The ECM Procedure

OUTSUM Statement

  • OUTSUM <outsum-options> <statistic-keyword<=variable-name> …statistic-keyword<=variable-name>>;

The OUTSUM statement specifies the data table in which PROC ECM writes the summary statistics of the total loss sample.

If you specify more than one OUTSUM statement, only the first one is used.

You can specify the following outsum-options:

OUT=CAS-libref.data-table
OUTSUM=CAS-libref.data-table

specifies the output data table that contains the summary statistics of the total loss sample. CAS-libref.data-table is a two-level name, where CAS-libref refers to the caslib and session identifier, and data-table specifies the name of the input data table. For more information about this two-level name, see the DATA= option and the section Using CAS Sessions and CAS Engine Librefs. The CAS-libref must be identical to the CAS-libref that you specify in the DATA= option.

You can control the statistics that appear in this data table by specifying the PCTLPTS= option, the TVARPTS= option, and different statistic-keyword values.

PCTLNDEC=integer-value

specifies the maximum number of decimal places to use when creating the names of the variables for the percentile values in the PCTLPTS= or TVARPTS= options. For example, for a percentile value of 99.9995, if you specify PCTLNDEC=4, then the suffix of the variable is 99_9995. Specifying a small number might result in duplicate variable names. If that happens, PROC ECM writes an error message and exits.

By default, PROC ECM computes the required number of decimal places by using the precision of the percentiles that you specify in the PCTLPTS= option or the TVARPTS= option.

PCTLPRE=prefix

specifies the prefix to use for creating the names of the variables that contain the percentile estimates. The percentile estimate for a value p is written to a variable that has the name of the form prefixt, where t is the text representation of p that is formed by replacing the decimal point with an underscore (_). For example, if PCTLPRE=P, then the estimate of the 97.5th percentile is written to a variable whose name is P97_5. By default, PCTLPRE=P.

PCTLPTS=percentile-option

specifies the percentiles of the total loss that you want PROC ECM to compute. The percentile-option can have one of the following two forms:

DEFAULT
DEF

computes only the default list of percentile values, which is {1, 5, 10, 25, 50, 75, 90, 95, 99, 99.5}.

percentile-list

adds the percentiles that you specify in the percentile-list to the default list of percentiles, where percentile-list is a comma-separated list of percentile values, each of which must belong to the (0,100) open interval. You can also use a list notation of the following form: <number1> to <number2> by <increment>. For example, the following two options are equivalent:

pctlpts=10, 20, 99.6, 99.7, 99.8, 99.9
pctlpts=10, 20, 99.6 to 99.9 by 0.1

TVARPRE=prefix

specifies the prefix to use for creating the names of the variables that contain the tail value-at-risk (TVar) estimates. The TVaR estimate for a percentile value p is written to a variable that has the name of the form prefixt, where t is the text representation of p that is formed by replacing the decimal point with an underscore (_). For example, if TVARPRE=TVaR, then the tail value-at-risk estimate for the 97.5th percentile is written to a variable whose name is TVaR97_5. By default, TVARPRE=TVaR.

TVARPTS=tvar-percentile-list

specifies the percentile values for which you want PROC ECM to compute the tail value-at-risk (TVaR) of the total loss, where tvar-percentile-list is a comma-separated list of percentile values, each of which must belong to the (0,100) open interval. You can also use a list notation of the form "<number1> to <number2> by <increment>". For example, the following two options are equivalent:

tvarpts=90, 95, 96.25, 97.5, 98.75, 99.5
tvarpts=90, 95 to 99 by 1.25, 99.5

For each value in the tvar-percentile-list, PROC ECM also reports the percentile estimates, which are the estimates of the value-at-risk (VaR) for the corresponding TVaR estimate.

If you specify a data table in the OUTSUM= option, PROC ECM adds the TVaR estimates to that table. You can control the name of each TVaR estimate’s variable by specifying the TVARPRE= option.

You can also specify one or more predefined statistics of the total loss sample to be written to the OUTSUM= table in the following form:

statistic-keyword<=variable-name>

writes the statistic that corresponds to the statistic-keyword to a variable named variable-name. For the predefined statistics that correspond to percentiles, the variable-name takes precedence over the default name that PROC ECM forms by using the PCTLPRE= option. All variable names in the OUTSUM= data table have a limit of 32 characters.

If you do not specify the variable-name, then PROC ECM writes the statistic to a variable named statistic-keyword.

You can specify the following statistic-keywords, which result in the specified statistic being written to the OUTSUM= table:

KURTOSIS | KURT

writes the kurtosis of the total loss sample.

MEAN

writes the mean of the total loss sample.

P01

writes the first percentile of the total loss sample.

P05

writes the fifth percentile of the total loss sample.

P10

writes the 10th percentile of the total loss sample.

P25 | Q1

writes the first quartile (the 25th percentile) of the total loss sample.

P50 | MEDIAN | Q2

writes the median (the 50th percentile) of the total loss sample.

P75 | Q3

writes the third quartile (the 75th percentile) of the total loss sample.

P90

writes the 90th percentile of the total loss sample.

P95

writes the 95th percentile of the total loss sample.

P99

writes the 99th percentile of the total loss sample.

P99_5 | P995

writes the 99.5th percentile of the total loss sample.

QRANGE

writes the interquartile range (Q3–Q1) of the total loss sample.

SKEWNESS | SKEW

writes the skewness of the total loss sample.

STDDEV | STD

writes the standard deviation of the total loss sample.

VARIANCE

writes the variance of the total loss sample.

Last updated: May 01, 2023