## #80 – Use Decimal Type for Monetary Calculations

September 5, 2010 Leave a comment

Since floating point numbers are stored as a binary data, most floating point numbers cannot be stored exactly and suffer from *round-off error*–the difference between the true mathematical value and the value being stored digitally.

Because of how floating point numbers are stored, even simple base-10 numbers with not much precision cannot be represented exactly. Consider the example below:

float f1 = 0.1f; float error = (f1 * 1000.0f) - 100.0f; // Error is 1.49e-6

This demonstrates that we weren’t able to store exactly the value of 0.1, but the value nearest to 0.1 that was representable using the **float** type.

This inaccuracy leads to errors when we try to store values representing financial transactions and perform simple mathematical operations on the values. Because of this, you should always use the **decimal** type for storing financial data:

decimal f1 = 0.1m; decimal error = (f1 * 999999999.0m) - 99999999.9m; // Error still 0