ChaoZhang
概述
该策略是一个基于技术指标的简单自动多头趋势策略,适用于比特币和以太坊等加密货币,旨在捕捉主要上涨趋势,降低频繁交易导致的手续费损失。
策略原理
使用MACD判断趋势方向,MACD向上交叉时看多;
计算20周期EMA,100周期SMA和200周期SMA,EMA和SMA同向上提时看多;
EMA高于SMA时买入做多,SMA高于SMA慢线时买入做多;
设定止损线,价格跌破止损线时止损退出。
当价格下跌时EMA下穿SMA时平仓退出。
该策略综合多个指标判断趋势及入场时机,通过追踪主要上涨趋势获得利润。
策略优势
多指标组合判断,可以有效过滤假突破等错误信号;
只在趋势明确时入场,可以减少不必要交易,降低交易频率;
止损策略可以有效控制单笔交易的最大亏损;
回测数据显示在比特币和以太坊中可以获得较好收益;
策略逻辑简单清晰,容易理解实现,适合初学者学习。
可扩展性强,可以引入更多指标进行优化。
策略风险
市场走势随机性大,判断失误风险;
单一持仓方式无法规避系统性风险;
止损点设置不当可能导致过度止损;
回测数据不代表实盘表现,实盘效果待验证;
没有考虑交易费用的影响,实盘效果可能有所差异。
没有考虑不同品种特点,需要调整优化。
策略优化方向
测试不同参数组合,优化指标参数;
增加类似KDJ等指标过滤入场信号;
优化止损策略,引入动态止损;
考虑账户资金管理,调整仓位大小;
区分品种特点,调整参数;
结合更多时间周期指标判断;
测试不同品种效果,找出最佳品种。
总结
该策略整体思路清晰易懂,使用多指标判断可以有效过滤错误信号。但仍需进一步优化参数、风险控制等,再结合实盘验证,方可实际应用。如果进一步扩展优化,可以成为一个非常实用的加密货币趋势跟踪策略。
策略源码
/*backtest
start: 2023-09-06 00:00:00
end: 2023-10-06 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
//@version=4
strategy(title="BTC Long strategy", overlay=true, max_bars_back=3000, initial_capital=1000, commission_value=0.075)
//////////// !!!!!!!!!!!!!!!! WORK BEST IN 2 HOURS for BTC, ETH and ETHXBT !!!!!!!!!!!!!!!!!!! /////////////////////
[macdLine, macdSignalLine, macdHist] = macd(close, 12, 26, 7)
//_rsi_len = input(14, title="RSI length")
_rsi_len = 14
NewValue = 0
PreviousValue = 0
leverage = 1
smaPercentageIncrease = 0.0
SMA_PERCENT_INCREASE = 0.0
float atrValue = 0
bool bPositionOpened = false
float stockPositionSize = 0
float volatilityPercentage = 0.0
bool bDisplayArrow = false
bool bEMAIsRising = false
bool bSMAIsRising = false
bool bSMASlowIsRising = false
bool bMACDIsRising = false
bool bMACDHistIsRising = false
bool bMACDSignalIsRising = false
float stopLoss = input (1.5, "StopLoss in %", type=input.float) //StopLoss associated with the order
//positionSize = input (1000, "in $")
float positionSize = 1000
float currentPrice = close
float stopLossPrice = 0
float entryPrice = 0
//-----------------------------------------------------------
// === INPUT BACKTEST RANGE ONE YEAR
//FromDay = input(defval = 01, title = "From Day", minval = 1, maxval = 31)
//FromMonth = input(defval = 01, title = "From Month", minval = 1, maxval = 12)
//FromYear = input(defval = 2020, title = "From Year", minval = 2017)
FromDay = 01
FromMonth = 01
FromYear = 2019
//ToDay = input(defval = 01, title = "To Day", minval = 1, maxval = 31)
//ToMonth = input(defval = 01, title = "To Month", minval = 1, maxval = 12)
//ToYear = input(defval = 2023, title = "To Year", minval = 2017)
ToDay = 31
ToMonth = 12
ToYear = 2099
// === FUNCTION EXAMPLE ===
start = timestamp(FromYear, FromMonth, FromDay, 00, 00) // backtest start window
finish = timestamp(ToYear, ToMonth, ToDay, 23, 59) // backtest finish window
window() => true // create function "within window of time"
//emaLength = input(20, "EMA Length")
//smaLength = input(100, "SMA Length")
//smaSlowLength = input(200, "SMA Length")
emaLength = 20
smaLength = 100
smaSlowLength = 200
ema = ema(close, emaLength)
sma = sma(close, smaLength)
smaSlow = sma(close, smaSlowLength)
plot(sma, color=color.green)
plot(smaSlow, color=color.orange)
plot(ema, color=color.yellow)
//reload previous values
stopLossPrice := na(stopLossPrice[1]) ? 0.0 : stopLossPrice[1]
entryPrice := na(entryPrice[1]) ? 0.0 : entryPrice[1]
bPositionOpened := na(bPositionOpened[1]) ? false : bPositionOpened[1]
positionSize := na(positionSize[1]) ? 50000 : positionSize[1]
stockPositionSize := na(stockPositionSize[1]) ? 0 : stockPositionSize[1]
//leverage := na(leverage[1]) ? 1 : leverage[1]
//ReEvaluate the direction of indicators
bEMAIsRising := rising(ema, 2)
bSMAIsRising := rising(sma, 3)
bMACDIsRising := rising(macdLine, 3)
bMACDHistIsRising := rising(macdHist, 1)
bSMASlowIsRising := rising(smaSlow, 10)
bMACDSignalIsRising := rising(macdSignalLine, 3)
atrValue := atr(14)
volatilityPercentage := (atrValue/currentPrice)*100 //calcute the volatility. Percentage of the actual price
//There is too many signal in tranding market, to avoid this we need to make sure that the smaSlow has a mininal increase
//THIS DOES NOT WORK AT ALL!!!!!
//if bSMASlowIsRising == true
// //calculate the percentegage difference over the last 10 bars
// smaPercentageIncrease := ((smaSlow[0]/sma[10])-1)*100
// if smaPercentageIncrease < SMA_PERCENT_INCREASE
// //Not enough increase we reset the flag
// bSMASlowIsRising := false
if (window())
//Check if we can open a LONG
//sma > smaSlow and
if ( volatilityPercentage < 2 and bPositionOpened == false and bSMASlowIsRising == true and bMACDIsRising == true and bEMAIsRising == true and bSMAIsRising == true and ema[0] > sma[0] and sma[0] < currentPrice)
// add comparaison between macd and macd signal line
//if (bPositionOpened == false and macdSignalLine < macdLine and bMACDIsRising == true and bMACDHistIsRising == true and bEMAIsRising == true and bSMAIsRising == true and ema[1] > sma[1] and sma[1] < currentPrice)
//Enter in short position
stockPositionSize := (positionSize*leverage)/currentPrice //Calculate the position size based on the actual price and the position Size (in $) configured.
//calculate exit values
stopLossPrice := currentPrice*(1-stopLoss/100)
strategy.entry("myPosition", strategy.long, qty=stockPositionSize, comment="BUY at " + tostring(currentPrice))
entryPrice := currentPrice //store the entry price
bPositionOpened := true
bDisplayArrow := true
//if (bPositionOpened == true and (currentPrice <= stopLossPrice or crossunder(ema[1], sma[1]) or currentPrice < sma[1]))
if (bPositionOpened == true and (currentPrice <= stopLossPrice or crossunder(ema[1], sma[1])))
strategy.close("myPosition", comment="" + tostring(currentPrice) ) //Stop
//uncomment the below line to make the bot investing the full portfolio amount to test compounding effect.
//positionSize := positionSize + ((stockPositionSize * currentPrice) - (positionSize*leverage))
//reset some flags
bPositionOpened := false
bDisplayArrow := true
entryPrice := 0.0