I remember sometime aback sparking conversation on how there would always be problems with investable attributes not taking into consideration certain strategy parameters, etc and how there would be no level playground until the algos can rate the strategy in it's own class/catergory.
First first things the strategies need to be classified into groups and then adjust the way algos rate each of them depending on their class/type so that swing trading strategy are not penalized for being "swing traders". It should not be that a trader should change/modify a strategy just to get good score.
Now we stumble upon the recognition of trading style (for more dynamic traders) which exists a mixture of styles opposed to just concentrating on a particular trading style. A constantly updating algo based on trades data to rate trade style first and then give weight according to the trades within that trade style.
eg. Pie chart to show that based on the trade data an underlying strategy is 20% - scalping, 15% intraday, 20% - swing, 35% position and 10% HFT and these populate as data is collected and to have each of the styles rated by the algorithms accordingly.
So the strategy parameters for all classes would be predefined already as well giving investors access to more data to make an informed decision and could also inform traders on what strategies work best when and on what pairs, etc
I see that the details for differentiating trading style, etc can be extracted from the existing metrics but it can be more user friendly for the less tech savy but where it misses out is that the algos don't adjust the way a strategy is rated based on its native strategy style.