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Grid 再平衡策略
Grid 再平衡策略是基于 StockSharp 高级 API 重写的 Mission Automate「Grid」专家顾问。策略在多头与空头网格之间交替运行,并始终在当前方向上维持阶梯式限价单。当组合仓位触及统一的止盈价位后,策略会平掉全部仓位、取消所有挂单,并以相反方向开始下一轮循环。
工作流程
- 开启循环:当没有持仓也没有挂单时,策略按照
FirstTradeSide 指定的方向,用 StartVolume 手开立市价仓位。
- 铺设网格:每次在当前方向成交后,会在距离
GridStepPoints(通过品种的 PriceStep 转换为绝对价格)的价位重新挂出一个限价单。新订单的手数等于最近一次成交手数乘以 LotMultiplier。
- 基于均价的止盈:每次加仓后都会重新计算加权平均持仓价格。整体止盈价设置为平均价加/减
TargetPoints(同样通过 PriceStep 转换)。策略使用 K 线的最高价和最低价来模拟服务器端触发逻辑。
- 结束循环:当价格触及止盈位时,策略用市价单平掉全部仓位,撤销剩余挂单,记录本次循环的方向,并在下一轮采用相反方向。
参数说明
FirstTradeSide:首个循环的方向(Buy 或 Sell),每完成一轮会自动切换方向。
StartVolume:每个循环首单的市价手数。
LotMultiplier:为下一层网格计算手数时使用的乘数,大于 1 时形成类似马丁格尔的加仓。
GridStepPoints:网格层之间的距离(点数),通过 Security.PriceStep 转换成实际价格间隔。
TargetPoints:止盈距离(点数),相对于持仓加权平均价计算。
CandleType:用于监控高低点、判定止盈触发的 K 线类型。
风控与实现细节
- 策略没有设置硬性止损,行情逆行时会持续加仓。
- 任意时刻只会保持一个挂单,成交后立即安排下一层网格。
- 只有在没有持仓、没有挂单且品种提供了有效
PriceStep 时才会启动新的循环。
- 所有计算都在策略内部完成,没有使用全局集合或指标缓冲区,符合项目规范。
- 循环结束时会统一撤销挂单,避免遗留旧订单。
其他说明
- 所有以点数表示的参数都会乘以
Security.PriceStep 转换成价格;若价格步长未知,策略会等待交易所提供数据。
- 实现完全依赖高层 API(
SubscribeCandles、Bind、BuyMarket、SellMarket、BuyLimit、SellLimit)。
- 本任务按要求不提供 Python 版本。
using System;
using Ecng.Common;
using StockSharp.Algo.Indicators;
using StockSharp.Algo.Strategies;
using StockSharp.BusinessEntities;
using StockSharp.Messages;
namespace StockSharp.Samples.Strategies;
/// <summary>
/// Grid Rebalance strategy: RSI + EMA crossover-based.
/// Buys when close crosses above EMA with RSI confirmation.
/// Sells when close crosses below EMA with RSI confirmation.
/// </summary>
public class GridRebalanceStrategy : Strategy
{
private readonly StrategyParam<DataType> _candleType;
private readonly StrategyParam<int> _rsiPeriod;
private readonly StrategyParam<int> _emaPeriod;
public DataType CandleType
{
get => _candleType.Value;
set => _candleType.Value = value;
}
public int RsiPeriod
{
get => _rsiPeriod.Value;
set => _rsiPeriod.Value = value;
}
public int EmaPeriod
{
get => _emaPeriod.Value;
set => _emaPeriod.Value = value;
}
public GridRebalanceStrategy()
{
_candleType = Param(nameof(CandleType), TimeSpan.FromMinutes(30).TimeFrame())
.SetDisplay("Candle Type", "Candle timeframe", "General");
_rsiPeriod = Param(nameof(RsiPeriod), 14)
.SetGreaterThanZero()
.SetDisplay("RSI Period", "RSI period", "Indicators");
_emaPeriod = Param(nameof(EmaPeriod), 20)
.SetGreaterThanZero()
.SetDisplay("EMA Period", "EMA period", "Indicators");
}
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
var rsi = new RelativeStrengthIndex { Length = RsiPeriod };
var ema = new ExponentialMovingAverage { Length = EmaPeriod };
decimal? prevClose = null;
decimal? prevEma = null;
var subscription = SubscribeCandles(CandleType);
subscription
.Bind(rsi, ema, (candle, rsiVal, emaVal) =>
{
if (candle.State != CandleStates.Finished)
return;
if (!IsFormedAndOnlineAndAllowTrading())
return;
var close = candle.ClosePrice;
if (prevClose.HasValue && prevEma.HasValue)
{
var crossUp = prevClose.Value <= prevEma.Value && close > emaVal;
var crossDown = prevClose.Value >= prevEma.Value && close < emaVal;
if (crossUp && rsiVal < 55m && Position <= 0)
BuyMarket();
else if (crossDown && rsiVal > 45m && Position >= 0)
SellMarket();
}
prevClose = close;
prevEma = emaVal;
})
.Start();
var area = CreateChartArea();
if (area != null)
{
DrawCandles(area, subscription);
DrawIndicator(area, ema);
DrawOwnTrades(area);
}
}
}
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 RelativeStrengthIndex, ExponentialMovingAverage
from StockSharp.Algo.Strategies import Strategy
class grid_rebalance_strategy(Strategy):
"""
Grid Rebalance: RSI + EMA crossover strategy.
Buys when close crosses above EMA with RSI < 55.
Sells when close crosses below EMA with RSI > 45.
"""
def __init__(self):
super(grid_rebalance_strategy, self).__init__()
self._rsi_period = self.Param("RsiPeriod", 14) \
.SetDisplay("RSI Period", "RSI period", "Indicators")
self._ema_period = self.Param("EmaPeriod", 20) \
.SetDisplay("EMA Period", "EMA period", "Indicators")
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromMinutes(30))) \
.SetDisplay("Candle Type", "Candle timeframe", "General")
self._prev_close = None
self._prev_ema = None
@property
def candle_type(self):
return self._candle_type.Value
def OnReseted(self):
super(grid_rebalance_strategy, self).OnReseted()
self._prev_close = None
self._prev_ema = None
def OnStarted2(self, time):
super(grid_rebalance_strategy, self).OnStarted2(time)
rsi = RelativeStrengthIndex()
rsi.Length = self._rsi_period.Value
ema = ExponentialMovingAverage()
ema.Length = self._ema_period.Value
subscription = self.SubscribeCandles(self.candle_type)
subscription.Bind(rsi, ema, self._process_candle).Start()
area = self.CreateChartArea()
if area is not None:
self.DrawCandles(area, subscription)
self.DrawIndicator(area, ema)
self.DrawOwnTrades(area)
def _process_candle(self, candle, rsi_val, ema_val):
if candle.State != CandleStates.Finished:
return
close = float(candle.ClosePrice)
rsi = float(rsi_val)
ema = float(ema_val)
if self._prev_close is not None and self._prev_ema is not None:
cross_up = self._prev_close <= self._prev_ema and close > ema
cross_down = self._prev_close >= self._prev_ema and close < ema
if cross_up and rsi < 55.0 and self.Position <= 0:
self.BuyMarket()
elif cross_down and rsi > 45.0 and self.Position >= 0:
self.SellMarket()
self._prev_close = close
self._prev_ema = ema
def CreateClone(self):
return grid_rebalance_strategy()