Gem Forest 1 Minute Breakout Strategy

Pine ScriptBreakout Mean reversion Trend following RSI EMA SMA ATR

Author: ChaoZhang
Complexity: Intermediate · 70 lines
Parameters: 7
Backtest bar: 1d · swing
Tested on: BTC/USDT · futures

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Overview

The Gem Forest 1 Minute Breakout Strategy is a quantitative trading strategy that aims to capture breakout signals within a 1-minute timeframe to realize quick profits. This strategy incorporates multiple indicators like moving averages, ATR, RSI to generate trading signals and achieve higher risk-reward ratios over short holding periods.

Strategy Logic

This strategy mainly uses the following elements to form trade signals:

ATR Indicator - Calculates average true range to set price channels;
Moving Average Indicators - Compute fast EMA and slow EMA to generate golden cross/dead cross signals;
RSI Indicator - Calculate fast and slow RSI to determine overbought/oversold area;
Price-Channel Relationship - Generates trade signals when price breaks out of the channels.

Specifically, the strategy computes N-period average of ATR, fast EMA, slow EMA, fast RSI and slow RSI. Combining the conditions of price breaking ATR channel, EMA golden cross, and RSI reaching extreme levels, the strategy sends out buy or sell signals.

Advantage Analysis

The main advantages of this strategy are:

Captures short-term price trends;
Responds swiftly, suitable for high frequency trading;
More reliable with multiple filtered indicators;
Parametric for users to optimize.

Risk Analysis

There are also some risks:

High risks in short-term trading, strict stop loss needed;
Improper parameter optimization leads to overfitting;
High trading frequency increases costs.

To control risks, stop loss should be implemented, and parameters need proper backtests to avoid overfitting. Moreover, adjusting trade frequency to control costs.

Optimization Directions

The strategy can be optimized through:

Test parameters settings over shorter periods (5-min, 15-min);
Add more filtering indicators like volume to improve signal quality;
Optimize ATR channel and moving average parameters to find best parameter combinations.

Conclusion

The Gem Forest 1 Minute Breakout Strategy focuses on capturing short-term trends by filtering with multiple indicators, featuring fast response and high risk-reward characteristics. It can be adapted to users' risk preferences through parameter optimization for better results. However, users should control trading risks via strict stop loss, reasonable trade frequencies etc. Overall, this strategy suits investors with certain quant trading knowledge and risk tolerance for short-term trading.

Parameters

Name	Default	What it controls
v_input_int_1	14	ATR Period
v_input_float_1	true	ATR Multi
v_input_string_1	0	ATR Smoothing: WMA \| SMA \| EMA \| RMA
v_input_int_2	21	Fast EMA
v_input_int_3	65	Slow EMA
v_input_int_4	25	Fast RSI Length
v_input_int_5	100	Slow RSI Length

Source Pine Script

/*backtest
start: 2023-02-12 00:00:00
end: 2024-02-18 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5
strategy("Gem Forest 1 Dakika Scalp", overlay=true)

source = close
atrlen = input.int(14, "ATR Period")
mult = input.float(1, "ATR Multi", step=0.1)
smoothing = input.string(title="ATR Smoothing", defval="WMA", options=["RMA", "SMA", "EMA", "WMA"])

ma_function(source, atrlen) => 
    if smoothing == "RMA"
        ta.rma(source, atrlen)
    else
        if smoothing == "SMA"
            ta.sma(source, atrlen)
        else
            if smoothing == "EMA"
                ta.ema(source, atrlen)
            else
                ta.wma(source, atrlen)

atr_slen = ma_function(ta.tr(true), atrlen)
upper_band = atr_slen * mult + close
lower_band = close - atr_slen * mult

ShortEMAlen = input.int(21, "Fast EMA")
LongEMAlen = input.int(65, "Slow EMA")
shortSMA = ta.ema(close, ShortEMAlen)
longSMA = ta.ema(close, LongEMAlen)
RSILen1 = input.int(25, "Fast RSI Length")
RSILen2 = input.int(100, "Slow RSI Length")
rsi1 = ta.rsi(close, RSILen1)
rsi2 = ta.rsi(close, RSILen2)
atr = ta.atr(atrlen)

RSILong = rsi1 > rsi2
RSIShort = rsi1 < rsi2

longCondition = open < lower_band
shortCondition = open > upper_band
GoldenLong = ta.crossover(shortSMA,longSMA)
Goldenshort = ta.crossover(longSMA,shortSMA)

plotshape(shortCondition, title="Sell Label", text="Sell", location=location.abovebar, style=shape.labeldown, size=size.tiny, color=color.new(color.red, 0), textcolor=color.white)
plotshape(longCondition, title="Buy Label", text="Buy", location=location.belowbar, style=shape.labelup, size=size.tiny, color=color.new(color.green, 0), textcolor=color.white)
plotshape(Goldenshort, title="Golden Sell Label", text="Golden Crossover Short", location=location.abovebar, style=shape.labeldown, size=size.tiny, color=color.new(color.blue, 0), textcolor=color.white)
plotshape(GoldenLong, title="Golden Buy Label", text="Golden Crossover Long", location=location.belowbar, style=shape.labelup, size=size.tiny, color=color.new(color.yellow, 0), textcolor=color.white)

if (longCondition)
    stopLoss = low - atr * 2
    takeProfit = high + atr * 5
    strategy.entry("long", strategy.long)

if (shortCondition)
    stopLoss = high + atr * 2
    takeProfit = low - atr * 5
    strategy.entry("short", strategy.short)

plot(upper_band)
plot(lower_band)
plot(shortSMA, color = color.red)
plot(longSMA, color = color.yellow)

Published by ChaoZhang on the FMZ strategy square · last modified 2024-02-19. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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