SMA Crossover Strategy with Pine Script Code, Backtest & Stops

Simple Moving Average Crossover Strategy [algo_aakash] | Full Code Inside

Welcome to a foundational guide on implementing a Simple Moving Average Crossover Strategy. This classic approach uses two moving averages to identify potential trend changes and generate trading signals. The following article explains the core logic and provides a complete, ready-to-use Pine Script strategy for your backtesting toolkit.

Understanding the Crossover Mechanics

The strategy’s core is built upon the relationship between a fast and a slow moving average. A fast MA, like a 50-period SMA, reacts quickly to recent price changes. A slow MA, such as a 200-period SMA, represents the longer-term trend. A bullish crossover occurs when the fast MA crosses above the slow MA, suggesting upward momentum and a potential long entry signal. Conversely, a bearish crossover, where the fast MA crosses below the slow MA, indicates weakening momentum and a potential short entry signal.

Implementing a Robust Trading System

To transform this concept into a viable strategy, clear entry and exit rules are defined. The code will enter a long position on a bullish crossover and exit that position on a subsequent bearish crossover, which also serves as the signal to enter a short trade. For risk management, a stop-loss and take-profit percentage are incorporated. This ensures each trade has a predefined risk-reward ratio, protecting your capital from excessive losses during unexpected market moves and systematically locking in profits.

In conclusion, the Simple Moving Average Crossover Strategy offers a systematic, rules-based method for identifying trends. While it may produce false signals in ranging markets, it excels in capturing sustained directional moves. The provided code gives you a solid foundation to backtest, optimize, and build upon for your own trading journey.

//@version=5
strategy("Simple Moving Average Crossover Strategy [algo_aakash] | Full Code Inside", overlay=true)

// Author: algo_aakash

// Input parameters
fastLength = input.int(50, "Fast MA Length")
slowLength = input.int(200, "Slow MA Length")
stopLossPerc = input.float(1.0, "Stop Loss %") / 100
takeProfitPerc = input.float(2.0, "Take Profit %") / 100

// Calculate Moving Averages
fastMA = ta.sma(close, fastLength)
slowMA = ta.sma(close, slowLength)

// Plot MAs on chart
plot(fastMA, "Fast MA", color=color.blue)
plot(slowMA, "Slow MA", color=color.red)

// Crossover Conditions
longCondition = ta.crossover(fastMA, slowMA)
shortCondition = ta.crossunder(fastMA, slowMA)

// Strategy Entry and Exit Logic
if (longCondition)
    strategy.entry("Long", strategy.long)
    strategy.exit("Long Exit", "Long", stop=close * (1 - stopLossPerc), limit=close * (1 + takeProfitPerc))

if (shortCondition)
    strategy.entry("Short", strategy.short)
    strategy.exit("Short Exit", "Short", stop=close * (1 + stopLossPerc), limit=close * (1 - takeProfitPerc))