Liberal arts brains can’t really be trained to get things truly clear.

Liberal arts students claim they’ve thoroughly familiarized themselves with history’s lessons and experiences, with a big-picture view and a cognitive perspective.
This is the kind of self-serving narration.
Once you put them into the market, these liberal arts students show up as “carving a boat to seek a sword” and “over-analysis,” never quite grasping what the true focus is.
When facing randomness, they always come up with “pale, powerless stories.”
How do science students learn to get things clear?
First, use mathematical descriptions of relationships to identify the real variables that drive the market.
Second, don’t rely on historical patterns; instead, do data calibration to find the current optimal decision.
It’s algorithms within algorithms—the most fundamental layer of the algorithm stack.
For a lifetime, liberal arts students find it very difficult to learn things clearly,
and they don’t have a big-picture view either.
Mathematics can compute “the results under hundreds of dimensions of observational data,”
but liberal arts students don’t have such computational tools.
They can only desperately fit multiple concepts into the books they’ve read,
yet they’re powerless when confronted with real market performance.