Improve performance

[ayushkrtiwari]

Description
Factor implementations currently rely on Python loops for cross-sectional operations; this causes slow runs for large universes and long backtests.

Impact
Large performance overhead for real-world sized universes (hundreds to thousands of tickers).

Related Files

• src/quant_research_starter/factors/ (or equivalent)
• code that applies factor calculations per-symbol in a for-loop

Suggestions

• Replace per-symbol loops with pandas groupby/apply or numpy vectorized ops.
• Add a benchmark script in examples/benchmarks/ to measure before/after improvements.

Labels: performance, enhancement
Difficulty: hard

[adityacosmos24]

@ayushkrtiwari assign this to me

[ayushkrtiwari]

@adityacosmos24 please submit your PR within max(2 days, till next assignee gets assigned)