> because that type of rounding error can end up in the millions over the course of a year if you deal 100+ million dollar transactions 5-6 times a day. I thin

> because that type of rounding error can end up in the millions over the course of a year if you deal 100+ million dollar transactions 5-6 times a day. I think we're talking past each other a bit. Financial products pricers themselves only have as much precision as the inputs, which in many cases might only have 3-5 significant figures. Using arbitrary precision math doesn't buy you any more precision than what your inputs have. Remember that a 64-bit float gives you 52 bits ~ 14 decimal digits of precision, so unless you're doing something that has terrible numerical stability, the error of your model assumptions and inputs will always dominate floating point error. It doesn't matter if your model spits out $XXXXXX.08 or $XXXXXX.15 - both answers are essentially the same. Just to provide context, we were pricing deals with notional amounts in the billions and PVs up to tens of millions. Note that we're comfortable doing nuclear bomb simulations or climate models using FP64 floating point calculations, for the same reasons — the error in your model is bigger anyway. > they would have you fired over the superfluous loss of a dollar The handling of customer accounts is different at a bank since you're not supposed to be creating or losing money out of thin air—that's the Fed's job. But that's not what the article claims—it claims that any monetary amount, anywhere, should never use a float, which IMO overstates things from both a business and maths standpoint.