# Overview

The Cross section analysis produces output series by performing a calculation across a set of input series at each point in time, e.g. average of multiple series. Below the possible calculation are listed:

### High

Find the highest observation.

### Low

Find the lowest observation.

### Mean

Calculate the mean of the observations.

### Median

Calculate the median of the observations.

### Percentile

Calculate the percentile of the observations as specified by the parameter.

### Product

Calculate the product of the observations.

### Standard deviation

Calculate the standard deviation of the observations.

### Sum

Calculate the sum of the values.

### Count

Count the number of observations that are TRUE (>0.5).

### Count valid

Count the number of valid observations.

### Average correlation

Calculate the average correlation of  the observations where length defines correlation window.

### Average absolute correlation

Calculate the average absolute correlation of  the observations where length defines correlation window.

### Lower tail mean

Calculate the mean of the lowest observations as specified by the parameter.

### Upper tail mean

Calculate the mean of the highest observations as specified by the parameter.

# Settings

Apart from the available calculations and their properties, there are three main settings regarding the output series and the calculation range. ## Include only observations where there are values for all series

When this is checked, calculations will be performed only when all series have values. It's useful feature when series are uneven.

## Do not include series used in calculations in the output

This excludes from the output all the series that were used as inputs in the calculation. Only the calculated output series and other series in your document that were not used as input will be visible on your chart or table.

## Include new series automatically

When this is checked, any new series that you add to your document will be automatically included in the calculations.

# Examples

Pairwise correlation

Here, we calculated the average correlation across all sectors of the S&P 500, on a rolling basis. The application will first calculate the correlation for each pair of series. Then, an average of all these correlations will be performed to get a single series.

Performing several statistical calculations across series

Another way of using cross section is to perform several calculations across many series. In this example, we used the MFI interest rates of the main Euro Area countries and performed several calculations in Cross section:

high - the highest value across all the series at each point in time

low - the lowest value across all the series at each point in time

median - the median value across all the series at each point in time

percentile [75, 25, 90, & 10] - specific percentile values across all the series at each point in time.