Demo GPT - 日内剥头皮策略
当连续两根阳线出现且第二根的开盘价高于第一根的收盘价,并且成交量高于20柱平均值时建立多头仓位。当连续两根阴线出现且第二根的开盘价低于第一根的收盘价,并且成交量同样高于平均值时平仓。额外计算EMA(20)、VWAP和Camarilla水平供参考。
实际条件与默认参数
默认:EmaLength=20、VolumeLookback=20、CandleType=1分钟。收集至少20根先前已完成K线后,成交量条件为 当前 TotalVolume > 先前20根的平均 TotalVolume(当前K线不参与均值)。仅空仓时、前后两根均阳线(Close > Open)、当前 Open > 前一根 Close 且放量,才做多。前后两根均阴线(Close < Open)、当前 Open < 前一根 Close 且放量时,全部平掉实际多仓。若没有严格的跳空开盘或放量,则不是信号;从不做空。EMA20 为收盘价指标;日内VWAP按 sum(典型价 × 成交量)/sum(成交量) 每日重置;前一日Camarilla H3/L3 = 前日收盘 ± 1.1 × (前日最高 − 前日最低) / 4。这些仅供参考,不参与入场过滤。无额外止损。
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;
/// <summary>
/// Two-candle scalp: long on two green candles with a gap up and a volume
/// spike; exit on two red candles with a gap down and a volume spike.
/// EMA20, session VWAP and prior-day Camarilla levels are reference-only.
/// </summary>
public class DemoGptDayTradingScalpingStrategy : Strategy
{
private readonly StrategyParam<int> _emaLength;
private readonly StrategyParam<int> _volumeLookback;
private readonly StrategyParam<DataType> _candleType;
private ExponentialMovingAverage _ema;
private readonly List<decimal> _priorVolumes = [];
private decimal? _previousClose;
private bool _previousGreen;
private bool _previousRed;
private DateTime? _sessionDate;
private decimal _sessionHigh;
private decimal _sessionLow;
private decimal _sessionClose;
private decimal _sessionSumPriceVolume;
private decimal _sessionSumVolume;
public int EmaLength { get => _emaLength.Value; set => _emaLength.Value = value; }
public int VolumeLookback { get => _volumeLookback.Value; set => _volumeLookback.Value = value; }
public DataType CandleType { get => _candleType.Value; set => _candleType.Value = value; }
/// <summary>Reference-only EMA of close prices.</summary>
public decimal ReferenceEma { get; private set; }
/// <summary>Current session VWAP, weighted by total candle volume.</summary>
public decimal ReferenceVwap { get; private set; }
/// <summary>Prior-day Camarilla H3 level.</summary>
public decimal ReferenceCamarillaH3 { get; private set; }
/// <summary>Prior-day Camarilla L3 level.</summary>
public decimal ReferenceCamarillaL3 { get; private set; }
public DemoGptDayTradingScalpingStrategy()
{
_emaLength = Param(nameof(EmaLength), 20)
.SetGreaterThanZero()
.SetDisplay("EMA Length", "Reference-only exponential moving average", "Indicators");
_volumeLookback = Param(nameof(VolumeLookback), 20)
.SetGreaterThanZero()
.SetDisplay("Volume Lookback", "Preceding candles in the volume confirmation", "Signals");
_candleType = Param(nameof(CandleType), TimeSpan.FromMinutes(1).TimeFrame())
.SetDisplay("Candle Type", "Scalping candle interval", "General");
}
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
{
return [(Security, CandleType)];
}
protected override void OnReseted()
{
base.OnReseted();
_ema = null;
_priorVolumes.Clear();
_previousClose = null;
_previousGreen = false;
_previousRed = false;
_sessionDate = null;
_sessionHigh = 0m;
_sessionLow = 0m;
_sessionClose = 0m;
_sessionSumPriceVolume = 0m;
_sessionSumVolume = 0m;
ReferenceEma = 0m;
ReferenceVwap = 0m;
ReferenceCamarillaH3 = 0m;
ReferenceCamarillaL3 = 0m;
}
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
_ema = new ExponentialMovingAverage { Length = EmaLength };
_priorVolumes.Clear();
_previousClose = null;
_previousGreen = false;
_previousRed = false;
_sessionDate = null;
_sessionSumPriceVolume = 0m;
_sessionSumVolume = 0m;
var subscription = SubscribeCandles(CandleType);
subscription.Bind(_ema, ProcessCandle).Start();
var area = CreateChartArea();
if (area != null)
{
DrawCandles(area, subscription);
DrawIndicator(area, _ema);
DrawOwnTrades(area);
}
}
private void ProcessCandle(ICandleMessage candle, decimal emaValue)
{
if (candle.State != CandleStates.Finished)
return;
ReferenceEma = emaValue;
var date = candle.OpenTime.Date;
if (_sessionDate != date)
{
if (_sessionDate is not null)
{
var range = _sessionHigh - _sessionLow;
ReferenceCamarillaH3 = _sessionClose + range * 1.1m / 4m;
ReferenceCamarillaL3 = _sessionClose - range * 1.1m / 4m;
}
_sessionDate = date;
_sessionHigh = candle.HighPrice;
_sessionLow = candle.LowPrice;
_sessionSumPriceVolume = 0m;
_sessionSumVolume = 0m;
}
_sessionHigh = Math.Max(_sessionHigh, candle.HighPrice);
_sessionLow = Math.Min(_sessionLow, candle.LowPrice);
_sessionClose = candle.ClosePrice;
var volume = Math.Max(0m, candle.TotalVolume);
_sessionSumPriceVolume += ((candle.HighPrice + candle.LowPrice + candle.ClosePrice) / 3m) * volume;
_sessionSumVolume += volume;
ReferenceVwap = _sessionSumVolume > 0m
? _sessionSumPriceVolume / _sessionSumVolume
: candle.ClosePrice;
decimal volumeSum = 0m;
foreach (var previousVolume in _priorVolumes)
volumeSum += previousVolume;
var volumeConfirmed = _priorVolumes.Count >= VolumeLookback &&
candle.TotalVolume > volumeSum / VolumeLookback;
var green = candle.ClosePrice > candle.OpenPrice;
var red = candle.ClosePrice < candle.OpenPrice;
var upGap = _previousClose is decimal lastCloseUp && candle.OpenPrice > lastCloseUp;
var downGap = _previousClose is decimal lastCloseDown && candle.OpenPrice < lastCloseDown;
// The previous-candle flags are updated only AFTER testing signals.
var buy = _previousGreen && green && upGap && volumeConfirmed;
var exit = _previousRed && red && downGap && volumeConfirmed;
_previousClose = candle.ClosePrice;
_previousGreen = green;
_previousRed = red;
_priorVolumes.Add(volume);
if (_priorVolumes.Count > VolumeLookback)
_priorVolumes.RemoveAt(0);
if (!IsFormedAndOnlineAndAllowTrading())
return;
if (Position == 0m && buy)
BuyMarket();
else if (Position > 0m && exit)
SellMarket(Position);
}
}
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
from StockSharp.Algo.Strategies import Strategy
class demo_gpt_day_trading_scalping_strategy(Strategy):
"""Long-only two-candle volume-confirmed gap strategy, with reference levels."""
def __init__(self):
super(demo_gpt_day_trading_scalping_strategy, self).__init__()
self._ema_length = self.Param("EmaLength", 20) \
.SetGreaterThanZero() \
.SetDisplay("EMA Length", "Reference EMA", "Indicators")
self._volume_lookback = self.Param("VolumeLookback", 20) \
.SetGreaterThanZero() \
.SetDisplay("Volume Lookback", "Preceding candles for volume confirmation", "Signals")
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromMinutes(1))) \
.SetDisplay("Candle Type", "Scalping candles", "General")
self._ema = None
self._prior_volumes = []
self._previous_close = None
self._previous_green = False
self._previous_red = False
self._session_date = None
self._session_high = 0.0
self._session_low = 0.0
self._session_close = 0.0
self._session_price_volume = 0.0
self._session_volume = 0.0
self.reference_ema = 0.0
self.reference_vwap = 0.0
self.reference_camarilla_h3 = 0.0
self.reference_camarilla_l3 = 0.0
@property
def candle_type(self):
return self._candle_type.Value
def OnReseted(self):
super(demo_gpt_day_trading_scalping_strategy, self).OnReseted()
self._ema = None
self._prior_volumes = []
self._previous_close = None
self._previous_green = False
self._previous_red = False
self._session_date = None
self._session_high = 0.0
self._session_low = 0.0
self._session_close = 0.0
self._session_price_volume = 0.0
self._session_volume = 0.0
self.reference_ema = 0.0
self.reference_vwap = 0.0
self.reference_camarilla_h3 = 0.0
self.reference_camarilla_l3 = 0.0
def OnStarted2(self, time):
super(demo_gpt_day_trading_scalping_strategy, self).OnStarted2(time)
self._ema = ExponentialMovingAverage()
self._ema.Length = int(self._ema_length.Value)
self._prior_volumes = []
self._previous_close = None
self._previous_green = False
self._previous_red = False
self._session_date = None
self._session_price_volume = 0.0
self._session_volume = 0.0
subscription = self.SubscribeCandles(self.candle_type)
subscription.Bind(self._ema, self._process_candle).Start()
area = self.CreateChartArea()
if area is not None:
self.DrawCandles(area, subscription)
self.DrawIndicator(area, self._ema)
self.DrawOwnTrades(area)
def _process_candle(self, candle, ema_value):
if candle.State != CandleStates.Finished:
return
self.reference_ema = float(ema_value)
date = candle.OpenTime.Date
hi = float(candle.HighPrice)
lo = float(candle.LowPrice)
close = float(candle.ClosePrice)
if self._session_date != date:
if self._session_date is not None:
range_val = self._session_high - self._session_low
self.reference_camarilla_h3 = self._session_close + range_val * 1.1 / 4.0
self.reference_camarilla_l3 = self._session_close - range_val * 1.1 / 4.0
self._session_date = date
self._session_high = hi
self._session_low = lo
self._session_price_volume = 0.0
self._session_volume = 0.0
self._session_high = max(self._session_high, hi)
self._session_low = min(self._session_low, lo)
self._session_close = close
volume = max(0.0, float(candle.TotalVolume))
self._session_price_volume += ((hi + lo + close) / 3.0) * volume
self._session_volume += volume
self.reference_vwap = (
self._session_price_volume / self._session_volume
if self._session_volume > 0 else close
)
length = int(self._volume_lookback.Value)
volume_confirmed = (
len(self._prior_volumes) >= length and
float(candle.TotalVolume) > sum(self._prior_volumes) / length
)
green = close > float(candle.OpenPrice)
red = close < float(candle.OpenPrice)
up_gap = self._previous_close is not None and float(candle.OpenPrice) > self._previous_close
down_gap = self._previous_close is not None and float(candle.OpenPrice) < self._previous_close
buy = self._previous_green and green and up_gap and volume_confirmed
exit_signal = self._previous_red and red and down_gap and volume_confirmed
self._previous_close = close
self._previous_green = green
self._previous_red = red
self._prior_volumes.append(volume)
if len(self._prior_volumes) > length:
self._prior_volumes.pop(0)
if not self.IsFormedAndOnlineAndAllowTrading():
return
if self.Position == 0 and buy:
self.BuyMarket()
elif self.Position > 0 and exit_signal:
self.SellMarket(self.Position)
def CreateClone(self):
return demo_gpt_day_trading_scalping_strategy()