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FactorForge

LLM-assisted quantitative factor research with safe DSL validation, benchmark comparisons, and cost-aware Top-K backtesting

Details

External ID
1379868599
Source
GITHUB
Company
—
Product
FactorForge
Website domain
github.com
Launched
Sept. 21, 2026
Cohort
—
Upvotes
20
Upvotes percentile
0.6029976940814757
Tags
—
Fetched at
Sept. 25, 2026, 5:02 p.m.
Updated at
Sept. 25, 2026, 5:02 p.m.

Enrichment

Theme
ML inference and model optimization
Vertical
Fintech
Function
Analytics & BI
Audience
Developer
AI stance
AI feature
Project type
Commercial product
Normalized one-liner
llm-assisted quantitative factor research and backtesting tool for quants
Manually corrected
False

Could you build this?

Partial Creating the LLM prompt interface and basic backtesting UI is straightforward, but building a mathematically sound financial backtesting engine with realistic slippage, corporate actions, and survivorship-bias-free data is non-trivial.

What it would actually take: A viable platform needs a high-performance vector-based backtesting pipeline (e.g., Python using Polars, Numba, or DuckDB) executing custom DSL expressions, paired with high-quality point-in-time equity market data (like CRSP or Compustat). The hard parts are preventing data lookahead bias, accurately modeling transaction costs/turnover, and safely sandboxing user DSL execution. Expertise in quantitative finance and robust financial data engineering is required.

Competitors

Other products that read as similar to this one — 786 launches clear the similarity bar, closest 8 shown.

Attention rank: #276 of 787 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 327 days after the earliest competitor.

Other launches for this product

Same idea, different domain

Nobody's really built a analytics & bi tool for Legal yet.