运作的机会,又实现了有效的风险控制。建议交易者在实盘中注意市场环境的选择,并根据具体情况调整参数设置。
/*backtest
start: 2019-12-23 08:00:00
end: 2024-12-25 08:00:00
period: 1d
basePeriod: 1d
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
//@version=6
strategy("Institutional Order Flow Strategy", overlay=true)
// Input settings
inputSession = input("0930-1600", "Trading Session") // Trading session
lookbackPeriod = input.int(20, "Order Block Lookback Period", minval=1) // Lookback for Order Blocks
target1Pct = input.float(0.5, "Target 1 (% move)", step=0.1, minval=0.1) // First profit target
target2Pct = input.float(1.0, "Target 2 (% move)", step=0.1, minval=0.1) // Second profit target
target3Pct = input.float(1.5, "Target 3 (% move)", step=0.1, minval=0.1) // Third profit target
// Order Block identification
highestHigh = ta.highest(high, lookbackPeriod)
lowestLow = ta.lowest(low, lookbackPeriod)
orderBlockBuy = ta.valuewhen(close[1] < open[1] and close > open, highestHigh, 0)
orderBlockSell = ta.valuewhen(close[1] > open[1] and close < open, lowestLow, 0)
// Entry logic
inSession = true
longCondition = close > orderBlockBuy and inSession
shortCondition = close < orderBlockSell and inSession
// Strategy entries
if longCondition
strategy.entry("Long", strategy.long)
if shortCondition
strategy.entry("Short", strategy.short)
// Calculate targets for scaling out
longTarget1 = strategy.position_avg_price + strategy.position_avg_price * target1Pct / 100
longTarget2 = strategy.position_avg_price + strategy.position_avg_price * target2Pct / 100
longTarget3 = strategy.position_avg_price + strategy.position_avg_price * target3Pct / 100
shortTarget1 = strategy.position_avg_price - strategy.position_avg_price * target1Pct / 100
shortTarget2 = strategy.position_avg_price - strategy.position_avg_price * target2Pct / 100
shortTarget3 = strategy.position_avg_price - strategy.position_avg_price * target3Pct / 100
// Exit logic with scaling out
if strategy.position_size > 0
strategy.exit("Target 1", from_entry="Long", limit=longTarget1, qty_percent=50)
strategy.exit("Target 2", from_entry="Long", limit=longTarget2, qty_percent=30)
strategy.exit("Target 3", from_entry="Long", limit=longTarget3, qty_percent=20)
if strategy.position_size < 0
strategy.exit("Target 1", from_entry="Short", limit=shortTarget1, qty_percent=50)
strategy.exit("Target 2", from_entry="Short", limit=shortTarget2, qty_percent=30)
strategy.exit("Target 3", from_entry="Short", limit=shortTarget3, qty_percent=20)
// Visualize Order Blocks
plot(orderBlockBuy, "Order Block Buy", color=color.green, linewidth=2, style=plot.style_line)
plot(orderBlockSell, "Order Block Sell", color=color.red, linewidth=2, style=plot.style_line)