EMA RSI Hidden Divergence Trend Following Strategy

Pine ScriptTrend following Mean reversion Momentum RSI EMA SMA ATR Stochastic Pivots / S&R

Author: ChaoZhang
Complexity: Intermediate · 99 lines
Parameters: 19
Backtest bar: 1m · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

This strategy opens long positions based on the EMA crossover and RSI hidden bullish divergence signals to identify the beginning of an upward trend. The combination of EMA lines, RSI indicator, and K-line closing prices provides double confirmation for ensuring an upward momentum. This strategy is suitable to follow mid-long term trends and open long positions after price consolidations.

Strategy Logic

EMA Strategy: Using the golden cross of 50-period EMA and 250-period EMA to determine the trend direction. A close above the 50 EMA gives a long signal.
RSI Hidden Divergence Strategy: The RSI forms lower lows while price forms higher lows, signaling a trend reversal at the beginning. Limiting the number of pivot points filters out false signals.
K-line Closing Strategy: Go long when the closing price is above the 50 EMA line.

The combination of the above three strategies identifies the start of an upward trend and opens long positions accordingly.

Advantage Analysis

Using EMA lines to determine trend direction along with RSI reversal signals allows early entry at the beginning of trends.
The dual confirmation from EMA lines, RSI indicator, and K-line closing prices effectively filters out false signals.
Following mid-long term trends makes it suitable to identify new up trends after consolidations.

Risk Analysis

Close positions when the EMA lines have a death cross.
Identifying RSI hidden divergences needs experience, improper parameter tuning could lead to missing or false signals.
Parameters need optimization for different trading instruments.

Optimization Directions

Dynamically adjust EMA parameters for better trend determination accuracy.
Fine tune RSI parameters for better hidden divergence signal accuracy.
Add stop loss mechanisms like ATR or percentage stops to control risks.
Develop strategies for short positions to trade downward trends.

Conclusion

This strategy combines EMA lines for trend determination and RSI signals for increase accuracy. It identifies new upward trends after consolidations. With proper parameter tuning and risk management, it could achieve good results. Compared to simple moving average strategies, it has higher accuracy in catching trends with better win rates. Overall it is a practical trend following strategy.

Parameters

Name	Default	What it controls
v_input_1	true	FromMonth
v_input_2	true	FromDay
v_input_3	2020	FromYear
v_input_4	true	ToMonth
v_input_5	true	ToDay
v_input_6	9999	ToYear
v_input_7	50	EMA1
v_input_8	250	EMA2
v_input_9	4	K
v_input_10	4	D
v_input_11	3	Smooth
v_input_12	14	RSI Period
v_input_13_close	0	RSI Source: close \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4
v_input_14	true	Pivot Lookback Right
v_input_15	19	Pivot Lookback Left
v_input_16	20	Max of Lookback Range
v_input_17	4	Min of Lookback Range
v_input_18	1.6	Profitfactor
v_input_19	38	Lowest Low Lookback

Source Pine Script

/*backtest
start: 2024-01-25 00:00:00
end: 2024-02-01 00:00:00
period: 1m
basePeriod: 1m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=4

strategy(title="EMA RSI ATR Hidden Div Strat", shorttitle="Hidden Div Strat", overlay = true, pyramiding = 0, max_bars_back=3000, calc_on_order_fills = false, commission_type =  strategy.commission.percent, commission_value = 0, default_qty_type = strategy.percent_of_equity, default_qty_value = 10, initial_capital=5000, currency=currency.USD)

// Time Range
FromMonth=input(defval=1,title="FromMonth",minval=1,maxval=12)
FromDay=input(defval=1,title="FromDay",minval=1,maxval=31)
FromYear=input(defval=2020,title="FromYear",minval=2016)
ToMonth=input(defval=1,title="ToMonth",minval=1,maxval=12)
ToDay=input(defval=1,title="ToDay",minval=1,maxval=31)
ToYear=input(defval=9999,title="ToYear",minval=2017)
start=timestamp(FromYear,FromMonth,FromDay,00,00)
finish=timestamp(ToYear,ToMonth,ToDay,23,59)
window()=>true

// Bar's time happened on/after start date?
afterStartDate = time >= start and time<=finish?true:false

//EMA'S
emasrc = close

len1 = input(50, minval=1, title="EMA1")
ema1 = ema(emasrc, len1)
col1 = color.white

len2 = input(250, minval=1, title="EMA2")
ema2 = ema(emasrc, len2)
col2 = color.yellow

//Plots
plot(ema1, title="EMA1", linewidth=1, color=col1)
plot(ema2, title="EMA2", linewidth=1, color=col2)

//Stoch
periodK = input(4, title="K", minval=1)
periodD = input(4, title="D", minval=1)
smoothK = input(3, title="Smooth", minval=1)
k = sma(stoch(close, high, low, periodK), smoothK)
d = sma(k, periodD)

//Hidden Divergence Indikator

len = input(title="RSI Period", minval=1, defval=14)
src = input(title="RSI Source", defval=close)
lbR = input(title="Pivot Lookback Right", defval=1)
lbL = input(title="Pivot Lookback Left", defval=19)
rangeUpper = input(title="Max of Lookback Range", defval=20)
rangeLower = input(title="Min of Lookback Range", defval=4)
hiddenBullColor = color.new(color.green, 80)
textColor = color.white
noneColor = color.new(color.white, 100)
osc = rsi(src, len)

plFound = na(pivotlow(osc, lbL, lbR)) ? false : true
phFound = na(pivothigh(osc, lbL, lbR)) ? false : true
_inRange(cond) =>
	bars = barssince(cond == true)
	rangeLower <= bars and bars <= rangeUpper

//------------------------------------------------------------------------------
// Hidden Bullish
// Osc: Lower Low

oscLL = osc[lbR] < valuewhen(plFound, osc[lbR], 1) and _inRange(plFound[1])

// Price: Higher Low

priceHL = low[lbR] > valuewhen(plFound, low[lbR], 1)
hiddenBullCond = priceHL and oscLL and plFound

//buy Conditions
buyhiddenbull = hiddenBullCond[1] or hiddenBullCond[2] or hiddenBullCond[3] or hiddenBullCond[4] or hiddenBullCond[5] or hiddenBullCond[6] or hiddenBullCond[7] or hiddenBullCond[8] or hiddenBullCond[9] or hiddenBullCond[10]
emacondition = ema1 > ema2
upcondition = close[1] > ema1[1] and ema2[1] and close[2] > ema1[2] and ema2[2] and close[3] > ema1[3] and ema2[3]
crossup = k[0] >= d[0] and k[1] <= d[1]
longcondition = emacondition and upcondition and crossup and buyhiddenbull

if (afterStartDate)
    strategy.entry("Long", strategy.long, when = longcondition)

//TakeProfit, StopLoss lowest low
profitfactor = input(title="Profitfactor", type=input.float, step=0.1, defval=1.6)
loLen = input(title="Lowest Low Lookback", type=input.integer,
  defval=38, minval=2)
stop_level = lowest(low, loLen)[1]
bought = strategy.position_size[1] < strategy.position_size
barsbought = barssince(bought)

if strategy.position_size>0
    profit_level = strategy.position_avg_price + ((strategy.position_avg_price - stop_level[barsbought])*profitfactor)
    strategy.exit(id="TP/ SL", stop=stop_level[barsbought], limit=profit_level)

Published by ChaoZhang on the FMZ strategy square · last modified 2024-02-02. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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