grunching here to a moderate degree.............

if I model stock market returns using normal returns, then yes, volatility drag is a real thing. of course, if I use 25% standard deviation then I will eventually have a period with a return below -100%. and then the model dies anyway.

if I use lognormal returns, then there is no volatility drag.

I have no idea why you would use normal returns or lognormal. maybe someone can explain

while the author perhaps used sensational headline to make a definitional case, I have heard people tell me, "the stock market is a complete joke.. if I lose 10% one quarter and gain 10% the next month, I don't breakeven, I lose 4%".... and of course, all that person has done is a mathematical trick with little real world meaning.

anyway, can someone explain why you would use normal or lognormal or something else (that is somewhat practical to implement)