The three metrics feel more logarithmic than linear, so it’d probably make more sense to use addition rather than multiplication. However, I’ve tested it and it practically doesn’t change the ordering for the top 50% and mostly influences the lower results (especially those that multiply to 0 😊).
(Also, it’s clearly an irrelevant level of analysis, as I’d expect the problems to be more in the choice and definition of the metrics, and the valuations thereof)
The three metrics feel more logarithmic than linear, so it’d probably make more sense to use addition rather than multiplication. However, I’ve tested it and it practically doesn’t change the ordering for the top 50% and mostly influences the lower results (especially those that multiply to 0 😊).
(Also, it’s clearly an irrelevant level of analysis, as I’d expect the problems to be more in the choice and definition of the metrics, and the valuations thereof)
I see what you mean, particularly for scale. But not so much for decision-relevance and forecasting fit.
Also, the threshold for decision-relevance is in a sense lower for larger events, so I think that evens out some of the variance.