This strategy identifies trend direction based on MACD indicator and makes specific buy and sell decisions using Stoch indicator. It adopts long cycle MACD to determine major trend and short cycle Stoch for entries and exits.
Judging major trend direction using MACD indicator
Calculating fast EMA, slow EMA and MACD histogram
Comparing MACD movements in different cycles to determine trend
Identifying specific buy and sell points using Stoch indicator
Calculating %K line and %D line
Divergence near overbought or oversold zone, with Stoch bouncing back as trading signals
Making buy and sell decisions based on trend direction and Stoch signals
Go long when major cycle MACD rises and Stoch buy signal appears
Go short when major cycle MACD falls and Stoch sell signal appears
Setting stop loss and take profit to optimize risk management
Combining trend following and overbought-oversold indicator helps capture mid-to-long term trends effectively
MACD determines major direction while Stoch works out trading details, which reduces risks
Making full use of indicator combinations to form systematic strategies
Setting stop loss and take profit controls trading risks
Optimizable parameters adapt to different market conditions
Inaccurate mid-to-long term trend judgment may lead to contrarian trading losses
False signals from Stoch cause insufficient profit or losses
Stop loss point may be broken when trend changes, expanding losses
Improper profit target levels affect strategy performance
Ineffective parameters and failure to adapt to changing environment can invalidate the strategy
Risks can be reduced by optimizing trend judgment, verifying Stoch signals, adjusting stop loss and take profit, etc.
Optimize MACD parameter mix to improve trend judgment accuracy
Consider multi-cycle Stoch to avoid false signals
Dynamically adjust stop loss and take profit ratios to adapt market volatility
Add other indicator signals to verify and improve validity
Optimize parameters based on different products’ characteristics and trading sessions
Introduce machine learning models to assist trend direction judgment
Incorporate volume indicators to avoid insufficient chasing or excessive follow
This strategy integrates the strengths of MACD and Stoch indicators to capture mid-to-long term trends while controlling risks. It can be effective in various market conditions by optimizing parameters, setting stop loss and take profit, verifying signals, etc. There is still room for improvement by further parameter tuning, improving signal accuracy, and incorporating machine learning. The strategy can be more comprehensive and intelligent.
/*backtest
start: 2023-09-19 00:00:00
end: 2023-09-26 00:00:00
period: 10m
basePeriod: 1m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
//@version=4
// strategy(title="自用策略v0.2",calc_on_order_fills=false,calc_on_every_tick =false, initial_capital=10000,commission_type=strategy.commission.percent, commission_value=0.00,overlay = true,default_qty_type = strategy.cash, default_qty_value = 10000)
//STOCH
periodD = input(3, title="%D Smoothing", minval=1)
periodK = input(14, title="%K Length", minval=1)
periodK2 = input(42, title="%K2 Length", minval=1)
periodK3 = input(126, title="%K3 Length", minval=1)
periodK4 = input(378, title="%K4 Length", minval=1)
periodK5 = input(14, title="%K5 Length", minval=1)
periodK6 = input(30, title="%K6 Length", minval=1)
smoothK = input(1, title="%K Smoothing", minval=1)
k = sma(stoch(close, high, low, periodK), smoothK)
k2 = sma(stoch(close, high, low, periodK2), smoothK*3)
k3 = sma(stoch(close, high, low, periodK3), smoothK*3*3)
k4 = sma(stoch(close, high, low, periodK4), smoothK*3*3*3)
d = sma(k, periodD)
all = (k+k2*3+k3*9+k4*18)/31
allp = sma(all, periodK6)
buffer = input(title="buffer", type=input.float, defval=0.3, minval = 0, step = 0.1)
b1 = close[1]* (1+buffer/100)
b2 = close[1]* (1-buffer/100)
//MACD
fast_length = input(title="Fast Length", defval=144)
slow_length = input(title="Slow Length", defval=312)
src = input(title="Source", defval=close)
signal_length = input(title="Signal Smoothing", minval = 1, maxval = 200, defval = 108)
sma_source = input(title="Oscillator MA Type", defval="EMA", options=["SMA", "EMA"])
sma_signal = input(title="Signal Line MA Type", defval="EMA", options=["SMA", "EMA"])
// Calculating
fast_ma = sma_source == "SMA" ? sma(src, fast_length) : ema(src, fast_length)
slow_ma = sma_source == "SMA" ? sma(src, slow_length) : ema(src, slow_length)
macd = fast_ma - slow_ma
signal = sma_signal == "SMA" ? sma(macd, signal_length) : ema(macd, signal_length)
hist = macd - signal
MACDCHA = input(title="MACDCHA步长", defval=30)
MACDCHA2 = input(title="MACDCHA步长2", defval=20)
MACDCHA3 = input(title="MACDCHA步长3", defval=10)
MACDCHA4 = input(title="MACDCHA步长4", defval=5)
MACDCHA5 = input(title="MACDCHA步长5", defval=3)
MACDCHA6 = input(title="MACDCHA步长6", defval=1)
HISTCHA = input(title="hist步长", defval=50)
macdcha = hist - hist[MACDCHA]
macdcha2 = hist - hist[MACDCHA2]
macdcha3 = hist - hist[MACDCHA3]
macdcha4 = hist - hist[MACDCHA4]
macdcha5 = hist - hist[MACDCHA5]
macdcha6 = hist - hist[MACDCHA6]
histcha = hist[HISTCHA]
var true2 = 0
var true2_1 = 0
var true2_2 = 0
var true2_3 = 0
var true2_4 = 0//延伸
var fangxiang =0
//确认方向
if(macdcha>=0 and macdcha2>=0 and macdcha3>=0 and macdcha4>=0 and macdcha5>=0 and macdcha6>=0)
fangxiang := 1
true2_2 := 0
if(macdcha<=0 and macdcha2<=0 and macdcha3<=0 and macdcha4<=0 and macdcha5<=0 and macdcha6<=0)
fangxiang :=-1
true2_1 := 1
//k3min = min(k3,k3[1],k3[2],k3[3],k3[4],k3[5],k3[6],k3[7],k3[8],k3[9],k3[10],k3[11],k3[12],k3[13],k3[14],k3[15],k3[16],k3[17],k3[18],k3[19],k3[20],k3[21],k3[22],k3[23],k3[24],k3[25],k3[26],k3[27],k3[28],k3[29],k3[30],k3[31],k3[32],k3[33],k3[34],k3[35],k3[36],k3[37],k3[38],k3[39],k3[40],k3[41],k3[42],k3[43],k3[44],k3[45],k3[46],k3[47],k3[48],k3[49],k3[50])
//k3max = max(k3,k3[1],k3[2],k3[3],k3[4],k3[5],k3[6],k3[7],k3[8],k3[9],k3[10],k3[11],k3[12],k3[13],k3[14],k3[15],k3[16],k3[17],k3[18],k3[19],k3[20],k3[21],k3[22],k3[23],k3[24],k3[25],k3[26],k3[27],k3[28],k3[29],k3[30],k3[31],k3[32],k3[33],k3[34],k3[35],k3[36],k3[37],k3[38],k3[39],k3[40],k3[41],k3[42],k3[43],k3[44],k3[45],k3[46],k3[47],k3[48],k3[49],k3[50])
allpmax = max(allp[1],allp[2],allp[3],allp[4],allp[5],allp[6])
allpmin = min(allp[1],allp[2],allp[3],allp[4],allp[5],allp[6])
if(histcha < 0 and macdcha>=0 and macdcha2>=0 and macdcha3>=0 and macdcha4>=0 and macdcha5>=0 and macdcha6>=0 and d < 20 and volume > volume[1] and true2_1 == 1 and allp>allp[1] and allp <80)//and k3max < 80 //and k3min < 30 and k3 >20 and k2<50
strategy.entry("开多", true, comment = "开多") // and close > close[1] and cci1> MEA1
true2_1 :=0
if(d >80)
strategy.close( "开多", comment = "平多")
true2_1 :=1
stop_loss=input(4, "做多止损 %", minval = 1, step = 1)
sl = strategy.position_avg_price * (1-stop_loss/100)
close_Stop = close < sl
if(close_Stop or(allp<20 and allp[1]>20))
strategy.close( "开多", comment = "做多止损")
true2_1 :=1
Target_profit=input(10, "做多止盈 %", minval = 1, step = 1)
tp = strategy.position_avg_price * (1+Target_profit/100)
close_Target = close > tp
strategy.close("开多", when = close_Target, comment ="做多盈利")
//空
if(histcha > 0 and macdcha<=0 and macdcha2<=0 and macdcha3<=0 and macdcha4<=0 and macdcha5<=0 and macdcha6<=0 and d > 80 and volume > volume[1] and true2_2 == 1 and allp<allp[1] and allp >20) // and k3max>70 and k3<80
//strategy.entry("开空", comment = "开空")
strategy.entry("开空", strategy.short,comment ="开空")
true2_2 := 0
if( d <20)
// strategy.close( comment = "平空")
strategy.close("开空", comment = "平空")
true2_2 := 1
stop_loss2=input(4, "做空止损 %", minval = 1, step = 1)
sl2 = strategy.position_avg_price * (1+stop_loss2/100)
close_Stop2 = close > sl2
if(close_Stop2 or(allp>80 and allp[1]<80))
strategy.close( "开空", comment = "做空止损")
true2_2 == 1
Target_profit2=input(10, "做空止盈 %", minval = 1, step = 1)
tp2 = strategy.position_avg_price * (1-Target_profit2/100)
close_Target2 = close < tp2
strategy.close("开空", when = close_Target2, comment ="做空盈利")