Dual EMA Golden Cross Profit Taking Strategy

This strategy calculates two groups of EMA indicators with different parameters and sets the buy signal when the two groups of EMA indicators have a golden cross and the sell signal when another two groups of EMA…

Pine ScriptTrend following Scalping Tools & templates MACD EMA

Author: ChaoZhang
Complexity: Starter · 62 lines
Parameters: 4
Backtest bar: 1d · swing
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Principle

The strategy uses 4 EMA indicators, EMA1 with a period of 9, EMA2 with a period of 26, EMA3 with a period of 100, and EMA4 with a period of 55. The buy signal is set when EMA1 crosses over EMA2, indicating that the short-term EMA crosses over the long-term EMA, which is a typical golden cross signal. The sell signal is set when EMA3 crosses below EMA4, which is a death cross signal. This allows fast entry when the short-term EMA indicator has a golden cross and fast stop loss when the long-term EMA indicator has a death cross to achieve efficient short-term trading.

Advantage Analysis

Use dual EMA cross for fast entry and exit to quickly lock short-term profits
Clear and simple trading signals, easy to implement
Adjustable parameters to suit different markets
Large profit range, suitable for short-term scalping trading

Risk Analysis

Dual EMA cross may have false signals, needs to be filtered with other indicators
Improper EMA parameter settings may cause too sensitive or dull
Need to closely monitor larger cycles for timely profit-taking

Optimization Direction

Can add MACD, KDJ and other indicators for signal filtering to improve signal accuracy
Can test more combinations to find the optimal EMA parameters
Can set moving stop loss to lock in profits

Summary

Overall, this is a very typical and effective short-term trading strategy. The advantages are fast entry and exit, suitable for scalping and large profit range. There are also some risks that need attention and prevention. With proper parameter adjustment and assistance of other indicators for signal filtering, it can become a very practical short-term trading strategy.

Parameters

Name	Default	What it controls
v_input_int_1	9	EMA_L
v_input_int_2	26	EMA_L2
v_input_int_3	100	EMA_S
v_input_int_4	55	EMA_S2

Source Pine Script

/*backtest
start: 2023-01-05 00:00:00
end: 2024-01-11 00:00:00
period: 1d
basePeriod: 1h
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/
// © YukalMoon

//@version=5
strategy(title="EMA SCALPEUR", overlay=true, initial_capital = 1000)


//// input controls

EMA_L = input.int (title = "EMA_L", defval = 9, minval = 1, maxval = 100, step =1)
EMA_L2 = input.int (title = "EMA_L2", defval = 26, minval = 1, maxval = 100, step =1)
EMA_S = input.int (title = "EMA_S", defval = 100, minval = 1, maxval = 100, step =1)
EMA_S2 = input.int (title = "EMA_S2", defval = 55, minval = 1, maxval = 100, step =1)


/// mise en place de ema

shortest = ta.ema(close, 9)
short = ta.ema(close, 26)
longer = ta.ema(close, 100)
longest = ta.ema(close, 55)

plot(shortest, color = color.red)
plot(short, color = color.orange)
plot(longer, color = color.aqua)
plot(longest, color = color.yellow)

plot(close)

//// trading indicators

EMA1 = ta.ema (close,EMA_L)
EMA2 = ta.ema (close,EMA_L2)
EMA3 = ta.ema (close, EMA_S)
EMA4 = ta.ema (close, EMA_S2)


buy = ta.crossover(EMA1, EMA2)
//sell = ta.crossunder(EMA1, EMA2)

buyexit = ta.crossunder(EMA3, EMA4)
//sellexit = ta.crossover(EMA3, EMA4)

/////strategy

strategy.entry ("long", strategy.long, when = buy, comment = "EXIT-LONG")
//strategy.entry ("short", strategy.short, when = sell, comment = "ENTER-SHORT")


///// market exit

strategy.close ("long", when = buyexit, comment = "ENTER-LONG")
//strategy.close ("short",  when = sellexit, comment = "EXIT-SHORT")

Published by ChaoZhang on the FMZ strategy square · last modified 2024-01-12. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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