Dual Moving Average Golden Cross Trend Trading Strategy

Pine ScriptTrend following Breakout Volatility EMA

Author: ChaoZhang
Complexity: Starter · 55 lines
Parameters: 6
Backtest bar: 1d · swing
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

The Dual Moving Average Golden Cross Trend Trading strategy calculates price with dual moving averages (DEMA and TEMA) and detects their crossovers to identify overall market trends and generate trading signals. This strategy combines trend indicators and breakout signals to track medium-to-long term trends and capture signals at early trend stages.

Strategy Logic

The core indicators of this strategy are a 200-period DEMA and two TEMAS with periods of 9 and 50. The DEMA judges overall trends while TEMA crossovers generate trading signals.

When the short-term 9-period TEMA crosses above the medium-term 50-period TEMA, a buy signal is generated, indicating an uptrend start for short-term moves. Traders can go long. When the 9-period TEMA crosses below the 50-period TEMA, a sell signal is triggered, showing a short-term downtrend beginning. Traders can go short.

To filter false breakouts, the strategy adds a DEMA filter so that TEMA crossover signals are only valid when prices are above the DEMA. This captures signals when trends start.

Advantage Analysis

This strategy combines the strengths of moving averages for trend analysis and crossovers for signal generation across short- and medium-term timeframes. It considers two types of indicators for robust signals and less noise.

Adding the DEMA filter enhances signal reliability by avoiding unfavorable market conditions like consolidations where signals underperform. This greatly cuts losses.

Risk Analysis

Though the stable parameter settings of this strategy allow solid historical performance, some risks may exist in specific market environments:

Violent price swings may cause lagging crossover signals, unable to reflect timely prices. This can cause missed entry timing and stop loss levels.
The long DEMA period may fail to convert signals quickly enough when trends reverse. This can amplify losses.
The strategy is more suited for medium-to-long term trading. Insufficient profits may occur with short-term trades.

Optimization Directions

Further enhancements for the strategy include:

Optimize DEMA and TEMA parameters for better adaptation across products and market regimes. More combinations can be tested to find the optimal settings.
Add more filters with indicators like volume and volatility to reinforce signal quality.
Add stop losses when prices breach the DEMA to control loss.
Optimize stop loss and take profit points based on typical price swing ranges.

Conclusion

The Dual Moving Average Golden Cross Trend Trading Strategy comprehensively considers multiple timeframe trends and crossover signals. The additional filter improves signal effectiveness to track medium-to-long trends for timely opportunity captures and avoid low-efficiency trades. This stable strategy suits various markets regimes and offers a robust algorithm worth long-term deployment. Future optimizations on parameters and modules can further boost its stability and profitability.

Parameters

Name	Default	What it controls
v_input_1	true	Porcentaje de Riesgo (%)
v_input_2	30	Stop Loss (pips)
v_input_3	90	Take Profit (pips)
v_input_4	200	Longitud DEMA
v_input_5	9	Longitud TEMA 9
v_input_6	50	Longitud TEMA 50

Source Pine Script

/*backtest
start: 2023-02-11 00:00:00
end: 2024-02-17 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5
strategy("Estrategia de Trading", shorttitle="DEMA+TEMA", overlay=true)

// Parámetros de la estrategia
risk_percentage = input(1, title="Porcentaje de Riesgo (%)") / 100
stop_loss_pips = input(30, title="Stop Loss (pips)")
take_profit_pips = input(90, title="Take Profit (pips)")
length_DEMA = input(200, title="Longitud DEMA")
length_TEMA_9 = input(9, title="Longitud TEMA 9")
length_TEMA_50 = input(50, title="Longitud TEMA 50")

// Indicadores
dema = ta.ema(close, length_DEMA)
tema_9 = ta.ema(close, length_TEMA_9)
tema_50 = ta.ema(close, length_TEMA_50)
tema_9_50_cross_up = ta.crossover(tema_9, tema_50)
tema_9_50_cross_down = ta.crossunder(tema_9, tema_50)

// Riesgo y gestión de operaciones
risk_per_trade = strategy.equity * risk_percentage
stop_loss = close - stop_loss_pips * syminfo.mintick
take_profit = close + take_profit_pips * syminfo.mintick

// Condiciones de entrada
long_condition = close > dema and tema_9_50_cross_up
short_condition = close > dema and tema_9_50_cross_down

// Estrategia de Trading
if (long_condition)
    strategy.entry("Buy", strategy.long)
    strategy.exit("Sell", from_entry="Buy", loss=stop_loss, profit=take_profit)

if (short_condition)
    strategy.entry("Sell", strategy.short)
    strategy.exit("Cover", from_entry="Sell", loss=stop_loss, profit=take_profit)

// Líneas de visualización
hline(0, "Zero Line", color=color.gray)
plot(dema, color=color.blue, title="DEMA")
plot(tema_9, color=color.green, title="TEMA 9")
plot(tema_50, color=color.red, title="TEMA 50")

// Triángulos
plotshape(tema_9_50_cross_up, color=color.green, style=shape.triangleup, location=location.belowbar, size=size.small)
plotshape(tema_9_50_cross_down, color=color.red, style=shape.triangledown, location=location.abovebar, size=size.small)

Published by ChaoZhang on the FMZ strategy square · last modified 2024-02-18. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

Build this with AgenKit

A spec is not a trading system. Paste this into your coding agent and AgenKit runs a specialist team — architecture, test-first build, risk gates, review — with paper trading on by default.

in Claude Code, Cursor, Codex & 4 more

/agenkit build a production-grade trading bot with a backtest engine, risk controls and paper trading by default from strategies/Dual-Moving-Average-Golden-Cross-Trend-Trading-Strategy.md

npx agenkit install engineering-kit in your project
Paste the command into your agent and approve each phase
Get tests, backtest, risk controls and a paper-trading switch

Get AgenKit How /agenkit works

Understand it first

Before you run this, read the lesson behind the idea and how to backtest it honestly. Specs like this one are the survivors of an unknown number of trials; deflate their results accordingly.