I never said you should use floating-point numbers for currency. I said that if you are not aware of the shortcomings of floating-point numbers (the only numeri

I never said you should use floating-point numbers for currency. I said that if you are not aware of the shortcomings of floating-point numbers (the only numeric type in JavaScript, not counting workarounds like typed arrays) you should not be working with values representing currencies until you do. Fixed-point numbers (aka "decimal" type in Java, C# and others) are the preferred way to deal with this problem as I mentioned in this same discussion hours ago. Now, in the example you presented, you have a round-off error amplication problem where the round-off error grows larger than the epsilon. You can avoid that using the Kahan summation algorithm. https://en.wikipedia.org/wiki/Kahan_summation_algorithm https://en.wikipedia.org/wiki/Kahan_summation_algorithm const arr = [0.1, 0.2, 0.9, 0.6]; let sum = 0.0; let c = 0.0; for(let i = 0, l = arr.length; i < l; i++) { y = arr[i] - c; t = sum + y; c = (t - sum) - y; sum = t; } Now you evaluate sum, and it's 1.8 as expected.