Calculating the mean of a series and standard deviation bands
Adding recession bands
Adding the last value of a series on the Y-axis
If you get stuck, use the worksheet to see what to do next.
If you need more detailed help, have a look at the learning resources below.
The Macrobond document is also available for download here.
To find the time series used in this example we will access the tree by Country & Region as most global commodity spot prices can be found under the region World.
Go to:
Country & Region > World > Commodities & Energy > Spot Prices > Energy > Crude Oil.
Locate and add:
You can also use the short code by simply writing “oil” in the expression box in “Series list”.
The oil price is originally a daily series. In the chart displayed, we decided to use a monthly frequency to make the chart easier to read. To do so:
To control how the frequency conversion is done, you can:
If you wish to calculate the mean of a specific series, you should use the Statistics analysis.
Now, add four mean-calculations to the document. The date ranges used are:
| From | To |
| 1986 | 2004 |
| 2005 | 2009 |
| 2010 | 2013 |
| 2014 |
Note! To limit the graph lines to the period over which the mean is calculated you must uncheck the Extrapolate tick-box for each calculation.
In this case, we’ve added observation labels for each mean, displaying the value and the period. You can create them manually one by one, but you can also automate the process, using dynamic properties.
First, create one observation label, which will be used later a default.
Next step is to edit the text. To automate the process, you should:
You should write a text structured as: [analysis]: [value]$. In the new window, you should use dynamic properties:
This is how the expression will look like: {s .AnalysesDescription}: {s .Value} $
You can now close the window. Your next step is to duplicate this observation label for the other mean series.
You can simply use a copy/paste function:
Changing the frequency of the document
Using Statistics to calculate the mean of the series for several time periods.
Creating several observation labels displaying the same information
If you get stuck, use the worksheet to see what to do next.
If you need more detailed help, have a look at the learning resources below.
The Macrobond document is also available for download here.
Changing the frequency of a series
Working with Observation labels
Performing a simple regression analysis
Adding a pane to the chart
Using dynamic properties to adjust an observation label
If you get stuck, use the worksheet to see what to do next.
If you need more detailed help, have a look at the learning resources below.
The Macrobond document is also available for download here.
In this case, we will reuse the document from Step 1 Case #9 which can be downloaded here. As such, all data needed for the exercise will already be in the document.
In the case #10 from Level 1, we established that the ISM PMI is a leading indicator of the Industrial Production in the US, by 4 months.
Now, you will have to build a regression model using this information.
Remember that the correlation results were based using a data sample starting in 2000-01.
The first step will be to set the model and the outputs needed:
Now, you should set the model itself: you want to explain the Industrial Production by the ISM PMI.
Also, the best correlation between the two series was when the ISM PMI was lagged by 4 months. You should include this in the model:
Finally, and since you are lagging the explanatory series, you can calculate forecasts (for 4 months).
As default, you always get a Report as first output of the regression analysis. You can check here several econometric statistics as well as the equation of the model.
In our chart, we displayed the residuals in a secondary chart, below the main one. In Macrobond, we call this “Panes”. To add panes, you should:
You can also automatically set the proportion of the panes.
(You can also manually adjust the ratio between the two panes by dragging the lower edge of upper chart up or down)
Each Pane can have subtitles.
We begin by removing the redundant “%” sign on the lower pane:
Now, click on the background of the lower chart
We will now briefly explore Dynamic properties to customize a text in Macrobond. First, add a chart annotation to the Industrial production:
To edit the text:
Then, add dynamic properties after this text:
Finally, you can edit the format of the dynamic text:
This will change the date-format to displaying the name of the month instead of the number.
However, right now, this observation label is associated to a specific date. You might want to always refer to the last predicted value when the chart will be updated. To remedy this:
The observation label will now always point to the last value of the Industrial Production series, and the text created using dynamic properties will also get updated automatically.
Calculating the monthly performance of a series over time
Using Slice to create one series per year
Using Cross Section to calculate the average of the sliced series
Using Change Region to replicate the file for another country
If you get stuck, use the worksheet to see what to do next.
If you need more detailed help, have a look at the learning resources below.
The Macrobond document is also available for download here.
Changing the frequency of a series
In this case, you will have to use the S&P 500 index.
Using the data tree, you can locate the data here:
Country & Region > United States > Equity Market > Equity Indices > S&P > 500 > Composite > Price return
Add:
You can also directly type its short code as Expression in Series List: spx
You first need to calculate the monthly returns (in %) of the series, meaning that you are looking for one value per month. However, the original series is in a daily frequency. Therefore, you will have to make some adjustments in Series List:
The series will become a monthly one, using the last value in each month.
To calculate the monthly return, you will have to use the Rate of Change analysis:
Next step is to create one series for each year, the S&P series stating in 1928.
In the Slice analysis, just make sure that “Periods” is set to Year.
You now have one category series for each year, starting in 1928, with values going from January to December. What you would like is now to calculate the average for each month. Since you are working with a large set of series, you should use Cross Section:
In the chart, we are comparing the average with 2018 values. Following these steps will output the average versus the 2018 year. Please note that average values on our screenshot will differ from the one you are making.
Click on the series' name to see all year-series. Exclude year 2018 from the calculation by unticking “include” for the last series in the list.
For instance, the series for 1928 only starts in February. If you do not untick the setting the Application will not calculate a value for January.
Add a Category chart after Cross Section.
To display the series as columns:
To change the width of the columns and the space between them,
You might want to look at the same chart for another equity market. Instead of recreating the analyses from scratch, you can first duplicate the file:
You now have an exact copy of the document. The next step is to change the region of the series:
This will change the original series used in the document while keeping the exact structure and analyses applied. You might however do a few manual changes in this specific case:
Using Slice to compare one series across different time periods
Exporting the underlying data into Excel
If you get stuck, use the worksheet to see what to do next.
If you need more detailed help, have a look at the learning resources below.
The Macrobond document is also available for download here.
In this case, you will have to use the S&P 500 index.
Using the data tree, you can locate the data here:
Country & Region > United States > Equity Market > Equity Indices > S&P > 500 > Composite > Price return
Add:
You can also directly type its short code as Expression in Series List: spx
To create the chart, you have to compare the performance of the S&P across different time periods. The Slice analysis will help you doing so.
Now, you need to slice the data into 3 series, each starting at the dates of major financial crises:
Next, you need to specify the length of these 3 series:
Finally, to make them comparable, you should rebase all of them to 100 at their respective start date:
You cannot add a “Time Chart” after the “Slice” analysis as the sliced series do not contain a notion of time. Instead the X-axis corresponds to numbers of observations. So:
To add the labels next to the graph lines:
To add an axis title
Exporting your chart to Excel is simple:
Should you instead want to export the underlying data from the Slice analysis to Excel:
In Excel, you will get the data resulted from the slice analysis. The data is stored in the red dataset button. By right-clicking on it and selecting “Macrobond Excel data set object”, you will access various settings allowing you to edit the format of the dataset. There, “Edit Document” will open the underlying Macrobond file, if you want to edit the calculations.
This dataset can also be refreshed:
The data and its calculations will be updated instantly.
