Optimized Grid with KNN Strategy
This strategy opens long positions when the T3 fast line crosses above the T3 slow line and the KNN-based average price change is positive. Entry and exit thresholds are adjusted by the average change. Positions close once the T3 fast line crosses below the slow line and price exceeds the profit threshold.
- Entry Conditions:
t3Fast > t3SlowandaverageChange > 0 - Exit Conditions:
t3Fast < t3Slowand(close - lastEntryPrice)/lastEntryPrice > adjustedCloseTh - Indicators: T3
using System;
using Ecng.Common;
using StockSharp.Algo.Indicators;
using StockSharp.Algo.Strategies;
using StockSharp.Messages;
namespace StockSharp.Samples.Strategies;
public class OptimizedGridWithKnnStrategy : Strategy
{
private readonly StrategyParam<int> _fastPeriod;
private readonly StrategyParam<int> _slowPeriod;
private readonly StrategyParam<DataType> _candleType;
public int FastPeriod { get => _fastPeriod.Value; set => _fastPeriod.Value = value; }
public int SlowPeriod { get => _slowPeriod.Value; set => _slowPeriod.Value = value; }
public DataType CandleType { get => _candleType.Value; set => _candleType.Value = value; }
public OptimizedGridWithKnnStrategy()
{
_fastPeriod = Param(nameof(FastPeriod), 14).SetGreaterThanZero();
_slowPeriod = Param(nameof(SlowPeriod), 40).SetGreaterThanZero();
_candleType = Param(nameof(CandleType), TimeSpan.FromMinutes(5).TimeFrame());
}
/// <inheritdoc />
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
var fast = new ExponentialMovingAverage { Length = FastPeriod };
var slow = new ExponentialMovingAverage { Length = SlowPeriod };
var rsi = new RelativeStrengthIndex { Length = 14 };
var prevF = 0m;
var prevS = 0m;
var init = false;
var lastSignal = DateTimeOffset.MinValue;
var cooldown = TimeSpan.FromMinutes(360);
var subscription = SubscribeCandles(CandleType);
subscription
.Bind(fast, slow, rsi, (candle, f, s, r) =>
{
if (candle.State != CandleStates.Finished)
return;
if (!fast.IsFormed || !slow.IsFormed || !rsi.IsFormed)
return;
if (!init)
{
prevF = f;
prevS = s;
init = true;
return;
}
if (candle.OpenTime - lastSignal >= cooldown)
{
if (prevF <= prevS && f > s && r > 50 && Position <= 0)
{
BuyMarket();
lastSignal = candle.OpenTime;
}
else if (prevF >= prevS && f < s && r < 50 && Position >= 0)
{
SellMarket();
lastSignal = candle.OpenTime;
}
}
prevF = f;
prevS = s;
})
.Start();
var area = CreateChartArea();
if (area != null)
{
DrawCandles(area, subscription);
DrawIndicator(area, fast);
DrawIndicator(area, slow);
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 ExponentialMovingAverage, RelativeStrengthIndex
from StockSharp.Algo.Strategies import Strategy
class optimized_grid_with_knn_strategy(Strategy):
def __init__(self):
super(optimized_grid_with_knn_strategy, self).__init__()
self._fast_period = self.Param("FastPeriod", 14) \
.SetGreaterThanZero()
self._slow_period = self.Param("SlowPeriod", 40) \
.SetGreaterThanZero()
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromMinutes(5)))
self._prev_fast = 0.0
self._prev_slow = 0.0
self._initialized = False
self._last_signal_ticks = 0
@property
def candle_type(self):
return self._candle_type.Value
@candle_type.setter
def candle_type(self, value):
self._candle_type.Value = value
def OnReseted(self):
super(optimized_grid_with_knn_strategy, self).OnReseted()
self._prev_fast = 0.0
self._prev_slow = 0.0
self._initialized = False
self._last_signal_ticks = 0
def OnStarted2(self, time):
super(optimized_grid_with_knn_strategy, self).OnStarted2(time)
self._prev_fast = 0.0
self._prev_slow = 0.0
self._initialized = False
self._last_signal_ticks = 0
self._fast = ExponentialMovingAverage()
self._fast.Length = self._fast_period.Value
self._slow = ExponentialMovingAverage()
self._slow.Length = self._slow_period.Value
self._rsi = RelativeStrengthIndex()
self._rsi.Length = 14
subscription = self.SubscribeCandles(self.candle_type)
subscription.Bind(self._fast, self._slow, self._rsi, self.OnProcess).Start()
def OnProcess(self, candle, f, s, r):
if candle.State != CandleStates.Finished:
return
if not self._fast.IsFormed or not self._slow.IsFormed or not self._rsi.IsFormed:
return
fv = float(f)
sv = float(s)
rv = float(r)
if not self._initialized:
self._prev_fast = fv
self._prev_slow = sv
self._initialized = True
return
cooldown_ticks = TimeSpan.FromMinutes(360).Ticks
current_ticks = candle.OpenTime.Ticks
if current_ticks - self._last_signal_ticks >= cooldown_ticks:
if self._prev_fast <= self._prev_slow and fv > sv and rv > 50 and self.Position <= 0:
self.BuyMarket()
self._last_signal_ticks = current_ticks
elif self._prev_fast >= self._prev_slow and fv < sv and rv < 50 and self.Position >= 0:
self.SellMarket()
self._last_signal_ticks = current_ticks
self._prev_fast = fv
self._prev_slow = sv
def CreateClone(self):
return optimized_grid_with_knn_strategy()