Rounding Standards - Financial Calculations

问题:

I am curious about the existence of any "rounding" standards" when it comes to the calculation of financial data. My initial thoughts are to perform rounding only when the data is being presented to the user (presentation layer).

If "rounded" data is then used for further calculations, should be use the "rounded" figure or the "raw" figure? Does anyone have any advice?

Please note that I am aware of different rounding methods, i.e. Bankers Rounding etc.

回答1:

The first and most important rule: use a decimal data type, never ever binary floating-point types.

When exactly rounding should be performed can be mandated by regulations, such as the conversion between the Euro and national currencies it replaced.

If there are no such rules, I'd do all calculations with high precision, and round only for presentation, i.e. not use rounded values for further calculations. This should yield the best overall precision.

回答2:

I just asked a greybeard mainframe programmer at the financial software company I work for, and he said there is no well-known standard and it's up to programmer practice.

While statisticians have been aware of the rounding issue since at least 1906, it's difficult to find a financial standard endorsing it.

According to this site, the "European Commission report The Introduction of the Euro and the Rounding of Currency Amounts suggests that there had previously been no standard approach to rounding in banking."

In general, use a symmetric rounding mode no matter what base you are working in (base-2 or base-10).

This will avoid systematic bias during calculations.

Such a mode is Round-Half-To-Even, otherwise known as "bankers rounding".

Use language tools that allow you to specify the numeric context explicity, including the rounding and truncation modes. For example, Python's decimal module. The implicit assumptions made by the C library might not be appropriate for your computations.

http://en.wikipedia.org/wiki/Rounding#Rounding_to_integer

回答3:

Ive not seen the existence of "the one standard to rule them all" - there are any number of rounding rules (as you have referenced), and they seem to come into play based on industry/customer/and currency code (http://en.wikipedia.org/wiki/ISO_4217) - since not everyone uses 2 places after the decimal, the problem becomes even more complicated. At the end of the day, your customer needs to specify the rules they want to implement...

回答4:

Consider using scaled integers.

In other words, store whole numbers of pennies instead of fractional numbers of dollars.

回答5:

It's frustrating that there aren't clear standards on this, both to guide the programmer, and as a defense in court. Just doing "regular" rounding toward nearest for payroll can lead to underpayment by a few pennies on a paycheck here and there, which is something labor lawyers eat up like crack.

Though a base pay rate may well only be specified in two decimal places ("You're hired at $22.71/hour"), things like blended overtime (determined by averaging multiple pay rates in a period) end up with an effective hourly rate of $23.37183475/hr.

How do you pay overtime on that?

15 hours x 23.37183475 x 1.5 = $525.87 rounded from $525.86628187
15 hours x 23.37       x 1.5 = $525.82

WHY DID YOU STEAL FIVE CENTS FROM MY CLIENT? Sadly, I'm not joking about this.

This gets even more uncomfortable when you calculate at the full precision value but display a truncated version: you do the first calculation above, but only display $23.37 for the rate on the pay stub.

Now the pay stub calculations don't tie out to the penny, and now you have to explain it, but even if it's in the employee's favor, it can be enough for a labor lawyer to smell blood in the water and start looking for other stuff.

One approach is to always round in favor of the employee, not in the "natural" direction, so there cannot ever be an accusation of "systematic wage theft".