Honey Trend ATR Breakout Strategy

Pine ScriptBreakout Trend following Tools & templates EMA Bollinger Bands ATR ADX / DMI Pivots / S&R

Author: ChaoZhang
Complexity: Intermediate · 73 lines
Parameters: 12
Backtest bar: 1h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

The Honey Trend ATR Breakout Strategy is a medium-term breakout strategy based on ATR indicator and Bollinger Bands for trading signal generation. It mainly monitors the trend changes of stock prices within a certain width of upper and lower ATR channels. When prices break through the lower or upper rail, combined with trend filtering, it makes trading decisions.

Strategy Principle

The strategy consists of three main parts:

ATR Channel: Calculate the fluctuation range of stock prices through ATR indicator and form a channel up and down within this range. The channel width is controlled by ATR lookback period and ATRdivisor factor.
Bee Line: Take the midline of stock prices as the baseline. The calculation method of midline is: the average value of yesterday's high, low and close prices.
Trend Filtering: Calculate the price trend through DMI indicator and set signal cycle. When pricesig '>': pricesig[3], the trend is up. When pricesig '<' pricesig[3], the trend is down.

The specific logic for generating trading signals is:

Long signal: pricesig '>' pricesig[3] and price break through the lower rail of channel.

Short signal: pricesig '<' pricesig[3] and price break through the upper rail of channel.

No trading in other situations.

The strategy also sets stop profit and stop loss conditions to control trading risks.

Advantage Analysis

The Honey Trend ATR Breakout Strategy has the following advantages:

Use ATR indicator to calculate the fluctuation range of stock prices, which can dynamically capture market changes;
Combine the midline to evaluate the sideways of stock prices and set the channel breakout trading points to avoid chasing highs and killing lows;
DMI indicator is used to determine the trend and avoid trading against the trend, improving the win rate;
Set stop profit and stop loss conditions to control the risk of single trade;
The strategy parameters are flexible enough to optimize the strategy by adjusting the channel width, ATR cycle and other factors.

Risk Analysis

The strategy also has some risks:

Medium-term trading has relatively large fluctuations and high risks. Prudent money management is required.
ATR channel range calculation may be inaccurate when stock prices fluctuate sharply, which easily leads to wrong trades.
DMI indicator may also make mistakes in trend judgment, thus affecting the accuracy of trading signals.

In response to the above risks, parameters like ATR channel can be adjusted and signal cycles can be increased for optimization and improvement.

Optimization Directions

The strategy can be optimized in the following aspects:

Adjust ATR channel width by modifying atrDivisor up or down to compress or expand the channel range.
Adjust ATR lookback cycle parameter to change the sensitivity of channel to recent fluctuations.
Adjust trend signal cycle parameter to improve the accuracy of bullish and bearish trend judgments.
Add other indicators for multi-factor verification to improve signal quality.
Optimize stop profit and stop loss algorithms to improve risk control.

Conclusion

The Honey Trend ATR Breakout Strategy integrates the analysis of price fluctuation range and trend judgment indicators. While capturing market hotspots, it also controls trading risks. It is a flexible and adaptable quantitative strategy. This strategy can be continuously improved through parameter adjustment and signal optimization, with broad application prospects.

Parameters

Name	Default	What it controls
v_input_1	D	Pivot Timeframe
v_input_2	D	ATR Band Timeframe (Lower timeframe = wider bands)
v_input_3	13	ATR lookback (Lower = bands more responsive to recent price action)
v_input_4	2	ATR divisor (Lower = wider bands)
v_input_5	2	Momentum Period
v_input_6	20	Slow Period
v_input_7	5	Fast Period
v_input_8	3	Smoothing Period
v_input_9	4	Signal Period
v_input_10	50	Extreme Value
v_input_11	false	Take Profit (In Market MinTick Value)
v_input_12	100	Stop Loss (In Market MinTick Value)

Source Pine Script

/*backtest
start: 2023-11-01 00:00:00
end: 2023-11-30 23:59:59
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=2
strategy(title="Strategy - Bobo PATR Swing", overlay=true, default_qty_type = strategy.fixed, default_qty_value = 1, initial_capital = 10000)

// === STRATEGY RELATED INPUTS AND LOGIC ===
PivottimeFrame = input(title="Pivot Timeframe",  defval="D")
ATRSDtimeFrame = input(title="ATR Band Timeframe (Lower timeframe = wider bands)",  defval="D")
len = input(title="ATR lookback (Lower = bands more responsive to recent price action)",  defval=13)
myatr = atr(len)
dailyatr = request.security(syminfo.tickerid, ATRSDtimeFrame, myatr[1])
atrdiv = input(title="ATR divisor (Lower = wider bands)", type=float, defval=2)
pivot0 = (high[1] + low[1]  + close[1]) / 3
pivot = request.security(syminfo.tickerid, PivottimeFrame, pivot0)
upperband1 = (dailyatr / atrdiv) + pivot
lowerband1 = pivot - (dailyatr / atrdiv)
middleband = pivot

// == TREND CALC ===
i1=input(2, "Momentum Period", minval=1) //Keep at 2 usually
i2=input(20, "Slow Period", minval=1)
i3=input(5, "Fast Period", minval=1)
i4=input(3, "Smoothing Period", minval=1)
i5=input(4, "Signal Period", minval=1)
i6=input(50, "Extreme Value", minval=1)
hiDif = high - high[1]
loDif = low[1] - low
uDM = hiDif > loDif and hiDif > 0 ? hiDif : 0
dDM =  loDif > hiDif and loDif > 0 ? loDif : 0
ATR = rma(tr(true), i1)
DIu = 100 * rma(uDM, i1) / ATR
DId = 100 * rma(dDM, i1) / ATR
HLM2 =  DIu - DId
DTI = (100 * ema(ema(ema(HLM2, i2), i3), i4)) /  ema(ema(ema(abs(HLM2), i2), i3), i4)
signal = ema(DTI, i5)


// === RISK MANAGEMENT INPUTS ===
inpTakeProfit   = input(defval = 0, title = "Take Profit (In Market MinTick Value)", minval = 0)
inpStopLoss     = input(defval = 100, title = "Stop Loss (In Market MinTick Value)", minval = 0)

// === RISK MANAGEMENT VALUE PREP ===
// if an input is less than 1, assuming not wanted so we assign 'na' value to disable it.
useTakeProfit   = inpTakeProfit  >= 1 ? inpTakeProfit  : na
useStopLoss     = inpStopLoss    >= 1 ? inpStopLoss    : na

// === STRATEGY - LONG POSITION EXECUTION ===
enterLong = (((low<=lowerband1) and (close >lowerband1)) or ((open <= lowerband1) and (close > lowerband1))) and (strategy.opentrades <1) and (atr(3) > atr(50)) and (signal>signal[3])
exitLong = (high > middleband)
strategy.entry(id = "Long", long = true, when = enterLong) 
strategy.close(id = "Long", when = exitLong)

// === STRATEGY - SHORT POSITION EXECUTION ===
enterShort = (((high>=upperband1) and (close < upperband1)) or ((open >= upperband1) and (close < upperband1))) and (strategy.opentrades <1) and (atr(3) > atr(50)) and (signal<signal[3])
exitShort = (low < middleband)
strategy.entry(id = "Short", long = false, when = enterShort)
strategy.close(id = "Short", when = exitShort)

// === STRATEGY RISK MANAGEMENT EXECUTION ===
strategy.exit("Exit Long", from_entry = "Long", profit = useTakeProfit, loss = useStopLoss)
strategy.exit("Exit Short", from_entry = "Short", profit = useTakeProfit, loss = useStopLoss)

// === CHART OVERLAY ===
plot(upperband1, color=#C10C00, linewidth=3)
plot(lowerband1, color=#23E019, linewidth=3)
plot(middleband, color=#00E2E2, linewidth=3)
//plot(strategy.equity, title="equity", color=red, linewidth=2, style=areabr)

Published by ChaoZhang on the FMZ strategy square · last modified 2023-12-06. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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