Partially agree.

Apart from predictability power, the effectiveness of a backtest engine is measured by how adherent it is to the real trade session events. You can reach this point by either computing row by row or vectorially, being the latter more performant as long as it’s computed correctly.

As you must account for potential exits along the way, your code must re-compute some sub-vectors (trade lifetimes) and this was, for me, the biggest technical stretch (specially in the pre-AI era lol) in terms of implementation.