Why not use Double or Float to represent currency?

Question

I've always been told never to represent money with double or float types, and this time I pose the question to you: why?

I'm sure there is a very good reason, I simply do not know what it is.

Answer 1

Some example... this works (actually don't work as expected), on almost any programming language... I've tried with Delphi, VBScript, Visual Basic, JavaScript and now with Java/Android:

    double total = 0.0;

    // do 10 adds of 10 cents
    for (int i = 0; i < 10; i++) {
        total += 0.1;  // adds 10 cents
    }

    Log.d("round problems?", "current total: " + total);

    // looks like total equals to 1.0, don't?

    // now, do reverse
    for (int i = 0; i < 10; i++) {
        total -= 0.1;  // removes 10 cents
    }

    // looks like total equals to 0.0, don't?
    Log.d("round problems?", "current total: " + total);
    if (total == 0.0) {
        Log.d("round problems?", "is total equal to ZERO? YES, of course!!");
    } else {
        Log.d("round problems?", "is total equal to ZERO? NO... thats why you should not use Double for some math!!!");
    }

OUTPUT:

round problems?: current total: 0.9999999999999999 round problems?: current total: 2.7755575615628914E-17 round problems?: is total equal to ZERO? NO... thats why you should not use Double for some math!!!

Answer 2

This is not a matter of accuracy, nor is it a matter of precision. It is a matter of meeting the expectations of humans who use base 10 for calculations instead of base 2. For example, using doubles for financial calculations does not produce answers that are "wrong" in a mathematical sense, but it can produce answers that are not what is expected in a financial sense.

Even if you round off your results at the last minute before output, you can still occasionally get a result using doubles that does not match expectations.

Using a calculator, or calculating results by hand, 1.40 * 165 = 231 exactly. However, internally using doubles, on my compiler / operating system environment, it is stored as a binary number close to 230.99999... so if you truncate the number, you get 230 instead of 231. You may reason that rounding instead of truncating would have given the desired result of 231. That is true, but rounding always involves truncation. Whatever rounding technique you use, there are still boundary conditions like this one that will round down when you expect it to round up. They are rare enough that they often will not be found through casual testing or observation. You may have to write some code to search for examples that illustrate outcomes that do not behave as expected.

Assume you want to round something to the nearest penny. So you take your final result, multiply by 100, add 0.5, truncate, then divide the result by 100 to get back to pennies. If the internal number you stored was 3.46499999.... instead of 3.465, you are going to get 3.46 instead 3.47 when you round the number to the nearest penny. But your base 10 calculations may have indicated that the answer should be 3.465 exactly, which clearly should round up to 3.47, not down to 3.46. These kinds of things happen occasionally in real life when you use doubles for financial calculations. It is rare, so it often goes unnoticed as an issue, but it happens.

If you use base 10 for your internal calculations instead of doubles, the answers are always exactly what is expected by humans, assuming no other bugs in your code.

Answer 3

Because floats and doubles cannot accurately represent the base 10 multiples that we use for money. This issue isn't just for Java, it's for any programming language that uses base 2 floating-point types.

In base 10, you can write 10.25 as 1025 * 10^-2 (an integer times a power of 10). IEEE-754 floating-point numbers are different, but a very simple way to think about them is to multiply by a power of two instead. For instance, you could be looking at 164 * 2^-4 (an integer times a power of two), which is also equal to 10.25. That's not how the numbers are represented in memory, but the math implications are the same.

Even in base 10, this notation cannot accurately represent most simple fractions. For instance, you can't represent 1/3: the decimal representation is repeating (0.3333...), so there is no finite integer that you can multiply by a power of 10 to get 1/3. You could settle on a long sequence of 3's and a small exponent, like 333333333 * 10^-10, but it is not accurate: if you multiply that by 3, you won't get 1.

However, for the purpose of counting money, at least for countries whose money is valued within an order of magnitude of the US dollar, usually all you need is to be able to store multiples of 10^-2, so it doesn't really matter that 1/3 can't be represented.

The problem with floats and doubles is that the vast majority of money-like numbers don't have an exact representation as an integer times a power of 2. In fact, the only multiples of 0.01 between 0 and 1 (which are significant when dealing with money because they're integer cents) that can be represented exactly as an IEEE-754 binary floating-point number are 0, 0.25, 0.5, 0.75 and 1. All the others are off by a small amount. As an analogy to the 0.333333 example, if you take the floating-point value for 0.1 and you multiply it by 10, you won't get 1.

Representing money as a double or float will probably look good at first as the software rounds off the tiny errors, but as you perform more additions, subtractions, multiplications and divisions on inexact numbers, errors will compound and you'll end up with values that are visibly not accurate. This makes floats and doubles inadequate for dealing with money, where perfect accuracy for multiples of base 10 powers is required.

A solution that works in just about any language is to use integers instead, and count cents. For instance, 1025 would be $10.25. Several languages also have built-in types to deal with money. Among others, Java has the BigDecimal class, and C# has the decimal type.

Answer 4

I prefer using Integer or Long to represent currency. BigDecimal junks up the source code too much.

You just have to know that all your values are in cents. Or the lowest value of whatever currency you're using.

Answer 5

Most answers have highlighted the reasons why one should not use doubles for money and currency calculations. And I totally agree with them.

It doesn't mean though that doubles can never be used for that purpose.

I have worked on a number of projects with very low gc requirements, and having BigDecimal objects was a big contributor to that overhead.

It's the lack of understanding about double representation and lack of experience in handling the accuracy and precision that brings about this wise suggestion.

You can make it work if you are able to handle the precision and accuracy requirements of your project, which has to be done based on what range of double values is one dealing with.

You can refer to guava's FuzzyCompare method to get more idea. The parameter tolerance is the key. We dealt with this problem for a securities trading application and we did an exhaustive research on what tolerances to use for different numerical values in different ranges.

Also, there might be situations when you're tempted to use Double wrappers as a map key with hash map being the implementation. It is very risky because Double.equals and hash code for example values "0.5" & "0.6 - 0.1" will cause a big mess.

Answer 6

As said earlier "Representing money as a double or float will probably look good at first as the software rounds off the tiny errors, but as you perform more additions, subtractions, multiplications and divisions on inexact numbers, you’ll lose more and more precision as the errors add up. This makes floats and doubles inadequate for dealing with money, where perfect accuracy for multiples of base 10 powers is required."

Finally Java has a standard way to work with Currency And Money!

JSR 354: Money and Currency API

JSR 354 provides an API for representing, transporting, and performing comprehensive calculations with Money and Currency. You can download it from this link:

JSR 354: Money and Currency API Download

The specification consists of the following things:

1. An API for handling e. g. monetary amounts and currencies
2. APIs to support interchangeable implementations
3. Factories for creating instances of the implementation classes
4. Functionality for calculations, conversion and formatting of monetary amounts
5. Java API for working with Money and Currencies, which is planned to be included in Java 9.
6. All specification classes and interfaces are located in the javax.money.* package.

Sample Examples of JSR 354: Money and Currency API:

An example of creating a MonetaryAmount and printing it to the console looks like this::

MonetaryAmountFactory<?> amountFactory = Monetary.getDefaultAmountFactory();
MonetaryAmount monetaryAmount = amountFactory.setCurrency(Monetary.getCurrency("EUR")).setNumber(12345.67).create();
MonetaryAmountFormat format = MonetaryFormats.getAmountFormat(Locale.getDefault());
System.out.println(format.format(monetaryAmount));

When using the reference implementation API, the necessary code is much simpler:

MonetaryAmount monetaryAmount = Money.of(12345.67, "EUR");
MonetaryAmountFormat format = MonetaryFormats.getAmountFormat(Locale.getDefault());
System.out.println(format.format(monetaryAmount));

The API also supports calculations with MonetaryAmounts:

MonetaryAmount monetaryAmount = Money.of(12345.67, "EUR");
MonetaryAmount otherMonetaryAmount = monetaryAmount.divide(2).add(Money.of(5, "EUR"));

CurrencyUnit and MonetaryAmount

// getting CurrencyUnits by locale
CurrencyUnit yen = MonetaryCurrencies.getCurrency(Locale.JAPAN);
CurrencyUnit canadianDollar = MonetaryCurrencies.getCurrency(Locale.CANADA);

MonetaryAmount has various methods that allow accessing the assigned currency, the numeric amount, its precision and more:

MonetaryAmount monetaryAmount = Money.of(123.45, euro);
CurrencyUnit currency = monetaryAmount.getCurrency();
NumberValue numberValue = monetaryAmount.getNumber();

int intValue = numberValue.intValue(); // 123
double doubleValue = numberValue.doubleValue(); // 123.45
long fractionDenominator = numberValue.getAmountFractionDenominator(); // 100
long fractionNumerator = numberValue.getAmountFractionNumerator(); // 45
int precision = numberValue.getPrecision(); // 5

// NumberValue extends java.lang.Number. 
// So we assign numberValue to a variable of type Number
Number number = numberValue;

MonetaryAmounts can be rounded using a rounding operator:

CurrencyUnit usd = MonetaryCurrencies.getCurrency("USD");
MonetaryAmount dollars = Money.of(12.34567, usd);
MonetaryOperator roundingOperator = MonetaryRoundings.getRounding(usd);
MonetaryAmount roundedDollars = dollars.with(roundingOperator); // USD 12.35

When working with collections of MonetaryAmounts, some nice utility methods for filtering, sorting and grouping are available.

List<MonetaryAmount> amounts = new ArrayList<>();
amounts.add(Money.of(2, "EUR"));
amounts.add(Money.of(42, "USD"));
amounts.add(Money.of(7, "USD"));
amounts.add(Money.of(13.37, "JPY"));
amounts.add(Money.of(18, "USD"));

Custom MonetaryAmount operations

// A monetary operator that returns 10% of the input MonetaryAmount
// Implemented using Java 8 Lambdas
MonetaryOperator tenPercentOperator = (MonetaryAmount amount) -> {
  BigDecimal baseAmount = amount.getNumber().numberValue(BigDecimal.class);
  BigDecimal tenPercent = baseAmount.multiply(new BigDecimal("0.1"));
  return Money.of(tenPercent, amount.getCurrency());
};

MonetaryAmount dollars = Money.of(12.34567, "USD");

// apply tenPercentOperator to MonetaryAmount
MonetaryAmount tenPercentDollars = dollars.with(tenPercentOperator); // USD 1.234567

Resources:

Handling money and currencies in Java with JSR 354

Looking into the Java 9 Money and Currency API (JSR 354)

See Also: JSR 354 - Currency and Money