Learn how to identify stock market trends using moving averages to help add context, support decision making, and complement other forms of analysis.
Sir Isaac Newton developed the laws of motion to understand and describe the relationships between an object, the forces acting on it, and its motion. One of these laws is the law of inertia, which states that an object at rest stays at rest. An object in motion stays in motion with the same velocity and direction unless acted upon by an opposing force.
Some investors borrow from the law of inertia to understand and describe the relationships between a stock price, buying and selling of the stock, and its motion. But instead of using the term “inertia,” investors typically call it “momentum.” The “forces” acting on a stock are buying and selling. And the “motion” of a stock is usually called a trend.
Trends can form in three directions: up, down, or sideways. These trends, or ways of describing a stock’s motion, are important building blocks in technical analysis.
A common way to define trends in stocks is by analyzing a chart of historical prices. In particular, investors look at and relate highs and lows in prices to help identify trends.
We’re going to look at examples of up, down, and sideways trends using line charts. Line charts are simple because they plot just one data point: closing prices. That simplicity can help when learning how to identify trends. Let’s begin with an uptrend.
An uptrend is usually defined as a series of higher highs and higher lows. See figure 1 for a good historical example of an uptrend. This is a monthly line chart of the S&P 500 ($SPX.X) from 2012 to 2015. Note the series of higher highs and higher lows.
FIGURE 1: S&P 500 ($SPX.X) MONTHLY LINE CHART.
This chart displays higher highs and higher lows in the $SPX.X from 2012 to 2015. Data source: SunGard. Image source: tdameritrade.com. For illustrative purposes only. Past performance does not guarantee future results.
A downtrend is usually defined as a series of lower highs and lower lows. Figure 2 shows a good historical example of a downtrend. This is a daily line chart of the $SPX.X from November 2015 to February 2016. Note the series of lower highs and lower lows over time.
FIGURE 2: S&P 500 ($SPX.X) DAILY LINE CHART.
This chart displays lower highs and lower lows in the $SPX.X from November 2015 to February 2016. Data source: SunGard. Image source: tdameritrade.com. For illustrative purposes only. Past performance does not guarantee future results.
A sideways trend is typically defined as a series of roughly equal highs and lows. Figure 3 shows an example of a sideways trend. This is a daily line chart of the $SPX.X from February 2015 to August 2015. Note the series of roughly equal highs and lows.
FIGURE 3: S&P 500 ($SPX.X) DAILY LINE CHART.
This chart displays roughly equal highs and lows in the $SPX.X from February 2015 to August 2015. Data source: SunGard. Image source: tdameritrade.com. For illustrative purposes only. Past performance does not guarantee future results.
Simple enough. But now that you know how to identify trends, what’s next? Let’s look at a few foundational assumptions of technical analysis:
The risk with assuming that patterns repeat and prices move in trends is hindsight bias. That simply means you may see an event as having been predictable—but only after the event actually happened. Think about this for a moment and look again at the trends above. It’s easy to identify trends after the fact. But were the patterns identifiable in real time? Were the trends predictable before all the prices were actually plotted on the charts? Maybe not.
So, before applying trends to investing decisions, it’s important to understand the limitations and risks of technical analysis. Some investors overlook these risks and attempt to apply technical analysis as a standalone strategy to make investing decisions. Some investors think all that’s needed for success in the markets is a chart. Unfortunately, it’s more complicated than that.
The great value of applying trends, and technical analysis in general, is context. Applying trends to investing can supply valuable information and support for investment decisions.
For example, suppose you find a beaten down energy stock. After reviewing the fundamentals, like earnings and sales, you conclude that the company might experience a turnaround. However, after checking the chart, you observe a steady pattern of lower highs and lower lows. Maybe the market knows something you don’t. Maybe the time to buy isn’t right. That’s what the trend on the chart is telling you, and that’s the value of applying trends. The right time might be when the trend reverses and a series of higher highs and higher lows unfolds. At that point, the uptrend might agree with your fundamental analysis, providing context and support for your decision.
How can investors find this context and use trend analysis to support decision making?
As opposed to traders, investors typically hold investments for long periods of time, like many months or several years. So when it comes to applying trend analysis to investing, it’s important to use a chart and time frame that aligns with investing.
One time frame investors might start with is a weekly chart. Charting stock prices on a weekly basis can provide investors with enough information to make investing decisions, but with less noise than is usually associated with shorter time frames like daily and especially intraday time frames.
On a weekly chart, investors can apply moving averages to help identify series of higher highs and lows, or lower highs and lows. A moving average is just like it sounds: an average of historical prices over a specified interval that updates with each new data point.
Some investors might use two moving averages (MAs) to help identify trends. For example, in figure 4, I’ve applied 13-week and 52-week simple moving averages to the weekly $SPX.X chart. There are about 13 weeks in a quarter and 52 weeks in a year, so these MAs measure quarterly and yearly averages of the $SPX.X. Now, don’t get hung up on these intervals—feel free to experiment with different moving average lengths. But for now, notice how higher highs and lows usually unfold when the 13-week MA is above the 52-week, and vice versa.
FIGURE 4: S&P 500 ($SPX.X) WEEKLY LINE CHART.
This chart displays two moving averages applied to the $SPX.X. An uptrend is unfolding when the 13-week MA is greater than the 52-week moving average. A downtrend is defined when the 13-week MA is less than the 52-week moving average. Data source: SunGard. Image source: tdameritrade.com. For illustrative purposes only. Past performance does not guarantee future results.
Here’s how these two moving averages can help identify trends. When the 13-week moving average is greater than the 52-week moving average, the $SPX.X is in an uptrend. When the 13-week is less than the 52-week moving average, the $SPX.X is in a downtrend.
The idea is to maximize profits when the $SPX.X is in an uptrend. But when the $SPX.X is in a downtrend, the idea is to limit losses.
There are a couple of examples of how this works in figure 4. Look at the uptrend from early 2012 to mid-2015. The $SPX.X trended higher from about 1250 to over 2000.
Now look at early 2008. This downtrend took the $SPX.X from about 1500 to 1000 before the 13-week crossed back above the 52-week moving average.
The risk in using two moving averages is when the $SPX.X is in a sideways trend. Look at mid-2010, late 2013, and mid-2015 to 2016. These are times when this strategy might have resulted in missed profit opportunities and even losses. Again, there are limitations and risks in technical analysis.
Identifying trends using technical analysis is not an exact science; it has flaws, and it’s not a standalone investing strategy. But identifying trends can help add context, support your decision making, and complement other forms of analysis like fundamental, macroeconomic, and psychological.
Log on to your account at tdameritrade.com, type $SPX.X in the symbol box, and press Enter. Click Upper Indicators and SMA to apply moving averages to the chart.
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