MACD Trend Following Intraday Strategy

Pine ScriptTrend following Machine learning Breakout MACD EMA SMA ATR

Author: ChaoZhang
Complexity: Intermediate · 136 lines
Parameters: 29
Backtest bar: 1h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

The MACD Trend Following Intraday Strategy is an intraday trading strategy that combines moving averages, the MACD indicator and the Williams Indicator. It utilizes different combinations of the three indicators to form entry and exit criteria for long and short positions, aiming to capture the trending characteristics of short-term price movements.

Strategy Logic

The key trading logic of this strategy is based on several aspects:

Go long when price breaks above the Exponential Moving Average (EMA) line, and go short when it breaks below;
Go long when the MACD fast line is above the slow line, and go short when below;
Go long when William Indicator's fast MA line is above the slow MA line, and vice versa;
Use the combinations of these 3 scenarios as entry conditions;
Exit on reversal signals.

By combining EMA for overall trend direction and MACD for short-term momentum, this strategy can capture price trend moves at decent entry points for profits. Williams Indicator further helps avoid false breakouts by gauging overbought/oversold levels.

Advantages

This multi-indicator combo structure makes a typical short-term trend following strategy, with main edges like:

Triple cross verification to reduce false signals;
EMA for main trend, MACD for short-term momentum;
Williams Indicator avoids chasing tops or bottom fishing during volatile moves;
Reversal combo ensures risk control aligns with exits.

Risks

There are also major risks to note for this strategy:

The complex structure makes parameter tuning challenging;
Frequent short-term trades may lead to higher transaction costs;
Failure to detect true trend reversal points may result in losses.

The main mitigations are parameter optimization and stop loss to maximize profit combos and control max single trade loss.

Enhancement Opportunities

Main aspects to enhance the strategy:

Test more parameter combinations for optimum set;
Add more data feeds like volume for entry validation;
Employ dynamic or trailing stop loss to strengthen risk control;
Incorporate machine learning for detecting true reversals.

Conclusion

This MACD trend following intraday strategy effectively combines indicators for identifying short-term trends and managing risks. Further improvements on tuning parameters, setting stop loss levels and incorporating more data feeds can lift strategy win rate and profitability. The concepts are worth researching for strategy advancement.

Parameters

Name	Default	What it controls
v_input_3_close	0	Source: close \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4
v_input_4	50	Volume MA Period
v_input_5	12	Fast Length
v_input_6	26	Slow Length
v_input_int_7	9	Signal Smoothing
v_input_string_1	0	Oscillator MA Type: EMA \| SMA
v_input_string_2	0	Signal Line MA Type: EMA \| SMA
v_input_int_8	34	w_length
v_input_13	5	Smoothed %R Length
v_input_14	13	Slow EMA Length
v_input_1	2011	(?Trading window)Start Year
v_input_int_1	true	Start Month
v_input_int_2	true	Start Day
v_input_2	2050	Finish Year
v_input_int_3	12	Finish Month
v_input_int_4	31	Finish Day
v_input_float_1	true	(?Trading Options)Leverage (if applicable)
v_input_bool_1	false	Reinvest profit
v_input_float_2	20	Reinvest percentage
v_input_int_5	14	(?Daily ATR)ATR period
v_input_float_3	5	% ATR to use for SL / PT
v_input_float_4	20	(?VIX Volatility Index)VIX Threshold for entry
v_input_int_6	200	(?Moving Averages)EMA
v_input_7	#2962FF	(?Color Settings)MACD Line
v_input_8	#FF6D00	Signal Line
v_input_9	#26A69A	(?Histogram)Above Grow
v_input_10	#B2DFDB	Fall
v_input_11	#FFCDD2	Below Grow
v_input_12	#FF5252	Fall

Source Pine Script

/*backtest
start: 2023-11-18 00:00:00
end: 2023-12-18 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © platsn

//@version=5
strategy("MACD Willy Strategy", overlay=true, pyramiding=1, initial_capital=10000) 

// ******************** Trade Period **************************************
startY = input(title='Start Year', defval=2011, group = "Trading window")
startM = input.int(title='Start Month', defval=1, minval=1, maxval=12, group = "Trading window")
startD = input.int(title='Start Day', defval=1, minval=1, maxval=31, group = "Trading window")
finishY = input(title='Finish Year', defval=2050, group = "Trading window")
finishM = input.int(title='Finish Month', defval=12, minval=1, maxval=12, group = "Trading window")
finishD = input.int(title='Finish Day', defval=31, minval=1, maxval=31, group = "Trading window")
timestart = timestamp(startY, startM, startD, 00, 00)
timefinish = timestamp(finishY, finishM, finishD, 23, 59)
// t1 = time(timeframe.period, "0945-1545:23456") 
// window = time >= timestart and time <= timefinish and t1 ? true : false 
// t2 = time(timeframe.period, "0930-1555:23456")
// window2 = time >= timestart and time <= timefinish and t2 ? true : false 

leverage = input.float(1, title="Leverage (if applicable)", step=0.1, group = "Trading Options")
reinvest = input.bool(defval=false,title="Reinvest profit", group = "Trading Options")
reinvest_percent = input.float(defval=20, title = "Reinvest percentage", group="Trading Options")
// entry_lookback = input.int(defval=10, title="Lookback period for entry condition", group = "Trading Options")

// -------------------------------------------- Data Source --------------------------------------------

src = input(title="Source", defval=close)

// ***************************************************************************************************** Daily ATR *****************************************************
atrlen = input.int(14, minval=1, title="ATR period", group = "Daily ATR")
iPercent = input.float(5, minval=1, maxval=100, step=0.1, title="% ATR to use for SL / PT", group = "Daily ATR")
 
percentage = iPercent * 0.01
datr = request.security(syminfo.tickerid, "1D", ta.rma(ta.tr, atrlen))
datrp = datr * percentage

// plot(datr,"Daily ATR")
// plot(datrp, "Daily % ATR")

//*********************************************************** VIX volatility index ****************************************

VIX = request.security("BTC_USDT:swap", timeframe.period, close)
vix_thres = input.float(20.0, "VIX Threshold for entry", step=0.5, group="VIX Volatility Index")

// ************************************************ Volume ******************************************************

vol_len = input(50, 'Volume MA Period')
avg_vol = ta.sma(volume, vol_len)

//-------------------------------------------------------- Moving Average ------------------------------------

emalen1 = input.int(200, minval=1, title='EMA', group= "Moving Averages")
ema1 = ta.ema(src, emalen1)

// ------------------------------------------ MACD ------------------------------------------
// Getting inputs
fast_length = input(title="Fast Length", defval=12)
slow_length = input(title="Slow Length", defval=26)
signal_length = input.int(title="Signal Smoothing",  minval = 1, maxval = 50, defval = 9)
sma_source = input.string(title="Oscillator MA Type",  defval="EMA", options=["SMA", "EMA"])
sma_signal = input.string(title="Signal Line MA Type", defval="EMA", options=["SMA", "EMA"])
// Plot colors
col_macd = input(#2962FF, "MACD Line  ", group="Color Settings", inline="MACD")
col_signal = input(#FF6D00, "Signal Line  ", group="Color Settings", inline="Signal")
col_grow_above = input(#26A69A, "Above   Grow", group="Histogram", inline="Above")
col_fall_above = input(#B2DFDB, "Fall", group="Histogram", inline="Above")
col_grow_below = input(#FFCDD2, "Below Grow", group="Histogram", inline="Below")
col_fall_below = input(#FF5252, "Fall", group="Histogram", inline="Below")
// Calculating
fast_ma = sma_source == "SMA" ? ta.sma(src, fast_length) : ta.ema(src, fast_length)
slow_ma = sma_source == "SMA" ? ta.sma(src, slow_length) : ta.ema(src, slow_length)
macd = fast_ma - slow_ma
signal = sma_signal == "SMA" ? ta.sma(macd, signal_length) : ta.ema(macd, signal_length)
hist = macd - signal

// ---------------------------------------- William %R --------------------------------------
w_length = input.int(defval=34, minval=1)
w_upper = ta.highest(w_length)
w_lower = ta.lowest(w_length)

w_output = 100 * (close - w_upper) / (w_upper - w_lower)

fast_period = input(defval=5, title='Smoothed %R Length')
slow_period = input(defval=13, title='Slow EMA Length')

w_fast_ma = ta.wma(w_output,fast_period)
w_slow_ma = ta.ema(w_output,slow_period)



// ------------------------------------------------ Entry Conditions ----------------------------------------

L_entry1 = close > ema1 and hist > 0 and w_fast_ma > w_slow_ma 
S_entry1 = close < ema1 and hist < 0 and w_fast_ma < w_slow_ma 

// -------------------------------------------------- Entry -----------------------------------------------
strategy.initial_capital = 50000
profit = strategy.netprofit
trade_amount = math.floor(strategy.initial_capital*leverage / close) 

if strategy.netprofit > 0 and reinvest
    trade_amount := math.floor((strategy.initial_capital+(profit*reinvest_percent*0.01))*leverage / close) 
else
    trade_amount := math.floor(strategy.initial_capital*leverage/ close) 


if L_entry1 //and window
    strategy.entry("Long", strategy.long, trade_amount)

if S_entry1 //and window
    strategy.entry("Short", strategy.short, trade_amount)

// --------------------------------------------------- Exit Conditions -------------------------------------

L_exit1 = hist < 0 and w_fast_ma < w_slow_ma and w_fast_ma < -20
S_exit1 = hist > 0 and w_fast_ma > w_slow_ma and w_fast_ma > -80

// ----------------------------------------------------- Exit ---------------------------------------------

if L_exit1 //and window2
    strategy.close("Long")
    
if S_exit1 //and window2
    strategy.close("Short")

// if time(timeframe.period, "1530-1600:23456")
//     strategy.close_all()

Published by ChaoZhang on the FMZ strategy square · last modified 2023-12-19. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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