隔夜高波动加密策略
该策略在高波动的夜间入场做多,并在午夜前平仓。波动率通过指定周期的对数收益标准差计算,并与历史波动率的中位数比较。
细节
- 入场条件:
- 启用
UseVolatilityFilter时:currentHour == EntryHour && highVolatility - 关闭过滤器时:
currentHour == EntryHour
- 启用
- 多空方向:多头
- 止损:无
- 默认参数:
VolatilityPeriodDays= 30MedianPeriodDays= 208EntryHour= 21ExitHour= 23UseVolatilityFilter= trueCandleType= TimeSpan.FromHours(1).TimeFrame()
- 过滤器:
- 类别:时间
- 方向:多头
- 指标:StandardDeviation,Median
- 止损:否
- 复杂度:初级
- 时间框架:日内
- 季节性:否
- 神经网络:否
- 背离:否
- 风险等级:低
using System;
using Ecng.Common;
using StockSharp.Algo.Indicators;
using StockSharp.Algo.Strategies;
using StockSharp.Messages;
namespace StockSharp.Samples.Strategies;
public class OvernightEffectHighVolatilityCryptoStrategy : Strategy
{
private readonly StrategyParam<DataType> _candleType;
private DateTime _currentDay;
private bool _tradeTakenToday;
public DataType CandleType { get => _candleType.Value; set => _candleType.Value = value; }
public OvernightEffectHighVolatilityCryptoStrategy()
{
_candleType = Param(nameof(CandleType), TimeSpan.FromMinutes(5).TimeFrame());
}
/// <inheritdoc />
protected override void OnReseted()
{
base.OnReseted();
_currentDay = default;
_tradeTakenToday = false;
}
/// <inheritdoc />
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
_currentDay = default;
_tradeTakenToday = false;
var sma = new SimpleMovingAverage { Length = 20 };
var subscription = SubscribeCandles(CandleType);
subscription
.Bind(sma, (candle, smaVal) =>
{
if (candle.State != CandleStates.Finished)
return;
if (!sma.IsFormed)
return;
var day = candle.OpenTime.Date;
if (_currentDay != day)
{
_currentDay = day;
_tradeTakenToday = false;
}
if (_tradeTakenToday)
return;
var hour = candle.OpenTime.Hour;
// Buy at 20:00, only once per day
if (hour == 20 && Position <= 0 && candle.ClosePrice > smaVal)
{
BuyMarket();
_tradeTakenToday = true;
}
// Sell at 8:00, only once per day
else if (hour == 8 && Position >= 0 && candle.ClosePrice < smaVal)
{
SellMarket();
_tradeTakenToday = true;
}
})
.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 overnight_effect_high_volatility_crypto_strategy(Strategy):
def __init__(self):
super(overnight_effect_high_volatility_crypto_strategy, self).__init__()
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromMinutes(5)))
self._current_day = None
self._trade_taken_today = False
@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(overnight_effect_high_volatility_crypto_strategy, self).OnReseted()
self._current_day = None
self._trade_taken_today = False
def OnStarted2(self, time):
super(overnight_effect_high_volatility_crypto_strategy, self).OnStarted2(time)
self._current_day = None
self._trade_taken_today = False
self._sma = SimpleMovingAverage()
self._sma.Length = 20
subscription = self.SubscribeCandles(self.candle_type)
subscription.Bind(self._sma, self.OnProcess).Start()
def OnProcess(self, candle, sma_val):
if candle.State != CandleStates.Finished:
return
if not self._sma.IsFormed:
return
sv = float(sma_val)
close = float(candle.ClosePrice)
day = candle.OpenTime.Date
if self._current_day is None or self._current_day != day:
self._current_day = day
self._trade_taken_today = False
if self._trade_taken_today:
return
hour = candle.OpenTime.Hour
if hour == 20 and self.Position <= 0 and close > sv:
self.BuyMarket()
self._trade_taken_today = True
elif hour == 8 and self.Position >= 0 and close < sv:
self.SellMarket()
self._trade_taken_today = True
def CreateClone(self):
return overnight_effect_high_volatility_crypto_strategy()