>You might have this backwards. Actual informed people have a good idea of the scale that these funds are operating at, and can understand without context wheth

>You might have this backwards. Actual informed people have a good idea of the scale that these funds are operating at, and can understand without context whether $3.7bn is a lot. Even "actual informed people" won't necessarily know how much much any given fund has in AUM. >Losing $3.7bn trading stocks in a tech bull-market the likes of which we've never seen is...not good, regardless of the fund size. Actually, fund size is very relevant. Losing $3.7b as a $10b fund will put you in at least 37% drawdown which can put you past a board-controlled threshold at which trading might pause or a re-evaluation of the trading strategies might be triggered. Losing $3.7b on a $100b account is 3.7% which is business as usual really. If you have a machine learning background this analogy might be useful: if you're building an algo trading strategy then training your model on absolute dollar returns data will be nonsense. What makes more sense is calculating the relative returns or even log-returns because then we're encoding an actual relative change.