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I’ve always been drawn to simplicity in trading. With so many technical indicators, AI bots, and complex momentum formulas competing for attention, one rule keeps appearing in books, forums, and interviews with experienced investors: the 200-day moving average.

This strategy is so familiar that many consider it too basic, and that is exactly why I decided to put it to the test.

I set out to see how this strategy performs on some of the biggest and most influential tech stocks in the U.S. over the past several years. This article breaks down my approach, results, and takeaways from a full backtest, with visuals and final comparisons that may surprise you.

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Why the 200-Day Moving Average?

The 200-day moving average (200DMA) is a long-term trend indicator. When a stock’s price is above its 200-day average, it’s generally considered to be in an uptrend, and when it’s below, a downtrend.

This has given rise to a simple rule followed by many traders:

Buy when the price crosses above the 200DMA, and sell when it crosses below.

The logic is based on staying aligned with the trend and avoiding large drawdowns by exiting early during major downturns.

Setting Up the Experiment

To fairly evaluate the strategy, I needed to define:

• Which stocks to test

• The historical time range

• How the strategy logic would be applied

I selected 10 tech-focused stocks with high liquidity, popularity, and long trading histories on the U.S. exchanges. These were:

AAPL, MSFT, GOOGL, AMZN, NVDA, TSLA, META, AMD, CRM, INTC

The test period began on 1 January 2018 and ended on 30 June 2025, giving over 7 years of market data, which included a bull market, the COVID-19 crash, rate hikes, and the AI stock surge.

I used daily closing prices and built a strategy that held the stock only when the price was above the 200DMA. While the stock was held, returns were accumulated. Otherwise, the capital sat idle.

A Closer Look at AAPL

To start, I focused on one stock, Apple (AAPL), to inspect the pattern and logic visually.

In this chart, you can see how the 200DMA strategy compared to simply holding the stock.

Periods where the line diverges from the buy-and-hold curve are where the strategy exited the position, typically during downturns or sharp consolidations.

Full Portfolio Backtest

Next, I expanded the strategy to all 10 tickers. Each stock was tested independently, not as a portfolio. This means the strategy either held a given stock or was fully in cash based on that individual price/MA relationship.

The results below show the performance of the 200DMA strategy versus a basic buy-and-hold for each company.

A few key patterns stood out:

• It significantly limited downside risk in high-volatility names like TSLA, AMD, and CRM, though sometimes at the cost of upside.

• In trending markets, such as NVDA’s sharp rise after 2022, the strategy kept pace or even outperformed.

• For more stable companies like MSFT, GOOGL, and META, the strategy showed moderate returns with smoother equity curves.

While the strategy didn’t outperform everywhere, it offered a useful trade-off between return and risk management, especially during sharp market reversals or long sideways periods.

Buy and Sell Signal Visualizations

To better understand the timing of trades, I generated a second grid of charts showing when buy (green) and sell (red) signals occurred based on the 200DMA crossovers.

These visuals were key in revealing how often whipsaws occurred, that is, signals that quickly reversed.

In some stocks, the 200DMA gave just a handful of clear entry and exit points. In others, like AMD, signals came more frequently, especially during sideways price action.

Performance Summary

Here’s a distilled table of the total return performance between the two strategies, measured over the 7-year test period:

For example:

• NVDA returned over 2700% in buy-and-hold, while the 200DMA version captured about 2900%.

• AMD and TSLA, which had more volatility, saw a significant reduction in return using the 200DMA approach.

• Apple and Microsoft showed slightly lower returns, but with less exposure to large drops.

To complete the picture, I looked at risk-adjusted performance using the Sharpe Ratio.

Some stocks saw a clear improvement in Sharpe Ratio using the 200DMA strategy, a sign that while total returns may have been lower, the risk taken to achieve those returns was also reduced.