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Game Theory Trading Strategy

Game Theory Trading Strategy 结合了群体行为分析、流动性陷阱侦测、机构资金流和纳什均衡区间，用于反向与动量交易。

策略监控 RSI 极值和成交量激增以识别群体买入或卖出。近期高低点附近的流动性陷阱、AD 指标和「聪明资金」偏向共同优化进场。基于均线和标准差的价格带定义纳什均衡用于回归交易。当价格接近均衡或出现机构成交量时，仓位大小会自动调整。

细节

  • 数据: 价格与成交量 K 线。
  • 入场条件: 反向、动量或纳什回归信号。
  • 离场条件: 止损/止盈或相反信号。
  • 止损: 可选的止损和止盈。
  • 默认参数:
    • RsiLength = 14
    • VolumeMaLength = 20
    • HerdThreshold = 2.0
    • LiquidityLookback = 50
    • InstVolumeMultiplier = 2.5
    • InstMaLength = 21
    • NashPeriod = 100
    • NashDeviation = 0.02
    • UseStopLoss = True
    • StopLossPercent = 2
    • UseTakeProfit = True
    • TakeProfitPercent = 5
  • 过滤器:
    • 类型: 反向与动量混合
    • 方向: 多空皆可
    • 指标: RSI, SMA, Accumulation/Distribution, StandardDeviation, Highest/Lowest
    • 复杂度: 高级
    • 风险等级: 中等
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;

public class GameTheoryTradingStrategy : Strategy
{
	private readonly StrategyParam<int> _fastEmaPeriod;
	private readonly StrategyParam<int> _slowEmaPeriod;
	private readonly StrategyParam<DataType> _candleType;
	private decimal _prevFastEma;
	private decimal _prevSlowEma;

	public int FastEmaPeriod { get => _fastEmaPeriod.Value; set => _fastEmaPeriod.Value = value; }
	public int SlowEmaPeriod { get => _slowEmaPeriod.Value; set => _slowEmaPeriod.Value = value; }
	public DataType CandleType { get => _candleType.Value; set => _candleType.Value = value; }

	public GameTheoryTradingStrategy()
	{
		_fastEmaPeriod = Param(nameof(FastEmaPeriod), 120)
			.SetGreaterThanZero()
			.SetDisplay("Fast EMA", "Fast EMA period", "Indicators");
		_slowEmaPeriod = Param(nameof(SlowEmaPeriod), 450)
			.SetGreaterThanZero()
			.SetDisplay("Slow EMA", "Slow EMA period", "Indicators");
		_candleType = Param(nameof(CandleType), TimeSpan.FromMinutes(1).TimeFrame())
			.SetDisplay("Candle Type", "Type of candles to use", "General");
	}

	public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
	{
		return [(Security, CandleType)];
	}

	protected override void OnReseted()
	{
		base.OnReseted();
		_prevFastEma = 0m;
		_prevSlowEma = 0m;
	}

	protected override void OnStarted2(DateTime time)
	{
		base.OnStarted2(time);
		var fastEma = new ExponentialMovingAverage { Length = FastEmaPeriod };
		var slowEma = new ExponentialMovingAverage { Length = SlowEmaPeriod };
		var subscription = SubscribeCandles(CandleType);
		subscription.Bind(fastEma, slowEma, ProcessCandle).Start();
		var area = CreateChartArea();
		if (area != null)
		{
			DrawCandles(area, subscription);
			DrawIndicator(area, fastEma);
			DrawIndicator(area, slowEma);
			DrawOwnTrades(area);
		}
	}

	private void ProcessCandle(ICandleMessage candle, decimal fastEmaValue, decimal slowEmaValue)
	{
		if (candle.State != CandleStates.Finished) return;
		if (_prevFastEma == 0m || _prevSlowEma == 0m)
		{
			_prevFastEma = fastEmaValue;
			_prevSlowEma = slowEmaValue;
			return;
		}
		if (_prevFastEma <= _prevSlowEma && fastEmaValue > slowEmaValue && Position <= 0)
			BuyMarket();
		else if (_prevFastEma >= _prevSlowEma && fastEmaValue < slowEmaValue && Position >= 0)
			SellMarket();
		_prevFastEma = fastEmaValue;
		_prevSlowEma = slowEmaValue;
	}
}