How to use moving averages in your trading to find better entries and exits

• One of the most well-known technical tools, moving averages are an indicator used as part of technical analysis, typically coming in three types: simple, exponential, and weighted
• Smoothing volatile price data into one easy-to-follow line, moving averages are typically used to show the general market trend and direction, with different period lengths determining how many candles are considered for the calculation
• Most commonly, a signal is considered valid when price action crosses and closes above or below a moving average, while other strategies can rely on two moving averages to cross

Popularized in the 1920s by Charles Dow, creator of the Dow Jones Industrial Average, moving averages are a technical analysis tool used to smooth price action and report the average price of a financial asset.

One of, if not the most commonly used, indicators worldwide, its calculation aims to simplify volatile price action into one easy-to-follow average plotted as a line directly on the chart.

While not used exclusively within the realms of financial markets, moving averages are a valuable tool in determining overall market direction and the strength of an existing trend.

Compared to other technical indicators, moving averages are relatively simple in design, but there are still a few things to know before applying them to your trading.

While there are many different types of moving averages, each using different calculation methods, traders typically rely on just three: simple, exponential and weighted.

• Simple moving average (SMA): Straightforward by design, an SMA sums the closing price over a set number of periods and divides by the same number. For example, a 10-period SMA is the average of the least 10 days’ closing prices. Crucially, the calculation is unweighted, meaning each data point is worth the same.
• Exponential moving average (EMA): Using a more complex formula, an EMA also sums the closing price over a set number of periods and divides by the same number, but more recent data points are weighted to give more significance to the final average. The influence of each data point diminishes exponentially as new data is collected, hence the name.
• Weighted moving average (WMA): A middle ground between the responsiveness of EMAs and the stability of SMAs, WMAs follow the same formula in averaging the closing price over a set number of periods. While similarly to EMAs, most recent data is weighted higher, WMAs have a linear-weighting system, not exponential, where each data point is multiplied by a specific weighting factor.

While much common ground is shared between the three types, simple moving averages are better at gauging longer-term market direction since all data points are treated the same, helping filter out short-term market noise.

Otherwise, and since exponential moving averages put more weight on the most recent data points, EMAs are more responsive to short-term price movements, helping traders react quicker to volatile market conditions.

Weighted moving averages can be considered a middle-ground between the two, often proving less temperamental than EMAs, but more reactive than SMAs, which could lead to better entries while avoiding false signals.

We’ve established that moving averages often come in three types, but there’s also a choice of how many data points the calculations should include, otherwise known as the period.

• Short-term: Using a small number of data points, short-term moving averages are used to identify emerging trends within price action. While the 5-, 10-, and 20-period moving averages are amongst the most common, it should be noted that the smaller the selected period, the more sensitive it is to recent price changes.
• Long-term: Calculated over a longer timeframe, typically 50, 100, or even 200 periods, long-term moving averages are best at filtering out noise and focusing on overarching market direction. While they are slower to react to recent price movements, owing to a larger number of averaged data points, they often paint a much smoother and more stable picture than their short-term counterparts. As such, these levels can usually be interpreted as more significant to market technicals.

In any case, traders will often use the same moving average periods, be they 5, 10, or 100, so moving averages can frequently be treated as pseudo key levels, similar to 1.0000 or $1000.

Moving averages are the core of many different forms of technical analysis. As part of a balanced and tested trading system, here are a few examples of potential use cases:

1. Entry indicator - If a candlestick is to close above or below the moving average, this could signal that either an existing trend will continue or a new trend is beginning to emerge. As such, moving averages can help suggest potential entries when trading.
2. Exit indicator - When managing an open trade, if a candlestick is to close above or below the moving average, this could signal that the current trend is exhausted and the price needs to consolidate, or predict a reversal. When used in this fashion, moving averages can be used to suggest when an existing trade should be closed.
3. Moving average crossovers - Not limited to one use case, when moving averages of different periods cross, this can be interpreted in many different ways. For example, if a 14-period moving average crosses above the 50-period moving average, this could suggest the start of a new uptrend and vice versa. Ultimately, crossovers can be used to gauge how short-term price action compares to long-term market trends.

While moving averages can prove an invaluable tool within your trading toolbox, much like any other technical indicator, they are not without their shortcomings:

1. Trend identification: Undeniably, the key advantage of using moving averages is objectively determining the prevailing direction of the market. While most traders look to ‘trade with the trend’, moving averages are valuable in ensuring this.
2. Smooth price action: At a glance, price action can often be confusing in times of high volatility, however, moving averages paint a clear, objective level to watch when looking to enter a trade or manage an active position.
3. Dynamic support and resistance: While traditional support and resistance levels are at fixed intervals on the chart, moving averages can be used to predict areas of interest to traders. Especially in the case of EMAs, these levels will change at the close of each candle, allowing them to reflect recent market movements better.

1. Lagging nature: A criticism shared with many technical indicators, moving averages can be considered a lagging indicator, using historical price data. As such, they are technically behind current market price, which is especially significant for shorter-period moving averages. This could lead to a poorly timed entry or exit in some situations.
2. False signals: While false signals are not unique to moving averages, problems can arise when using them in periods of consolidation without a clear trend. While they excel in trending conditions, sideways markets can sometimes generate a signal that, at best, takes up margin or, worse, amounts to a losing trade.
3. Dependence on historical data: Separately to their lagging nature, the reliance on using historical data means that moving averages cannot adjust for any changes in price before the candle closes. This goes double for SMAs, as the most recent candle data is weighted the same as the eldest.

• Moving averages are a technical indicator used to show average pricing over a set time period, while smoothing price data to an easy-to-follow line.
• Within the realms of technical analysis, traders primarily use three different types of moving averages: simple, exponential, and weighted. Each type varies in calculation method and can all be uniquely applied in various use cases.
• Used in many different systems, most forms of technical analysis rely on price action crossing above or below the moving average to generate a signal. In some cases, when two moving averages cross or price action trades far from a moving average, this can also be considered as part of a trading strategy.
• Like any other form of analysis, moving averages are likely to work better when used as part of a tested and balanced trading system. Traders should look to build ‘confluences’ within their trading strategies, where multiple forms of analysis, either technical or fundamental, come to the same consensus of long or short.