in ML there’s something called “benign overfitting”
I think in quant finance there are also things like “benign lookahead bias” or “benign in-sample fitting”
where committing those supposedly sins are actually beneficial/non-detrimental(?)
Someone asked about red flags to look for when applying to quant firms, so I'll start with the most obvious one: When they have 0 Chinese, Indians, or Russians on the team.
the deeper i go into programming the more i realize that almost everything is just data flow: if you can figure out how the data should flow, you nail 80% of it.
Hey chess fans! Exciting news! The FIDE World Corporate Chess Championship is happening in New York! Don't miss Goldman Sachs, Google, BlackRock, and many more teams battling it out for the cup from June 15-17 in the heart of Wall Street. (1/3)