XNPV - chart function

XNPV() returns the aggregated net present value for a schedule of cash flows (not necessarily periodic) represented by paired numbers in the expressions given by pmt and date iterated over the chart dimensions. All payments are discounted based on a 365-day year.

Syntax:  

XNPV([TOTAL [<fld{,fld}>]] discount_rate, pmt, date)

Return data type: numeric The result has a default number format of money.

Arguments:  

Argument Description
discount_rate discount_rate is the rate of discount over the length of the period.
pmt Payments.The expression or field containing the cash flows corresponding to the payment schedule given in date.
date The expression or field containing the schedule of dates corresponding to the cash flow payments given in pmt.
TOTAL

If the word TOTAL occurs before the function arguments, the calculation is made over all possible values given the current selections, and not just those that pertain to the current dimensional value, that is, it disregards the chart dimensions.

The TOTAL qualifier may be followed by a list of one or more field names within angle brackets <fld>. These field names should be a subset of the chart dimension variables.

See: Defining the aggregation scope

Limitations:  

discount_rate, pmt and date must not contain aggregation functions, unless these inner aggregations contain the TOTAL qualifier. For more advanced nested aggregations, use the advanced aggregation function Aggr, in combination with calculated dimensions.

Text values, NULL values and missing values in any or both pieces of a data-pair result in the entire data-pair being disregarded.

Examples and results:  

Example Result
XNPV(Discount, Payments, Date) -$3164.35

Data used in examples:

Cashflow:

LOAD 2013 as Year, * inline [

Date|Discount|Payments

2013-01-01|0.1|-10000

2013-03-01|0.1|3000

2013-10-30|0.1|4200

2014-02-01|0.2|6800

] (delimiter is '|');

Did this information help you?

Thanks for letting us know. Is there anything you'd like to tell us about this topic?

Can you tell us why it did not help you and how we can improve it?