在 GitHub 上查看
Advanced EA Panel Strategy
该策略将 MQL5 的 Advanced EA Panel 手动交易面板移植到 StockSharp 平台。原始面板提供多周期指标、枢轴点、风险评估以及一键交易。现在所有计算都由 C# 策略自动完成,并通过日志与参数呈现,方便接入自动化流程或自建界面。
主要特性
- 同时订阅 9 个周期(M1 … MN1),跟踪 EMA(3/6/9)、SMA(50/200)、CCI(14)、RSI(21) 的方向性投票。
- 根据
PivotFormula 选择 Classic、Woodie 或 Camarilla 枢轴点公式,并在指定周期上重新计算。
- 通过 ATR 监控波动率,数值变化时在日志中输出最新读数。
- 维护风险面板:保存进场价、止损、止盈,并计算风险、收益距离以及 R/R 比例。
- 多周期投票超过
DirectionalThreshold 时可自动下单。若持有反向仓位,先调用 ClosePosition() 平仓,再发送新的市价单。
- 借助
StartProtection 创建随策略一起恢复的止损/止盈保护,忠实再现原面板的防护逻辑。
交易流程
- 每个周期的订阅通过
Bind 获取指标值。当收盘价高于所有均线、CCI>+100、RSI>60 时计入一个看涨票数;若条件反向则记为看跌票,其他情况不计分。
- 将所有已就绪周期的票数求和。结果 ≥
DirectionalThreshold 时生成买入信号,≤ -DirectionalThreshold 时生成卖出信号。
AutoTradingEnabled = true 时:
- 若当前持有反向仓位,先调用
ClosePosition() 退出。
- 之后按
Volume(四舍五入到 VolumeStep)发送市价单,并通过 StartProtection 挂出基于点差的止损/止盈。
- 主周期的 ATR 每次发生可识别的变化都会写入日志,便于监测波动率环境。
- 枢轴点在所选周期的 K 线收盘后重新计算,日志中给出 PP、R1–R4、S1–S4,可用于自定义面板或预警系统。
参数说明
| 名称 |
说明 |
分组 |
默认值 |
Volume |
交易手数,发送订单前会按 VolumeStep 调整。 |
Trading |
1.0 |
StopLossPips |
止损距离(价格步长数),设为 0 则不挂止损。 |
Risk |
50 |
TakeProfitPips |
止盈距离(价格步长数),设为 0 则不挂止盈。 |
Risk |
100 |
VolatilityPeriod |
ATR 计算周期。 |
Volatility |
14 |
PrimaryCandleType |
用于 ATR 和图表绘制的 K 线类型。 |
General |
15 分钟 |
PivotCandleType |
计算枢轴点时使用的 K 线类型。 |
General |
1 小时 |
DirectionalThreshold |
触发交易所需的绝对票数。 |
Signals |
3 |
AutoTradingEnabled |
是否自动执行信号。 |
Signals |
true |
PivotFormula |
枢轴点公式(Classic、Woodie、Camarilla)。 |
General |
Classic |
风险控制
StartProtection 把点差参数换算成绝对价格,并创建随策略维护的保护单。
_entryPrice、_stopPrice、_takePrice 在成交时更新,随后计算风险、收益及 R/R 比例并写入日志。
- 即便关闭自动交易,风险面板仍会跟踪外部或手动执行的仓位。
与 MQL5 版本的差异
- 不再绘制 UI 控件,所有结果通过日志与参数暴露;需要图形界面时可在 StockSharp 中自行订阅这些数据。
- 面板按钮 (
Buy, Sell, Reverse, Close) 改写为 RequestExecution、SendOrder、ClosePosition() 等方法,保持同样的执行顺序。
- 原有的 Points of Interest、文本编辑框、拖拽线条未迁移;改为在代码里重新计算枢轴点,必要时可以扩展成绘图逻辑。
- 波动率与风险指标不依赖图表对象,而是按需重新计算,因此重启后不会丢失。
使用建议
- 连接策略后确认数据源能提供
PanelTimeFrames 中列出的全部周期,否则信号生成会延迟。
- 调整
DirectionalThreshold 以匹配偏好的信号敏感度;阈值越大,越需要多周期一致才会触发。
- 将
AutoTradingEnabled 设为 false 时,可把策略当作信息面板使用,交易动作由其他系统完成。
- 代码默认绘制主周期的蜡烛、ATR 以及成交点,可按需要移除或扩展,以适应自定义可视化。
移植要点
- 操作映射:
EAPanelClickHandler 等回调映射为策略内部的下单与风控函数,复现买入、卖出、反手与平仓流程。
- 枢轴点公式:保留面板的预设组合(Classic/Woodie/Camarilla),便于与原策略对照。
- 指标替换:使用 StockSharp 的
ExponentialMovingAverage、SimpleMovingAverage、CommodityChannelIndex、RelativeStrengthIndex 处理多周期数据。
- 风险日志:原面板输入框显示的信息,现在全部写入日志,方便外部系统订阅。
借助这些改动,Advanced EA Panel 的市场洞察和操作流程被完整保留,同时具备 StockSharp 策略的自动化与可优化特性。
using System;
using System.Collections.Generic;
using Ecng.Common;
using StockSharp.Algo.Indicators;
using StockSharp.Algo.Strategies;
using StockSharp.BusinessEntities;
using StockSharp.Messages;
namespace StockSharp.Samples.Strategies;
/// <summary>
/// Advanced EA Panel strategy using EMA crossover.
/// Buys when fast EMA crosses above slow EMA, sells on reverse.
/// </summary>
public class AdvancedEaPanelStrategy : Strategy
{
private readonly StrategyParam<int> _fastPeriod;
private readonly StrategyParam<int> _slowPeriod;
private readonly StrategyParam<int> _stopLossPoints;
private readonly StrategyParam<int> _takeProfitPoints;
private ExponentialMovingAverage _fast;
private ExponentialMovingAverage _slow;
private decimal _prevFast;
private decimal _prevSlow;
private decimal _entryPrice;
private int _cooldown;
public int FastPeriod { get => _fastPeriod.Value; set => _fastPeriod.Value = value; }
public int SlowPeriod { get => _slowPeriod.Value; set => _slowPeriod.Value = value; }
public int StopLossPoints { get => _stopLossPoints.Value; set => _stopLossPoints.Value = value; }
public int TakeProfitPoints { get => _takeProfitPoints.Value; set => _takeProfitPoints.Value = value; }
public AdvancedEaPanelStrategy()
{
_fastPeriod = Param(nameof(FastPeriod), 14).SetGreaterThanZero().SetDisplay("Fast Period", "Fast EMA period", "Indicator");
_slowPeriod = Param(nameof(SlowPeriod), 50).SetGreaterThanZero().SetDisplay("Slow Period", "Slow EMA period", "Indicator");
_stopLossPoints = Param(nameof(StopLossPoints), 200).SetNotNegative().SetDisplay("Stop Loss", "Stop-loss in price steps", "Risk");
_takeProfitPoints = Param(nameof(TakeProfitPoints), 400).SetNotNegative().SetDisplay("Take Profit", "Take-profit in price steps", "Risk");
}
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
{
yield return (Security, TimeSpan.FromMinutes(5).TimeFrame());
}
protected override void OnReseted()
{
base.OnReseted();
_fast = null; _slow = null;
_prevFast = 0; _prevSlow = 0; _entryPrice = 0; _cooldown = 0;
}
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
_fast = new ExponentialMovingAverage { Length = FastPeriod };
_slow = new ExponentialMovingAverage { Length = SlowPeriod };
var subscription = SubscribeCandles(TimeSpan.FromMinutes(5).TimeFrame());
subscription.Bind(_fast, _slow, ProcessCandle);
subscription.Start();
}
private void ProcessCandle(ICandleMessage candle, decimal fastValue, decimal slowValue)
{
if (candle.State != CandleStates.Finished) return;
if (!_fast.IsFormed || !_slow.IsFormed) { _prevFast = fastValue; _prevSlow = slowValue; return; }
if (_cooldown > 0) { _cooldown--; _prevFast = fastValue; _prevSlow = slowValue; return; }
var close = candle.ClosePrice;
var step = Security?.PriceStep ?? 1m;
if (Position > 0 && _entryPrice > 0)
{
if (StopLossPoints > 0 && close <= _entryPrice - StopLossPoints * step) { SellMarket(); _entryPrice = 0; _cooldown = 100; _prevFast = fastValue; _prevSlow = slowValue; return; }
if (TakeProfitPoints > 0 && close >= _entryPrice + TakeProfitPoints * step) { SellMarket(); _entryPrice = 0; _cooldown = 100; _prevFast = fastValue; _prevSlow = slowValue; return; }
}
else if (Position < 0 && _entryPrice > 0)
{
if (StopLossPoints > 0 && close >= _entryPrice + StopLossPoints * step) { BuyMarket(); _entryPrice = 0; _cooldown = 100; _prevFast = fastValue; _prevSlow = slowValue; return; }
if (TakeProfitPoints > 0 && close <= _entryPrice - TakeProfitPoints * step) { BuyMarket(); _entryPrice = 0; _cooldown = 100; _prevFast = fastValue; _prevSlow = slowValue; return; }
}
if (_prevFast <= _prevSlow && fastValue > slowValue && Position <= 0)
{ if (Position < 0) BuyMarket(); BuyMarket(); _entryPrice = close; _cooldown = 100; }
else if (_prevFast >= _prevSlow && fastValue < slowValue && Position >= 0)
{ if (Position > 0) SellMarket(); SellMarket(); _entryPrice = close; _cooldown = 100; }
_prevFast = fastValue; _prevSlow = slowValue;
}
}
import clr
clr.AddReference("StockSharp.Messages")
clr.AddReference("StockSharp.Algo")
clr.AddReference("StockSharp.Algo.Indicators")
clr.AddReference("StockSharp.Algo.Strategies")
from System import TimeSpan
from StockSharp.Messages import DataType, CandleStates
from StockSharp.Algo.Indicators import ExponentialMovingAverage
from StockSharp.Algo.Strategies import Strategy
class advanced_ea_panel_strategy(Strategy):
def __init__(self):
super(advanced_ea_panel_strategy, self).__init__()
self._fast_period = self.Param("FastPeriod", 14) \
.SetDisplay("Fast Period", "Fast MA period", "Indicator")
self._slow_period = self.Param("SlowPeriod", 50) \
.SetDisplay("Slow Period", "Slow MA period", "Indicator")
self._stop_loss_points = self.Param("StopLossPoints", 200) \
.SetDisplay("Stop Loss", "Stop-loss in price steps", "Risk")
self._take_profit_points = self.Param("TakeProfitPoints", 400) \
.SetDisplay("Take Profit", "Take-profit in price steps", "Risk")
self._fast = None
self._slow = None
self._prev_fast = 0.0
self._prev_slow = 0.0
self._entry_price = 0.0
self._cooldown = 0
@property
def fast_period(self):
return self._fast_period.Value
@property
def slow_period(self):
return self._slow_period.Value
@property
def stop_loss_points(self):
return self._stop_loss_points.Value
@property
def take_profit_points(self):
return self._take_profit_points.Value
def OnReseted(self):
super(advanced_ea_panel_strategy, self).OnReseted()
self._fast = None
self._slow = None
self._prev_fast = 0.0
self._prev_slow = 0.0
self._entry_price = 0.0
self._cooldown = 0
def OnStarted2(self, time):
super(advanced_ea_panel_strategy, self).OnStarted2(time)
self._fast = ExponentialMovingAverage()
self._fast.Length = self.fast_period
self._slow = ExponentialMovingAverage()
self._slow.Length = self.slow_period
subscription = self.SubscribeCandles(DataType.TimeFrame(TimeSpan.FromMinutes(5)))
subscription.Bind(self._fast, self._slow, self._process_candle)
subscription.Start()
def _process_candle(self, candle, fast_value, slow_value):
if candle.State != CandleStates.Finished:
return
fast_val = float(fast_value)
slow_val = float(slow_value)
if not self._fast.IsFormed or not self._slow.IsFormed:
self._prev_fast = fast_val
self._prev_slow = slow_val
return
if self._cooldown > 0:
self._cooldown -= 1
self._prev_fast = fast_val
self._prev_slow = slow_val
return
close = float(candle.ClosePrice)
step = float(self.Security.PriceStep) if self.Security is not None and self.Security.PriceStep is not None else 1.0
if self.Position > 0 and self._entry_price > 0:
if self.stop_loss_points > 0 and close <= self._entry_price - self.stop_loss_points * step:
self.SellMarket()
self._entry_price = 0.0
self._cooldown = 100
self._prev_fast = fast_val
self._prev_slow = slow_val
return
if self.take_profit_points > 0 and close >= self._entry_price + self.take_profit_points * step:
self.SellMarket()
self._entry_price = 0.0
self._cooldown = 100
self._prev_fast = fast_val
self._prev_slow = slow_val
return
elif self.Position < 0 and self._entry_price > 0:
if self.stop_loss_points > 0 and close >= self._entry_price + self.stop_loss_points * step:
self.BuyMarket()
self._entry_price = 0.0
self._cooldown = 100
self._prev_fast = fast_val
self._prev_slow = slow_val
return
if self.take_profit_points > 0 and close <= self._entry_price - self.take_profit_points * step:
self.BuyMarket()
self._entry_price = 0.0
self._cooldown = 100
self._prev_fast = fast_val
self._prev_slow = slow_val
return
if self._prev_fast <= self._prev_slow and fast_val > slow_val and self.Position <= 0:
if self.Position < 0:
self.BuyMarket()
self.BuyMarket()
self._entry_price = close
self._cooldown = 100
elif self._prev_fast >= self._prev_slow and fast_val < slow_val and self.Position >= 0:
if self.Position > 0:
self.SellMarket()
self.SellMarket()
self._entry_price = close
self._cooldown = 100
self._prev_fast = fast_val
self._prev_slow = slow_val
def CreateClone(self):
return advanced_ea_panel_strategy()