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Fluctuate 策略
Fluctuate Strategy 是 MetaTrader 顾问 "Fluctuate" 的 StockSharp 版本。整套逻辑基于高层 API:通过 SubscribeCandles 监听蜡烛,使用 BuyMarket / SellMarket 完成入场,并通过止损单布置补仓订单。为了模拟 MetaTrader 的对冲账户,策略内部分别维护多头与空头敞口,而在 StockSharp 中显示的始终是净头寸。
核心思路
- 每根新蜡烛收盘时比较最近两根的收盘价。若当前收盘高于上一根,则市价买入;若更低,则市价卖出;相等时不操作。
- 每笔成交都会设置固定点数的止损与止盈,同时记录成交价以及该笔交易带来的新增手数。
- 成交后会在距离成交价
StepPips(再加一个极小的价差缓冲)的位置挂出反向止损单。其手数来源于上一笔成交和 LotCoefficient,在 MultiplyLotCoefficient = true 时则按总敞口计算。
- 当止损单被触发时,旧的挂单会被取消,内部敞口统计随之更新,并立刻在反方向放置新的补仓止损单,复现原 EA 的网格 / 马丁循环。
- 当价格朝有利方向至少运行
TrailingStopPips + TrailingStepPips 点时,保护性移动止损被激活,将止损紧跟在 TrailingStopPips 的距离之外,对应 MQL 版本的阶梯式 trailing stop。
工作流程
- 信号判定。 仅处理
CandleStates.Finished 的收盘数据,超出 [StartHour, EndHour) 的交易窗口或触及权益保护时暂停建仓。
- 初始仓位。
PositionSizingMode = FixedVolume 时使用固定手数;RiskPercent 模式下,按照权益的百分比风险除以止损产生的货币亏损来计算手数,点值与货币的换算依赖 PriceStep 与 StepPrice。
- 敞口跟踪。 分别维护多头与空头的手数、均价以及自建仓以来的最高/最低价,从而在净值账户中模拟对冲持仓。
- 补仓止损。 每次成交后重新计算下一张止损单的手数:
MultiplyLotCoefficient = false 时为 LastVolume × LotCoefficient;
true 时按当前总绝对敞口乘以 LotCoefficient;
- 手数会按交易所限制(步长/最小/最大)归一化,并在超过
MaxTotalVolume 或达到 MaxPositions(持仓方向数量 + 活动止损单)时被拒绝。
- 止盈与权益保护。 通过
PriceStep / StepPrice 把价差换算为货币,得到整体未实现盈亏;当达到 ProfitTarget 时,立即平掉所有仓位并取消挂单。若权益低于初始余额的 MinEquityPercent%,策略仅允许平仓,暂停新建仓。
- 移动止损。 多头记录入场后的最高价,若超过均价
TrailingStopPips + TrailingStepPips 点,则把止损上移到最高价减去 TrailingStopPips;空头逻辑对称。
风险控制
- 止损 / 止盈。 将相应点值设为
0 可关闭功能。新增仓位时会重新计算对应方向的整体水平。
- MaxPositions。 统计当前开启的方向(多/空各算 1)以及有效的补仓止损单,达到上限后不再提交新的止损单。
- MaxTotalVolume。 限制当前绝对持仓量与补仓订单手数之和。
- CloseAllAtStart。 启动策略前可选择性地平掉所有仓位并取消挂单。
参数
| 名称 |
说明 |
默认值 |
CandleType |
用于产生信号的主时间框架。 |
1 分钟 K 线 |
StopLossPips |
入场价到止损的距离(点)。0 表示关闭。 |
50 |
TakeProfitPips |
入场价到止盈的距离(点)。0 表示关闭。 |
50 |
TrailingStopPips |
移动止损的基础距离(点)。需与 TrailingStepPips 同时为正。 |
5 |
TrailingStepPips |
每次推进移动止损所需的额外盈利(点)。 |
5 |
StepPips |
最近一笔成交到反向补仓止损的距离(点)。 |
30 |
LotCoefficient |
补仓止损单的手数系数。 |
2.0 |
MultiplyLotCoefficient |
若为 true,对总敞口而非上一笔成交应用系数。 |
false |
MaxPositions |
同时允许的方向数量 + 活动止损单。 |
9 |
MaxTotalVolume |
绝对持仓量加补仓止损手数的上限。 |
50 |
ProfitTarget |
未实现利润(账户货币)达到该值时全部平仓。0 表示关闭。 |
50 |
MinEquityPercent |
权益低于初始余额百分比阈值时暂停建仓。 |
30 |
CloseAllAtStart |
启动时是否先清空仓位和挂单。 |
false |
StartHour |
交易窗口起始小时(含)。 |
10 |
EndHour |
交易窗口结束小时(不含)。 |
20 |
PositionSizingMode |
FixedVolume 为固定手数,RiskPercent 为按权益百分比。 |
FixedVolume |
VolumeOrRisk |
固定手数或风险百分比,取决于 PositionSizingMode。 |
1.0 |
实现细节
- 止损单价格额外加入最小价差(优先使用
PriceStep),以贴近 MetaTrader 对 freeze-level 的要求。
- 每次成交后,旧的补仓止损单都会被取消,与原 EA 的行为一致。
- 由于 StockSharp 账户为净额模式,对冲持仓通过内部变量模拟,实际提交给经纪商的是净手数。
RiskPercent 模式需要品种提供有效的 PriceStep 与 StepPrice。
使用建议
- 选择与原 EA 回测时间框架相匹配的
CandleType(常见为 M5 或 M15)。
- 确认交易所手数限制允许放置补仓单;若归一化后的手数为 0,策略将停止扩展网格。
- 在
RiskPercent 模式下务必保持投资组合权益数据最新,否则会退回到固定手数模式。
- 如需额外保护,可配合
StartProtection() 启用 StockSharp 内置的账户级风控。
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>
/// Fluctuate strategy using EMA crossover with stop-loss and take-profit.
/// Buys when fast EMA crosses above slow EMA, sells on reverse cross.
/// </summary>
public class FluctuateStrategy : 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;
/// <summary>
/// Fast EMA period.
/// </summary>
public int FastPeriod
{
get => _fastPeriod.Value;
set => _fastPeriod.Value = value;
}
/// <summary>
/// Slow EMA period.
/// </summary>
public int SlowPeriod
{
get => _slowPeriod.Value;
set => _slowPeriod.Value = value;
}
/// <summary>
/// Stop-loss distance in price steps.
/// </summary>
public int StopLossPoints
{
get => _stopLossPoints.Value;
set => _stopLossPoints.Value = value;
}
/// <summary>
/// Take-profit distance in price steps.
/// </summary>
public int TakeProfitPoints
{
get => _takeProfitPoints.Value;
set => _takeProfitPoints.Value = value;
}
/// <summary>
/// Initialize <see cref="FluctuateStrategy"/>.
/// </summary>
public FluctuateStrategy()
{
_fastPeriod = Param(nameof(FastPeriod), 50)
.SetGreaterThanZero()
.SetDisplay("Fast Period", "Fast EMA period", "Indicator");
_slowPeriod = Param(nameof(SlowPeriod), 200)
.SetGreaterThanZero()
.SetDisplay("Slow Period", "Slow EMA period", "Indicator");
_stopLossPoints = Param(nameof(StopLossPoints), 200)
.SetNotNegative()
.SetDisplay("Stop Loss", "Stop-loss distance in price steps", "Risk");
_takeProfitPoints = Param(nameof(TakeProfitPoints), 400)
.SetNotNegative()
.SetDisplay("Take Profit", "Take-profit distance in price steps", "Risk");
}
/// <inheritdoc />
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
{
yield return (Security, TimeSpan.FromMinutes(5).TimeFrame());
}
/// <inheritdoc />
protected override void OnReseted()
{
base.OnReseted();
_fast = null;
_slow = null;
_prevFast = 0;
_prevSlow = 0;
_entryPrice = 0;
_cooldown = 0;
}
/// <inheritdoc />
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;
// Check SL/TP
if (Position > 0 && _entryPrice > 0)
{
if (StopLossPoints > 0 && close <= _entryPrice - StopLossPoints * step)
{
SellMarket();
_entryPrice = 0;
_cooldown = 50;
_prevFast = fastValue;
_prevSlow = slowValue;
return;
}
if (TakeProfitPoints > 0 && close >= _entryPrice + TakeProfitPoints * step)
{
SellMarket();
_entryPrice = 0;
_cooldown = 50;
_prevFast = fastValue;
_prevSlow = slowValue;
return;
}
}
else if (Position < 0 && _entryPrice > 0)
{
if (StopLossPoints > 0 && close >= _entryPrice + StopLossPoints * step)
{
BuyMarket();
_entryPrice = 0;
_cooldown = 50;
_prevFast = fastValue;
_prevSlow = slowValue;
return;
}
if (TakeProfitPoints > 0 && close <= _entryPrice - TakeProfitPoints * step)
{
BuyMarket();
_entryPrice = 0;
_cooldown = 50;
_prevFast = fastValue;
_prevSlow = slowValue;
return;
}
}
// EMA crossover buy signal
if (_prevFast <= _prevSlow && fastValue > slowValue && Position <= 0)
{
if (Position < 0)
BuyMarket();
BuyMarket();
_entryPrice = close;
_cooldown = 50;
}
// EMA crossover sell signal
else if (_prevFast >= _prevSlow && fastValue < slowValue && Position >= 0)
{
if (Position > 0)
SellMarket();
SellMarket();
_entryPrice = close;
_cooldown = 50;
}
_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 fluctuate_strategy(Strategy):
def __init__(self):
super(fluctuate_strategy, self).__init__()
self._fast_period = self.Param("FastPeriod", 50) \
.SetDisplay("Fast Period", "Fast EMA period", "Indicator")
self._slow_period = self.Param("SlowPeriod", 200) \
.SetDisplay("Slow Period", "Slow EMA period", "Indicator")
self._stop_loss_points = self.Param("StopLossPoints", 200) \
.SetDisplay("Stop Loss", "Stop-loss distance in price steps", "Risk")
self._take_profit_points = self.Param("TakeProfitPoints", 400) \
.SetDisplay("Take Profit", "Take-profit distance 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(fluctuate_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(fluctuate_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
# Check SL/TP
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 = 50
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 = 50
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 = 50
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 = 50
self._prev_fast = fast_val
self._prev_slow = slow_val
return
# EMA crossover buy signal
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 = 50
# EMA crossover sell signal
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 = 50
self._prev_fast = fast_val
self._prev_slow = slow_val
def CreateClone(self):
return fluctuate_strategy()