Strategy of Indicators Combination Breakthrough Trend Tracking

Author: ChaoZhang, Date: 2024-02-20 11:38:22



The strategy is named “Strategy of Indicators Combination Breakthrough Trend Tracking”. It combines various indicators to identify market trend directions and carry out trend tracking operations. The main components include:

  1. Using Wave Trend indicator to judge the main trend of the market
  2. Filtering out some false signals with RSI and MFI indicators
  3. Determining specific operational directions with EMA indicator
  4. Entering the market with breakthrough tracking method to ensure following the trend

Strategy Principle

The strategy mainly judges the direction and strength of the major trend, and sets bidirectional trading of long and short. The specific operating principles are as follows:

Long signal:

  1. Price is above 200-day EMA, indicating a bull market
  2. Price pulls back to around 50-day EMA forming support
  3. Wave Trend reverses to upward trend and a buy signal appears
  4. Both RSI and MFI show overbought
  5. 3 consecutive K-lines break through 50-day EMA successively, indicating a breakthrough upwards

Short signal: Opposite of long signal

Profit taking and stop loss: Two options provided: lowest price/highest price stop loss, ATR stop loss

Advantage Analysis

The strategy has the following advantages:

  1. Integrates multiple indicators to determine the major trend and avoid false breakouts
  2. Adopts EMA to determine operational direction, easy to follow trends
  3. Trailing stop loss method achieves sustained profits
  4. Capable of going both long and short, following the market in either direction

Risk Analysis

The strategy also has some risks:

  1. Probability of wrong signals from the indicators
  2. Stop loss point set too small, increasing stop loss risk
  3. High trading frequency leads to hidden loss from trading fees

To reduce the above risks, optimization can be done in the following aspects:

  1. Adjust indicator parameters to filter wrong signals
  2. Appropriately loosen the stop loss point
  3. Optimize indicator parameters to reduce trading frequency

Optimization Directions

From the code level, the main optimizable directions of this strategy include:

  1. Adjusting parameters of Wave Trend, RSI and MFI to find the best parameter combination
  2. Testing the performance of different EMA cycle parameters
  3. Adjusting risk-reward ratio factors of profit taking and stop loss to obtain optimal configuration

Through parameter adjustment and testing, the strategy can maximize returns while reducing drawdowns and risks.


The strategy integrates multiple indicators to determine the major trend direction, uses EMA indicator as specific operation signal, and uses trailing stop loss to lock in profits. Through parameter optimization, relatively good steady profits can be obtained. But the certain system risks should also be noted, the effectiveness of indicators and changes in market environment need to be continuously monitored.

start: 2023-02-13 00:00:00
end: 2024-02-19 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]

//Lowest Low/ Highest High & ATR Stop Loss/ Take Profit
//Optimized for the 30 minutes chart

strategy(title="TradePro's Trading Idea Cipher B+ Divergence EMA Pullback Strategy", shorttitle="WT MFI RSI EMA PB STRAT", overlay = true, pyramiding = 0, max_bars_back=5000, calc_on_order_fills = false, commission_type =  strategy.commission.percent, commission_value = 0, default_qty_type = strategy.percent_of_equity, default_qty_value = 100, initial_capital=5000, currency=currency.USD)

// { Time Range

// See if this bar's time happened on/after start date
afterStartDate = time >= start and time<=finish?true:false

zeroline = 0

// } Time Range

// { Wavetrend, RSI, MFI

// WaveTrend
cl = input(12, "Channel Length")
al = input(12, "Average Length")
overbought = input(53, title = 'WT Overbought Level 1', type = input.integer)
oversold = input(-53, title = 'WT Oversold Level 1', type = input.integer)
ap = hlc3 
esa = ema(ap, cl)
d = ema(abs(ap - esa), cl)
ci = (ap - esa) / (0.015 * d)
tci = ema(ci, al)
wt1 = tci
wt2 = sma(wt1,4)

wtOs = wt2 <= oversold
wtOb = wt2 >= overbought
wtX = cross(wt1, wt2)
wtUp = wt2 - wt1 <= 0
wtDown = wt2 - wt1 >= 0
buySignal = wtX and wtOs and wtUp
sellSignal = wtX and wtOb and wtDown

// RSI & MFI

rsiMFIPosY = input(2, title = 'MFI Area Y Pos', type = input.float)
rsiMFIperiod = input(80,title = 'MFI Period', type = input.integer)
rsiMFIMultiplier = input(200, title = 'MFI Area multiplier', type = input.float)
f_rsimfi(_period, _multiplier, _tf) => security(syminfo.tickerid, _tf, sma(((close - open) / (high - low)) * _multiplier, _period) - rsiMFIPosY)
rsiMFI = f_rsimfi(rsiMFIperiod, rsiMFIMultiplier, timeframe.period)

// } Wavetrend, RSI, MFI

// { EMA
emasrc = close
res = input(title="EMA Timeframe", type=input.resolution, defval="30")
len1 = input(title="EMA1 Length", type=input.integer, defval=200)
col1 = color.yellow

len2 = input(title="EMA2 Length", type=input.integer, defval=50)
col2 =

// Calculate EMA
ema1 = ema(emasrc, len1)
emaSmooth1 = security(syminfo.tickerid, res, ema1, barmerge.gaps_off, barmerge.lookahead_off)

ema2 = ema(emasrc, len2)
emaSmooth2 = security(syminfo.tickerid, res, ema2, barmerge.gaps_off, barmerge.lookahead_off)

// Draw EMA
plot(emaSmooth1, title="EMA1", linewidth=1, color=col1)
plot(emaSmooth2, title="EMA2", linewidth=1, color=col2)

// } EMA

// { Long Entry

enablelong = input(true, title="Enable long?")

//Long Signal
upcondition = close > emaSmooth1
wavetrendlong = wt1 and wt2 < zeroline
mfilong = rsiMFI > 0
emapblong1 = (close > emaSmooth2) and (close[1] < emaSmooth2[1])
emapblong2 = ((close[2] > emaSmooth2[2]) and (close[3] > emaSmooth2[3]) and (close[4] > emaSmooth2[4])) or ((close[5] > emaSmooth2[5]) and (close[6] > emaSmooth2[6]) and (close[7] > emaSmooth2[7])) or ((close[8] > emaSmooth2[8]) and (close[9] > emaSmooth2[9]) and (close[10] > emaSmooth2[10]))

longcondition = upcondition and wavetrendlong and buySignal and mfilong and emapblong1 and emapblong2

//strategy buy long
if (longcondition) and (afterStartDate) and strategy.opentrades < 1 and (enablelong == true)
    strategy.entry("long", strategy.long)

plotshape(longcondition, style=shape.arrowup,

// } Long Entry

// { Short Entry

enableshort = input(true, title="Enable short?")

//Short Signal
downcondition = close < emaSmooth1
wavetrendshort = wt1 and wt2 > zeroline
mfishort = rsiMFI < 0
emapbshort1 = (close < emaSmooth2) and (close[1] > emaSmooth2[1])
emapbshort2 = ((close[2] < emaSmooth2[2]) and (close[3] < emaSmooth2[3]) and (close[4] < emaSmooth2[4])) or ((close[5] < emaSmooth2[5]) and (close[6] < emaSmooth2[6]) and (close[7] < emaSmooth2[7])) or ((close[8] < emaSmooth2[8]) and (close[9] < emaSmooth2[9]) and (close[10] < emaSmooth2[10]))

shortcondition = downcondition and wavetrendshort and sellSignal and mfishort and emapbshort1 and emapbshort2

//strategy buy short
if (shortcondition) and (afterStartDate) and strategy.opentrades < 1 and (enableshort == true)
    strategy.entry("short", strategy.short)

plotshape(shortcondition, style=shape.arrowdown,

// } Short Entry

// { Exit Conditions
bought = strategy.position_size[1] < strategy.position_size
sold = strategy.position_size[1] > strategy.position_size
barsbought = barssince(bought)
barssold = barssince(sold)
slbuffer = input(title="SL Buffer", type=input.float, step=0.1, defval=0)

// } Exit Conditions

// { Lowest Low/ Highes High Exit Condition
enablelowhigh = input(false, title="Enable lowest low/ highest high exit?")

//Lowest Low LONG
profitfactorlong = input(title="ProfitfactorLong", type=input.float, step=0.1, defval=2)
loLen = input(title="Lowest Low Lookback", type=input.integer,
  defval=50, minval=2)
stop_level_long = lowest(low, loLen)[1]

if enablelowhigh == true and strategy.position_size>0
    profit_level_long = strategy.position_avg_price + ((strategy.position_avg_price - stop_level_long[barsbought])*profitfactorlong) + slbuffer
    strategy.exit(id="TP/ SL", stop=stop_level_long[barsbought] - slbuffer, limit=profit_level_long)

//Lowest Low SHORT
profitfactorshort = input(title="ProfitfactorShort", type=input.float, step=0.1, defval=2)
highLen = input(title="highest high lookback", type=input.integer,
  defval=50, minval=2)
stop_level_short = highest(high, highLen)[1]

if enablelowhigh == true and strategy.position_size<0
    profit_level_short = strategy.position_avg_price - ((stop_level_short[barssold] - strategy.position_avg_price)*profitfactorshort) - slbuffer
    strategy.exit(id="TP/ SL", stop=stop_level_short[barssold] + slbuffer, limit=profit_level_short)

// } Lowest Low/ Highes High Exit Condition

// { ATR Take Profit/ Stop Loss
enableatr = input(true, title="Enable ATR exit?")
atrprofitfactorlong = input(title="ATR Profitfactor Long", type=input.float, step=0.1, defval=6)
atrstopfactorlong = input(title="ATR Stopfactor Long", type=input.float, step=0.1, defval=5)
atrprofitfactorshort = input(title="ATR Profitfactor Short", type=input.float, step=0.1, defval=3)
atrstopfactorshort = input(title="ATR Stopfactor Short", type=input.float, step=0.1, defval=5)

lengthATR = input(title="ATR Length", defval=11, minval=1)
atr = atr(lengthATR)

if (afterStartDate) and ((enableatr == true) and (strategy.opentrades > 0))
    barsbought1 = barssince(bought)
    profit_level = strategy.position_avg_price + (atr*atrprofitfactorlong)
    stop_level = strategy.position_avg_price - (atr*atrstopfactorlong)
    strategy.exit("Take Profit/ Stop Loss", "long", stop=stop_level[barsbought1], limit=profit_level[barsbought1])

if (afterStartDate) and ((enableatr == true) and (strategy.opentrades > 0))
    barssold1 = barssince(sold)
    profit_level = strategy.position_avg_price - (atr*atrprofitfactorshort)
    stop_level = strategy.position_avg_price + (atr*atrstopfactorshort)
    strategy.exit("Take Profit/ Stop Loss", "short", stop=stop_level[barssold1], limit=profit_level[barssold1])

// } ATR Take Profit/ Stop Loss