As technical analysis is built on the assumption that prices trend, the use of trend lines is important for both trend identification and confirmation. A trend line is a straight line that connects two or more price points and then extends into the future to act as a line of support or resistance. Many of the principles applicable to support and resistance levels can be applied to trend lines as well. It is important that you understand all of the concepts presented in our Support and Resistance article before continuing on.
An uptrend line has a positive slope and is formed by connecting two or more low points. The second low must be higher than the first for the line to have a positive slope. Note that at least three points must be connected before the line is considered to be a valid trend line. Uptrend lines act as support and indicate that net-demand demand less supply is increasing even as the price rises. A rising price combined with increasing demand is very bullish, and shows a strong determination on the part of the buyers.
As long as prices remain above the trend line, the uptrend is considered solid and intact. A break below the uptrend line indicates that net-demand has weakened and a change in trend could be imminent. A downtrend line has a negative slope and is formed by connecting two or more high points. The second high must be lower than the first for the line to have a negative slope.
Downtrend lines act as resistance, and indicate that net-supply supply less demand is increasing even as the price declines.
A declining price combined with increasing supply is very bearish, and shows the strong resolve of the sellers. As long as prices remain below the downtrend line, the downtrend is solid and intact. A break above the downtrend line indicates that net-supply is decreasing and that a change of trend could be imminent. For a detailed explanation of trend changes, which are different than just trend line breaks, please see our article on the Dow Theory.
Excel trendline types, equations and formulas
High points and low points appear to line up better for trend lines when prices are displayed using a semi-log scale. This is especially true when long-term trend lines are being drawn or when there is a large change in price. Most charting programs allow users to set the scale as arithmetic or semi-log. An arithmetic scale displays incremental values 5,10,15,20,25,30 evenly as they move up the y-axis.
A semi-log scale displays incremental values in percentage terms as they move up the y-axis. In the case of Amazon. These false breakouts could have led to premature buying as the stock continued to decline after each one. The semi-log scale reflects the percentage loss evenly, and the downtrend line was never broken. In the case of EMC, there was a large price change over a long period of time. While there were not any false breaks below the uptrend line on the arithmetic scale, the rate of ascent appears smoother on the semi-log scale.
EMC doubled three times in less than two years. On the semi-log scale, the trend line fits all the way up. On the arithmetic scale, three different trend lines were required to keep pace with the advance. It takes two or more points to draw a trend line. The more points used to draw the trend line, the more validity attached to the support or resistance level represented by the trend line.
It can sometimes be difficult to find more than 2 points from which to construct a trend line. Even though trend lines are an important aspect of technical analysis, it is not always possible to draw trend lines on every price chart.
Sometimes the lows or highs just don't match up, and it is best not to force the issue. The general rule in technical analysis is that it takes two points to draw a trend line and the third point confirms the validity.Joinsubscribers and get a daily digest of news, geek trivia, and our feature articles.
You can add a trendline to a chart in Excel to show the general pattern of data over time. You can also extend trendlines to forecast future data.
TREND function and other ways to do trend analysis in Excel
Excel makes it easy to do all of this. A trendline or line of best fit is a straight or curved line which visualizes the general direction of the values. You can add a trendline to an Excel chart in just a few clicks. The Format Trendline pane opens and presents all trendline types and further options. In the first example, the line graph had only one data series, but the following column chart has two.
If you want to apply a trendline to only one of the data series, right-click on the desired item. You might want to format the trendline differently—especially if you have multiple trendlines on a chart. I also increased the width to 2 pts and changed the dash type.
A very cool feature of trendlines in Excel is the option to extend them into the future. This gives us an idea of what future values might be based on the current data trend. The R-squared value is a number that indicates how well your trendline corresponds to your data. The closer the R-squared value is to 1, the better the fit of the trendline.
A value of 0. This is a reasonable fit, as a value over 0. The Best Tech Newsletter Anywhere. Joinsubscribers and get a daily digest of news, comics, trivia, reviews, and more. Windows Mac iPhone Android. Smarthome Office Security Linux. The Best Tech Newsletter Anywhere Joinsubscribers and get a daily digest of news, geek trivia, and our feature articles.
Skip to content.Free statistics calculators designed for data scientists. This Least Squares Regression Calculator:. Click To Clear; enter values seperated by commas or new lines. Can be comma separated or one line per data point; you can also cut and paste from Excel.
Saved in your browser; you can retrieve these and use them elsewhere on this site. Need to pass an answer to a friend? It's easy to link and share the results of this tool. Hit calculate - then simply cut and paste the url after hitting calculate - it will retain the values you enter so you can share them via email or social media. This is a online regression calculator for statistical use. Enter your data as a string of number pairs, separated by commas.
Enter each data point as a separate line. Then hit calculate. The linear regression calculator will estimate the slope and intercept of a trendline that is the best fit with your data. This page includes a regression equation calculator, which will generate the parameters of the line for your analysis.
It can serve as a slope of regression line calculator, measuring the relationship between the two factors. You can save your data for use with this webpage and the similar tools on this site. Just hit the "save data" button. It will save the data in your browser not on our server, it remains private. It will appear on the list of saved datasets below the data entry panel.
To retrieve it, all you need to do is click the "load data" button next to it. This linear regression calculator fits a trend-line to your data using the least squares technique. This approach optimizes the fit of the trend-line to your data, seeking to avoid large gaps between the predicted value of the dependent variable and the actual value. The Least Squares Regression Calculator will return the slope of the line and the y-intercept.
It will also generate an R-squared statistic, which evaluates how closely variation in the independent variable matches variation in the dependent variable the outcome. For a deeper view of the mathematics behind the approach, here's a regression tutorial.
To help you visualize the trend - we display a plot of the data and the trend-line we fit through it. If you hover or tap on the chart in most browsersyou can get a predicted Y value for that specific value of X.
The equation of the line is of particular interest since you can use it to predict points outside your original data set. Similarly, the r-squared gives you an estimate of the error associated with effort: how far the points are from the calculated least squares regression line.
Some practical comments on real world analysis: The modeling process only looks at the mean of the dependent variable. This is important if you're concerned with a small subset of the population, where extreme values trigger extreme outcomes.
Data observations must be truly independent. Each observation in the model must truly stand on its own.As a member, you'll also get unlimited access to over 79, lessons in math, English, science, history, and more. Plus, get practice tests, quizzes, and personalized coaching to help you succeed.
Already registered? Log in here for access. Log in or sign up to add this lesson to a Custom Course. Log in or Sign up. Amy has a master's degree in secondary education and has taught math at a public charter high school.
In this lesson, we'll talk about finding the equation of a trend line. In the real world, your data will usually be scattered like in this graph instead of lining up neatly in a straight line. In some real world cases, though, your data will look like it follows a line.
If it does, then you'll be able to approximate your data with a line and a linear equation. This line that you approximate your data with is called the trend line. If this line is a straight line, then you'll be able to find an equation for this line. In this lesson, we'll talk about finding an equation for trend lines that are straight lines.
For these types of trend lines, you'll be able to find an equation in the slope-intercept form where m is your slope and b is your y -intercept. Remember, your slope is how steep your line is. A flat, horizontal line has a slope of 0. A diagonal line on the graph has a slope of 1. Steeper lines have larger slopes. Your y -intercept is where your line crosses the y -axis. You begin by drawing your trend line. You want your trend line to follow your data. You want to have roughly half your data above the line and the other half below the line, like this:.
Your next step is to locate two points on the trend line. Look carefully at your trend line and look for two easy to figure out points on the line. Ideally, these are points where the trend line crosses a clearly identifiable location.
We can label our first point as x 1y 1and our second point as x 2y 2. Plugging these values into the equation for slope and evaluating, we get this:. Your last step uses the point with the smaller numbers to help you find the equation of your trend line. You'll want to use the smaller point as using smaller numbers is easier to work with. You'll be plugging the values of this point into the point-slope formula for the equation of a line to find the equation of your trend line.
Your point will be labeled like before as x 1y 1. The point-slope formula is this one:. You can see that it also uses the slope. You'll plug in your x 1 and y 1 along with the slope into the formula.
Then you'll evaluate and rewrite it in the slope-intercept form by solving for the y variable. Looking carefully at this graph, we see that this trend line passes through the points 3, 3 and 5, 7.A couple months back I wrote Add One Trendline for Multiple Series which shows how to add a trendline to a chart, and have the trendline calculated for multiple series in the chart.
In fact, that tutorial was based on my answer to a question on Quora, How can I have multiple scatter plots and one trendline for all of them combined in Excel? Feedback on that tutorial was positive, but it seems that people would like the process to be faster and simpler. Fair enough. If you recall, the original problem was that we had three series of data in the chart, and we can easily get a trendline for any or all individual series, but we want a trendline that covers all points in all three series.
We created a new series in the chart that included all points from the first three series the yellow markers cover the blue, orange, and green ones :.
This was the tedious step, adding all the data to a new series, and this is the part that my add-in will speed through. In between we will combine the X values and Y values of the original three series. Our constructed series formula looks like:. What our code will do is count the series in the chart, read each series formula in turn, split out its arguments, and concatenate the separate X and Y values into combined X and Y values.
The code will then add the new series, apply the arguments of the series formula, hide the markers, and add a trendline. I discuss why in a decade-old tutorial, VB Editor Settings. Skip a line after Option Explicit in your brand new code module, then copy the code from above, and paste it into the module. Before you run the code, select a chart. Select ComputeMultipleTrendline and click Run. I used a solid black line, rather than the default dotted line Excel uses, because I think a solid line makes it easier to see.
I used the code above as the basis for my add-in. I added a custom ribbon tab named Multi Trendline with a custom button labeled Multi Scatter Trendline to invoke the code.Finding the Line of Best Fit
I also designed a dialog so that you can select which series in the chart to include in your analysis and which to exclude. You can download the add-in from this link: MultiScatterTrendlineCalculator. The add-in is packaged in a zip file. Unzip the file, and store the add-in in the User Add-in Library, which is. Windows protects your computer from malicious software that came from a different computer than yours, but it also protects your computer from useful software that came from my computer, so you need to unblock the add-in.
Right click on the add-in file in Windows Explorer, and choose Properties. At the bottom of the General tab of the Properties dialog, there may be a notice that the file may be blocked, and there is a checkbox to unblock the file.You may need to determine the y-intercept of a trend line in order to understand more about the data that the trend line is representing. A trend line is a line that is drawn above, below or through various data points in order to show their general direction.
The trend line may be drawn from the upper left corner to the lower right corner, indicating that the data have a negative slope, or from the lower left corner to the upper right corner, indicating that the data have a positive slope.
The y-intercept of the trend line is the point at which the trend line has an x value of zero. Examine the trend line that is on the graph. One of the methods for determining the y-intercept is through observation. Place your pencil over this point.
Follow the vertical line above this point with your pencil until the pencil intersects the trend line. Look at the y-axis, or vertical axis, and find the value for which this intersection occurs. This value is the y-intercept. Compare the general equation of a line to the equation of the trend line. By looking at the equation of the trend line, you can determine the y-intercept.
Review the point-slope formula. If the trend line does not have an equation, then you will want to create one in order to determine the y-intercept.
Find the slope of the line. In order to generate the equation of the line, you need to find the slope. For example, two points on the trend line may be 2,9 and 3, Find another point on the trend line and put the values of the point and the slope into the point-slope formula. Therefore, the y-intercept of the trend line is 5.
Mara Pesacreta has been writing for over seven years. She has been published on various websites and currently attends the Polytechnic Institute of New York University. About the Author. Photo Credits. Copyright Leaf Group Ltd.In this tutorial, you will find the detailed description of all the trendline options available in Excel and when to use them.
You will also learn how to display a trendline equation in a chart and find the slope of trendline. It is very easy to add a trendline in Excel. The only real challenge is to choose the trendline type that best corresponds to the type of data you are analyzing. If you are looking for how to insert a trendline in an Excel chart, please check out the above linked tutorial. When adding a trendline in Excel, you have 6 different options to choose from.
Additionally, Microsoft Excel allows displaying a trendline equation and R-squared value in a chart:. Below, you will find a brief description of each trendline type with chart examples. The linear trend line is best to be used with linear data sets when the data points in a chart resemble a straight line. Typically, a linear trendline describes a continuous rise or fall over time.
For example, the following linear trendline shows a steady increase in sales over 6 months. And the R 2 value of 0. The exponential trendline is a curved line that illustrates a rise or fall in data values at an increasing rate, therefore the line is usually more curved at one side.
This trendline type is often used in sciences, for example to visualize a human population growth or decline in wildlife populations. Please note that an exponential trendline cannot be created for data that contains zeros or negative values. A good example of an exponential curve is the decay in the entire wild tiger population on the earth. The logarithmic best-fit line is generally used to plot data that quickly increases or decreases and then levels off. It can include both positive and negative values.
An example of a logarithmic trendline may be an inflation rate, which first is getting higher but after a while stabilizes. The polynomial curvilinear trendline works well for large data sets with oscillating values that have more than one rise and fall. Generally, a polynomial is classified by the degree of the largest exponent. The degree of the polynomial trendline can also be determined by the number of bends on a graph.
Typically, a quadratic polynomial trendline has one bend hill or valleya cubic polynomial has 1 or 2 bends, and a quartic polynomial has up to 3 bends. When adding a polynomial trendline in an Excel chart, you specify the degree by typing the corresponding number in the Order box on the Format Trendline pane, which is 2 by default:. For example, the quadratic polynomial trend is evident on the following graph that shows the relationship between the profit and the number of years the product has been on the market: rise in the beginning, peak in the middle and fall near the end.
The power trend line is very similar to the exponential curve, only it has a more symmetrical arc. It is commonly used to plot measurements that increase at a certain rate. As an example, let's draw a power trendline to visualize the chemical reaction rate. Note the R-squared value of 0. When the data points in your chart have a lot of ups and downs, a moving average trendline can smooth the extreme fluctuations in data values to show a pattern more clearly.
For this, Excel calculates the moving average of the number of periods that you specify 2 by default and puts those average values as points in the line.
The higher the Period value, the smoother the line. A good practical example is using the moving average trendline to reveal fluctuations in a stock price that otherwise would be difficult to observe. For more information, please see: How to add a moving average trendline to an Excel chart. This section describes the equations that Excel uses for different trendline types. You do not have to build these formulas manually, simply tell Excel to display the trendline equation in a chart.