Intraday Pivot Breakout Strategy

This strategy generates trading signals based on price breakouts within a specified time period. The main idea is to observe price movements during certain periods and use breakouts in price range to determine trend…

Pine ScriptBreakout Machine learning Trend following EMA ATR Pivots / S&R

Author: ChaoZhang
Complexity: Intermediate · 118 lines
Parameters: 6
Backtest bar: 1d · swing
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Logic

The strategy calculates the highest high and lowest low of price within a certain timeframe, known as pivot high and pivot low, to gauge price movements.

Specifically, it computes the highest high of past N bars as the pivot high and the lowest low of past M bars as the pivot low. A long signal is generated when the current bar's high breaks above the pivot high. A short signal is generated when the current bar's low breaks below the pivot low.

After entry, the strategy uses ATR for stop loss and intraday stop loss. It also closes all positions at a specific timeframe (e.g. 14:55).

The strategy effectively captures trends using simple price breakouts during certain periods, making it ideal for intraday trading. The logic is clear and easy to implement.

Advantages

Captures trend changes reliably using price breakouts
Simple implementation with basic OHLC data
Reasonable stop loss and intraday stop loss manage risks
Avoids overnight risks suitable for intraday trading
Few parameters easy to optimize

Risks and Mitigations

Potential lag, may miss early trend start

Adjust timeframe or combine other indicators for entry
More false signals when trend is unclear

Tune parameters, add filters like indicators, volume etc.
Higher capital costs for active intraday trading

Adjust position sizing, extend holding period
Reliance on parameter optimization

Adapt parameters to changing market conditions using machine learning etc.

Enhancement Opportunities

Test other price data like typical price, median price etc.
Add filters like volume, volatility
Try different parameter combinations
Incorporate trend indicators to determine direction
Auto-optimize parameters using machine learning
Expand to multiple timeframes for better entry

Conclusion

The strategy has a clear and concise logic, effectively capitalizing on price breakouts to capture short-term trends with good profit factors. With few tunable parameters easy for testing and optimization, it is well suited for intraday trading. While lag and false signals exist, they can be addressed through parameter tuning, adding filters etc. The strategy provides a robust breakout-based trading framework with ample optimization space.

Parameters

Name	Default	What it controls
v_input_1	10	leftbars
v_input_2	15	rightbars
v_input_int_1	150	PRICE CROSS EMA
v_input_float_1	3.2	_ATR LONG
v_input_float_2	3.2	_ATR SHORT
v_input_float_3	200	RISK

Source Pine Script

/*backtest
start: 2022-10-27 00:00:00
end: 2023-11-02 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//   ____________        _________           _____________
//  |____________|      ||________|          ||__________|
//       ||             ||        ||         ||
//       ||             ||________||         ||
//       ||     H E     ||________   U L L   ||       H A R T I S T
//       ||             ||        ||         ||
//       ||             ||________||         ||__________
//       ||             ||________|          ||__________|
  
//@version=5
// strategy("PIVOT STRATEGY [5MIN TF]",overlay=true ,commission_type = strategy.cash, commission_value = 30 , slippage = 2, default_qty_value = 60, currency = currency.NONE, pyramiding = 0)
leftbars = input(defval = 10)
rightbars = input(defval = 15)

// ═══════════════════════════ //
// ----------> INPUTS <------- //
// ═══════════════════════════ //

EMA1 = input.int(title='PRICE CROSS EMA', defval = 150, minval = 10 ,maxval = 400)
factor1 = input.float(title='_ATR LONG',defval = 3.2 , minval = 1 , maxval = 5 , step = 0.1, tooltip = "ATR TRAIL LONG")
factor2 = input.float(title='_ATR SHORT',defval = 3.2 , minval = 1 , maxval = 5 , step = 0.1, tooltip = "ATR TRAIL SHORT")
risk = input.float(title='RISK',defval = 200 , minval = 1 , maxval = 5000 , step = 50, tooltip = "RISK PER TRADE")

var initialCapital = strategy.equity
t = time(timeframe.period, '0935-1400:1234567')
time_cond = true

// ══════════════════════════════════ //
// -----------> EMA DATA <----------- //
// ══════════════════════════════════ //
ema1 = ta.ema(close, EMA1)

plot(ema1, color=color.new(color.yellow, 0), style=plot.style_linebr, title='ema1')

// ══════════════════════════════════ //
// --------> TRAIL DATA <------------ //
// ══════════════════════════════════ //
// *******Calculate LONG TRAIL data*****
ATR_LO = ta.atr(14)*factor1

// *******Calculate SHORT TRAIL data*****
ATR_SH = ta.atr(14)*factor2

longStop = close - ATR_LO
shortStop = close + ATR_SH

// Plot atr data
//plot(longStop, color=color.new(color.green, 0), style=plot.style_linebr, title='Long Trailing Stop')
//plot(shortStop , color=color.new(color.red, 0), style=plot.style_linebr, title='Short Trailing Stop')

// ══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════ //
// --------------------------------------------------------> PIVOT DATA <---------------------------------------------------------------------------------------------------- //
// ══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════ //

ph = ta.pivothigh(close,leftbars, rightbars)
pl = ta.pivotlow(close,leftbars, rightbars)

pvt_condition1 = not na(ph)

upper_price = 0.0
upper_price := pvt_condition1 ? ph : upper_price[1]

pvt_condition2 = not na(pl)

lower_price = 0.0
lower_price := pvt_condition2 ? pl : lower_price[1]

// Signals
long  = ta.crossover(high, upper_price + syminfo.mintick)
short = ta.crossunder(low, lower_price - syminfo.mintick)

plot(upper_price, color= close > ema1  ? color.green : na, style=plot.style_line, title='PH')

plot(lower_price,  color= close <  ema1  ? color.red : na, style=plot.style_line, title='PL')


// ══════════════════════════════════//
// --------> LONG POSITIONS <--------//
// ══════════════════════════════════//
//******barinstate.isconfirmed used to avoid repaint in real time*******

if ( long and strategy.opentrades==0 and barstate.isconfirmed and time_cond and close >= ema1 )
    strategy.entry(id= "Long" ,direction = strategy.long, comment = "B")
    
//plot(longStop , color=color.new(color.blue, 0), style=plot.style_linebr, title='long Stop')

if strategy.position_size > 0 
    strategy.exit("long tsl", "Long" , stop = longStop ,comment='S')
 

// ═════════════════════════════════════//
// --------> SHORT POSITIONS <--------- //
// ═════════════════════════════════════//
if ( short and strategy.opentrades==0 and barstate.isconfirmed and time_cond and close <= ema1 )
    strategy.entry(id = "Short" ,direction = strategy.short,  comment = "S") 

if strategy.position_size < 0
    strategy.exit("short tsl", "Short" ,  stop = shortStop ,comment='B')

// ════════════════════════════════════════════════//
// --------> CLOSE ALL POSITIONS BY 3PM <--------- //
// ════════════════════════════════════════════════//
strategy.close_all(when = hour == 14 and minute == 55)

// ════════════════════════════════════════//
// --------> MAX INTRADAY LOSS  <--------- //
// ════════════════════════════════════════//
// strategy.risk.max_intraday_loss(type = strategy.cash, value = risk)

Published by ChaoZhang on the FMZ strategy square · last modified 2023-11-03. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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