Moving Average Trading: How to Use SMA and EMA

Moving average trading means using the average price of the last few periods, drawn as a line on the chart, to judge the direction of a trend and to time entries and exits. The line smooths out daily noise, so a rising average suggests an uptrend and a falling one a downtrend, and many traders act when the price, or a faster average, crosses it. It is one of the simplest tools of technical analysis, but it always reacts after the price has moved, so it describes the trend rather than predicting it.

In brief

• A moving average is the average closing price over a fixed number of periods, recalculated each period, so the line moves along with the chart.
• The simple moving average (SMA) weights every price equally, while the exponential moving average (EMA) gives more weight to recent prices and reacts faster.
• The most common signal is a crossover: a fast average crossing above a slow one is read as bullish, and crossing below as bearish.
• A review of 92 modern studies of technical analysis found 58 with positive results, 24 with negative results and 10 mixed, but many had problems such as data snooping and ignored costs.
• Moving averages lag the price and give false signals in sideways markets, so they work best inside a written plan with a stop loss and a limit on risk.

In this article · 11 min read

1. What a moving average is
2. How moving average trading works, step by step
3. What the research says about moving averages
4. Moving averages in crypto
5. Advantages and limits
6. Where this fits: averages, rules and automation
7. How to start, step by step
8. Checklist before acting on a moving average
9. Who it is for
10. Key terms
11. Frequently asked questions
12. Sources

What a moving average is

StockCharts' ChartSchool puts it simply: moving averages smooth the price data to form a trend-following indicator, and a moving average does not predict price direction but defines the current direction, with a lag because it is based on past prices. IG's glossary gives the same idea in other words: a technical indicator that combines the prices of an asset over a set period and divides them by the number of data points, to give a single trend line.

A quick example makes it concrete. Take the last five daily closing prices of a coin: 100, 102, 101, 105 and 107. Their sum is 515, and 515 divided by 5 gives a 5-day average of 103. Tomorrow the oldest price drops out, the new close comes in, and the average is calculated again. That is why it "moves".

There are two main types:

• Simple moving average (SMA): the plain average of the closes over the period, as in the example. Every day counts the same.
• Exponential moving average (EMA): a weighted average that gives more importance to the most recent prices, so it turns sooner when the price changes direction.

The period is the number of candles in the average. Short periods, such as 9, 10 or 20, follow the price closely; long ones, such as 50, 100 or 200, move slowly and show the bigger trend. The 50-day and 200-day averages are the ones traders quote most often.

In Lazy Investor, Smart Investor (see the book on Amazon), John Bax lists moving averages among the five essential concepts of technical analysis, together with Japanese candlesticks, support, resistance and trendlines. He describes them as a way to smooth price data and identify trends, and notes that they can act as dynamic support or resistance levels.

How moving average trading works, step by step

The classic moving average trading strategy is the crossover, which John Bax describes in the same book: one short average and one longer average, with a buy signal when the short one crosses above the long one, often called a "golden cross", and a sell signal when it crosses below, often called a "death cross".

1. Choose the market and the timeframe. A daily chart of a liquid asset is the usual starting point; on a 5-minute chart, signals come much more often and are noisier.
2. Choose two periods. A fast one and a slow one, for example 50 and 200 days for the long-term trend, or a 9 and a 21 EMA for shorter trades, as in the example John Bax gives.
3. Wait for the cross. The fast average crossing above the slow one suggests the recent trend has turned up; crossing below suggests it has turned down.
4. Confirm and plan the risk. Many traders wait for the candle to close, check the volume and look at nearby support and resistance levels before acting. The stop loss goes where the idea would be wrong.
5. Exit with a rule. Either at the next opposite cross, at a target, or at the stop loss, decided before the trade.

A second, simpler use is the price against one average: when the price is above a rising 200-day line, many traders treat the long-term trend as up, and they are more careful with buys when it is below a falling one.

What the research says about moving averages

Moving averages are among the most tested trading rules. One of the best-known studies, by Brock, Lakonishok and LeBaron in 1992, applied rules such as 1/50, 1/150, 5/150, 1/200 and 2/200 day averages to the Dow Jones Industrial Average from 1897 to 1986. As summarised in a review by the University of Illinois, days with a buy signal had an average daily return of 0.042%, about 12% per year, while days with a sell signal had an average of -0.025%, against an average day of 0.017%. Transaction costs were not taken into account.

That review, "The Profitability of Technical Analysis: A Review" by Cheol-Ho Park and Scott Irwin (AgMAS Project Research Report, October 2004), counted 92 modern studies of technical trading rules. 58 found positive results, 24 found negative results and 10 were mixed. The authors add an important warning: most of these studies had problems in how they were tested, such as data snooping (trying many rules until one fits the past), choosing the rules after the fact, and difficulties in measuring risk and transaction costs.

There is crypto evidence too, but it is recent and narrow. In a paper posted on arXiv on 11 February 2026, Tomasz Mroziewicz and Robert Ślepaczuk tested an EMA strategy on intraday Bitcoin data with a fee of 0.1% per transaction. In the out-of-sample period, the strategy performed similarly to simply holding Bitcoin, with a smaller drawdown, the largest fall from a peak. The break-even point was around 0.4% per transaction, which shows how much costs matter when a rule trades often.

In our experience, the same crossover settings rarely work equally well on two different coins, or on the same coin in two different years. That is why we treat any number in a backtest as a starting point to test, not as a result to expect.

In a press release dated 27 March 2018, the European Securities and Markets Authority (ESMA) reported that between 74% and 89% of retail accounts typically lose money on contracts for difference (CFDs), which are leveraged products. CFDs are not the same as crypto on a spot market, but the figure is a sober reminder of how often frequent traders lose.

Moving averages in crypto

Crypto trades 24 hours a day, seven days a week, so a "200-day" average covers 200 calendar days, weekends included, while on a stock market it counts only the trading sessions.

Volatility also changes the picture. A sharp move can push the price far above or below its average in hours, and a crossover can flip several times in a week when the market goes sideways. Each flip is a trade, a fee and often a small loss: this back-and-forth is called a whipsaw.

John Bax's view

In Lazy Investor, Smart Investor, John Bax draws a clear line between two ways of looking at a market: fundamental analysis looks at the "why" behind an asset's value, technical analysis at the "when" of price movements. Investors buy because they believe in an asset's intrinsic value; speculators care about the price movement. A moving average answers a "when" question, so it belongs to the speculator's toolbox, not to the long-term plan.

He adds a point that matters a lot in crypto: large coins such as Bitcoin and Ethereum, with high trading volumes, tend to form more consistent price patterns, so chart reading means more there. Small, thinly traded altcoins move erratically, and for those he points to a different approach based on blockchain data, called on-chain analysis.

Advantages and limits

What moving averages do well

• Simple and objective. Two people using the same 50-day SMA see the same line, which is not true of hand-drawn trendlines.
• Easy to write as a rule. A crossover can be defined exactly, which makes it easy to test on past data and to automate.

Where they fall short

• Lag. A moving average is a lagging indicator: it turns after the price has turned, so part of every move is missed at the start and given back at the end.
• False signals in sideways markets. Without a trend, the lines cross again and again, and each whipsaw costs money.
• No single best setting. Periods that worked in the past may not work in the future, and choosing them by looking back is the data snooping Park and Irwin warn about.
• Risk. A signal is not a promise. Trading on crossovers can lose money quickly, especially with leverage, which multiplies losses as well as gains.

Where this fits: averages, rules and automation

A moving average is most useful as part of a written plan: which signal you take, where the stop loss goes and how much you risk on each trade. Our article on risk management in trading shows how to size a position from the distance to the stop, and the guide to candlestick patterns helps you read the candle that makes the cross. Before you trade a crossover, write it down precisely and test it on past data, as described in our guide to backtesting a strategy.

Trend-following bots that enter when a trend starts and exit when it fades often rely on rules like these; our guide to the crypto trading bot explains the main families. Crypto Go Bot, which we built, works differently: it is a signal bot whose source is the Smart Money on-chain, not price averages, and it trades your own Kraken account with the take profit and the stop loss placed as real orders on the exchange. Trading always carries risk, and past results do not guarantee future ones.

How to start, step by step

1. Open a daily chart of a liquid coin, such as Bitcoin, on your exchange or a charting site.
2. Add a 50-period and a 200-period SMA, then a 9 and a 21-period EMA on a separate copy of the chart, and compare how quickly each turns.
3. Mark the past crosses of the last year and note what the price did afterwards, the good signals and the false ones.
4. Write one rule with its entry, exit, stop loss and position size.
5. Test it on past data, including fees, and then follow it on paper for a few weeks without real money.
6. If you go further, start with a small amount you can afford to lose, and keep a record of every trade.

Checklist before acting on a moving average

• I know which average I use, its type (SMA or EMA) and its period, and why.
• I have checked whether the market is trending or moving sideways.
• I know where my stop loss goes and how much I lose if it is hit.
• The amount is one I can afford to lose, because crypto is volatile and past results do not guarantee future ones.

Who it is for

Moving averages are useful to many people who look at charts, in different ways.

• Beginner learning to read charts: a 50 and a 200-period line make the trend visible at a glance, as long as you treat them as a description of the past, not a forecast.
• Long-term investor who buys regularly: a weekly or 200-day average can help you keep perspective during sharp falls, provided it does not turn your plan into frequent trading.
• Active trader with a written plan: crossovers give clear, testable rules for entries and exits, with a stop loss and a fixed limit on the risk per trade.
• User of an automated tool: knowing how averages and crossovers work helps you understand what a trend-following rule does, even if you never place a trade by hand.

Key terms

• Simple moving average (SMA): the plain average of the closing prices over a set number of periods.
• Exponential moving average (EMA): an average that gives more weight to recent prices, so it reacts faster.
• Crossover: the moment a fast average crosses a slow one, used by many traders as a signal.
• Golden cross: a short average, often the 50-day, crossing above a long one, often the 200-day.
• Death cross: a short average crossing below a long one, read as a bearish sign.
• Whipsaw: a series of quick, opposite signals in a sideways market, each one usually ending in a small loss.

Frequently asked questions

What is the best moving average for trading?

There is no single best one. The 50 and 200-period SMAs are the most watched for the long-term trend, and short EMAs such as 9 and 21 are popular for shorter trades; the right choice depends on your timeframe and has to be tested.

What is a golden cross?

A golden cross happens when a short moving average, often the 50-day, crosses above a long one, often the 200-day. Many traders read it as a sign that the long-term trend has turned up, but it usually arrives well after the turn.

Does moving average trading work in crypto?

Sometimes, in strong trends, and much less in sideways markets. A recent study on Bitcoin found an EMA strategy performed about like holding the coin, with smaller falls, and costs above roughly 0.4% per trade wiped out its gains.

Can I automate a moving average strategy?

Yes, because a crossover can be written as an exact rule. Test it on past data with fees first, and remember that past results do not guarantee future ones.

Sources

• Park and Irwin, The Profitability of Technical Analysis: A Review, AgMAS Project Research Report 2004-04, University of Illinois, October 2004
• Mroziewicz and Ślepaczuk, A novel approach to trading strategy parameter optimization, using double out-of-sample data and walk-forward techniques, arXiv, 11 February 2026
• StockCharts ChartSchool, Moving Averages: Simple and Exponential
• IG, Moving average definition
• ESMA, ESMA agrees to prohibit binary options and restrict CFDs to protect retail investors, 27 March 2018
• StockCharts TV, 5 Simple and Powerful Uses for Moving Averages, 12 June 2024
• Wikipedia, Moving average