Yeong RRG
Стратегия на основе нормализованного относительной силы и темпа (RRG).
Входит в лонг, когда JDK RS и JDK RoC выше 100, и выходит, когда оба опускаются ниже 100.
Детали
- Условия входа: JDK RS и JDK RoC выше 100
- Длинные/короткие: Только лонг
- Условия выхода: JDK RS и JDK RoC ниже 100
- Стопы: Нет
- Значения по умолчанию:
Length= 14CandleType= TimeSpan.FromMinutes(5)
- Фильтры:
- Категория: Relative Strength
- Направление: Long
- Индикаторы: SMA, ROC, StandardDeviation
- Стопы: Нет
- Сложность: Базовая
- Таймфрейм: Внутридневной (5м)
- Сезонность: Нет
- Нейросети: Нет
- Дивергенция: Нет
- Уровень риска: Средний
using System;
using System.Linq;
using System.Collections.Generic;
using Ecng.Common;
using Ecng.Collections;
using Ecng.Serialization;
using StockSharp.Algo.Indicators;
using StockSharp.Algo.Strategies;
using StockSharp.BusinessEntities;
using StockSharp.Messages;
namespace StockSharp.Samples.Strategies;
/// <summary>
/// Yeong Relative Rotation Graph strategy.
/// Uses normalized relative strength (price vs SMA) and momentum
/// to classify market into quadrants and trade accordingly.
/// </summary>
public class YeongRrgStrategy : Strategy
{
private readonly StrategyParam<int> _length;
private readonly StrategyParam<DataType> _candleType;
private readonly List<decimal> _rsRatioHistory = new();
private readonly List<decimal> _rmRatioHistory = new();
private decimal _prevRsRatio;
public int Length { get => _length.Value; set => _length.Value = value; }
public DataType CandleType { get => _candleType.Value; set => _candleType.Value = value; }
public YeongRrgStrategy()
{
_length = Param(nameof(Length), 20)
.SetGreaterThanZero()
.SetDisplay("Length", "Period for calculations", "Indicators");
_candleType = Param(nameof(CandleType), TimeSpan.FromHours(4).TimeFrame())
.SetDisplay("Candle Type", "Type of candles", "General");
}
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
{
return [(Security, CandleType)];
}
protected override void OnReseted()
{
base.OnReseted();
_rsRatioHistory.Clear();
_rmRatioHistory.Clear();
_prevRsRatio = 0;
}
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
var sma = new SimpleMovingAverage { Length = Length };
_rsRatioHistory.Clear();
_rmRatioHistory.Clear();
_prevRsRatio = 0;
var subscription = SubscribeCandles(CandleType);
subscription.Bind(sma, ProcessCandle).Start();
var area = CreateChartArea();
if (area != null)
{
DrawCandles(area, subscription);
DrawIndicator(area, sma);
DrawOwnTrades(area);
}
}
private void ProcessCandle(ICandleMessage candle, decimal smaVal)
{
if (candle.State != CandleStates.Finished)
return;
if (smaVal <= 0)
return;
// RS ratio: price relative to its SMA (like relative strength vs benchmark)
var rsRatio = (candle.ClosePrice / smaVal) * 100m;
_rsRatioHistory.Add(rsRatio);
if (_rsRatioHistory.Count > Length * 3)
_rsRatioHistory.RemoveAt(0);
// RM ratio: momentum of RS ratio
decimal rmRatio;
if (_prevRsRatio > 0)
rmRatio = rsRatio - _prevRsRatio;
else
rmRatio = 0;
_prevRsRatio = rsRatio;
_rmRatioHistory.Add(rmRatio);
if (_rmRatioHistory.Count > Length * 3)
_rmRatioHistory.RemoveAt(0);
if (_rsRatioHistory.Count < Length || _rmRatioHistory.Count < Length)
return;
// Normalize RS ratio
var rsMean = _rsRatioHistory.Skip(_rsRatioHistory.Count - Length).Average();
var rsStd = StdDev(_rsRatioHistory.Skip(_rsRatioHistory.Count - Length));
if (rsStd == 0) rsStd = 1;
// Normalize RM ratio
var rmMean = _rmRatioHistory.Skip(_rmRatioHistory.Count - Length).Average();
var rmStd = StdDev(_rmRatioHistory.Skip(_rmRatioHistory.Count - Length));
if (rmStd == 0) rmStd = 1;
var jdkRs = 100m + ((rsRatio - rsMean) / rsStd);
var jdkRm = 100m + ((rmRatio - rmMean) / rmStd);
// Quadrant classification
// Green: RS > 100 && RM > 100 (leading)
// Red: RS < 100 && RM < 100 (lagging)
var buySignal = jdkRs > 100m && jdkRm > 100m;
var sellSignal = jdkRs < 100m && jdkRm < 100m;
if (buySignal && Position <= 0)
{
BuyMarket();
}
else if (sellSignal && Position >= 0)
{
SellMarket();
}
}
private static decimal StdDev(IEnumerable<decimal> values)
{
var list = values.ToList();
if (list.Count < 2) return 0;
var mean = list.Average();
var sumSq = list.Sum(v => (v - mean) * (v - mean));
return (decimal)Math.Sqrt((double)(sumSq / list.Count));
}
}
import clr
clr.AddReference("StockSharp.Messages")
clr.AddReference("StockSharp.Algo")
clr.AddReference("StockSharp.Algo.Indicators")
clr.AddReference("StockSharp.Algo.Strategies")
from System import TimeSpan, Math
from StockSharp.Messages import DataType, CandleStates
from StockSharp.Algo.Indicators import SimpleMovingAverage
from StockSharp.Algo.Strategies import Strategy
class yeong_rrg_strategy(Strategy):
def __init__(self):
super(yeong_rrg_strategy, self).__init__()
self._length = self.Param("Length", 20) \
.SetDisplay("Length", "Period for calculations", "Indicators")
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromHours(4))) \
.SetDisplay("Candle Type", "Type of candles", "General")
self._rs_ratio_history = []
self._rm_ratio_history = []
self._prev_rs_ratio = 0.0
@property
def length(self):
return self._length.Value
@property
def candle_type(self):
return self._candle_type.Value
def OnReseted(self):
super(yeong_rrg_strategy, self).OnReseted()
self._rs_ratio_history = []
self._rm_ratio_history = []
self._prev_rs_ratio = 0.0
def OnStarted2(self, time):
super(yeong_rrg_strategy, self).OnStarted2(time)
sma = SimpleMovingAverage()
sma.Length = self.length
self._rs_ratio_history = []
self._rm_ratio_history = []
self._prev_rs_ratio = 0.0
subscription = self.SubscribeCandles(self.candle_type)
subscription.Bind(sma, self.on_process).Start()
area = self.CreateChartArea()
if area is not None:
self.DrawCandles(area, subscription)
self.DrawIndicator(area, sma)
self.DrawOwnTrades(area)
def on_process(self, candle, sma_val):
if candle.State != CandleStates.Finished:
return
if sma_val <= 0:
return
rs_ratio = (float(candle.ClosePrice) / float(sma_val)) * 100.0
self._rs_ratio_history.append(rs_ratio)
if len(self._rs_ratio_history) > self.length * 3:
self._rs_ratio_history.pop(0)
if self._prev_rs_ratio > 0:
rm_ratio = rs_ratio - self._prev_rs_ratio
else:
rm_ratio = 0.0
self._prev_rs_ratio = rs_ratio
self._rm_ratio_history.append(rm_ratio)
if len(self._rm_ratio_history) > self.length * 3:
self._rm_ratio_history.pop(0)
if len(self._rs_ratio_history) < self.length or len(self._rm_ratio_history) < self.length:
return
rs_slice = self._rs_ratio_history[-self.length:]
rm_slice = self._rm_ratio_history[-self.length:]
rs_mean = sum(rs_slice) / len(rs_slice)
rs_std = self._std_dev(rs_slice)
if rs_std == 0:
rs_std = 1.0
rm_mean = sum(rm_slice) / len(rm_slice)
rm_std = self._std_dev(rm_slice)
if rm_std == 0:
rm_std = 1.0
jdk_rs = 100.0 + ((rs_ratio - rs_mean) / rs_std)
jdk_rm = 100.0 + ((rm_ratio - rm_mean) / rm_std)
buy_signal = jdk_rs > 100.0 and jdk_rm > 100.0
sell_signal = jdk_rs < 100.0 and jdk_rm < 100.0
if buy_signal and self.Position <= 0:
self.BuyMarket()
elif sell_signal and self.Position >= 0:
self.SellMarket()
def _std_dev(self, values):
if len(values) < 2:
return 0.0
mean = sum(values) / len(values)
sum_sq = 0.0
for v in values:
sum_sq += (v - mean) * (v - mean)
return Math.Sqrt(sum_sq / len(values))
def CreateClone(self):
return yeong_rrg_strategy()