namespace StockSharp.Samples.Strategies;
using System;
using Ecng.Common;
using StockSharp.Algo.Indicators;
using StockSharp.Algo.Strategies;
using StockSharp.Messages;
/// <summary>
/// Candlestick reversal strategy: detects hammer/shooting star patterns.
/// Buys on bullish hammer candle, sells on bearish shooting star.
/// </summary>
public class ExpertCandlesStrategy : Strategy
{
private readonly StrategyParam<DataType> _candleType;
private readonly StrategyParam<decimal> _shadowRatio;
public DataType CandleType
{
get => _candleType.Value;
set => _candleType.Value = value;
}
public decimal ShadowRatio
{
get => _shadowRatio.Value;
set => _shadowRatio.Value = value;
}
public ExpertCandlesStrategy()
{
_candleType = Param(nameof(CandleType), TimeSpan.FromMinutes(30).TimeFrame())
.SetDisplay("Candle Type", "Candle timeframe", "General");
_shadowRatio = Param(nameof(ShadowRatio), 0.3m)
.SetGreaterThanZero()
.SetDisplay("Shadow Ratio", "Min shadow to body ratio for pattern", "Signals");
}
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
var sma = new SimpleMovingAverage { Length = 20 };
var subscription = SubscribeCandles(CandleType);
subscription
.Bind(sma, (candle, smaVal) =>
{
if (candle.State != CandleStates.Finished)
return;
if (!IsFormedAndOnlineAndAllowTrading())
return;
var open = candle.OpenPrice;
var high = candle.HighPrice;
var low = candle.LowPrice;
var close = candle.ClosePrice;
var range = high - low;
if (range <= 0)
return;
var body = Math.Abs(close - open);
var upperShadow = high - Math.Max(open, close);
var lowerShadow = Math.Min(open, close) - low;
var isHammer = lowerShadow > range * ShadowRatio && upperShadow < body;
var isShootingStar = upperShadow > range * ShadowRatio && lowerShadow < body;
if (isHammer && close > smaVal && Position <= 0)
BuyMarket();
else if (isShootingStar && close < smaVal && Position >= 0)
SellMarket();
})
.Start();
var area = CreateChartArea();
if (area != null)
{
DrawCandles(area, subscription);
DrawIndicator(area, sma);
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 SimpleMovingAverage
from StockSharp.Algo.Strategies import Strategy
class expert_candles_strategy(Strategy):
def __init__(self):
super(expert_candles_strategy, self).__init__()
self._shadow_ratio = self.Param("ShadowRatio", 0.3) \
.SetDisplay("Shadow Ratio", "Min shadow to body ratio for pattern", "Signals")
self._sma = None
@property
def shadow_ratio(self):
return self._shadow_ratio.Value
def OnReseted(self):
super(expert_candles_strategy, self).OnReseted()
self._sma = None
def OnStarted2(self, time):
super(expert_candles_strategy, self).OnStarted2(time)
self._sma = SimpleMovingAverage()
self._sma.Length = 20
subscription = self.SubscribeCandles(DataType.TimeFrame(TimeSpan.FromMinutes(30)))
subscription.Bind(self._sma, self._process_candle)
subscription.Start()
def _process_candle(self, candle, sma_value):
if candle.State != CandleStates.Finished:
return
if not self._sma.IsFormed:
return
open_p = float(candle.OpenPrice)
high = float(candle.HighPrice)
low = float(candle.LowPrice)
close = float(candle.ClosePrice)
sma_val = float(sma_value)
range_size = high - low
if range_size <= 0:
return
body = abs(close - open_p)
upper_shadow = high - max(open_p, close)
lower_shadow = min(open_p, close) - low
is_hammer = lower_shadow > range_size * self.shadow_ratio and upper_shadow < body
is_shooting_star = upper_shadow > range_size * self.shadow_ratio and lower_shadow < body
if is_hammer and close > sma_val and self.Position <= 0:
self.BuyMarket()
elif is_shooting_star and close < sma_val and self.Position >= 0:
self.SellMarket()
def CreateClone(self):
return expert_candles_strategy()