Funding
Funding not disclosed
Founders
Product
Problem
Analysts, traders, and researchers often rely on fragmented, subscription‑based tools or low‑quality public data, which can limit the depth and reproducibility of quantitative finance and scientific analysis. Access to rigorous, peer‑reviewed research and reliable offline software is scarce, especially for users who need full control over data and modeling assumptions.
Solution
Faber delivers a curated suite of PhD‑level research papers and professional‑grade analytical software that operate locally without cloud dependencies or recurring fees. Its financial tools include a Monte Carlo‑enabled discounted cash‑flow (DCF) modeler, a portfolio tracker with real‑time P&L and multi‑criteria stock screening, an SEC filing analyzer that extracts key metrics, and a backtesting platform for testing trading signals. Each application runs in a browser or as a standalone executable, ensuring data never leaves the user’s machine and eliminating the need for accounts or subscriptions. The research library spans quantitative finance, antimatter physics, stellar engineering, and related fields, providing open access to empirical studies and theoretical frameworks. By combining rigorous scholarship with transparent, offline tools, Faber enables serious analysts to conduct reproducible, high‑precision work without vendor lock‑in.
Target Audience
Primary customers are quantitative analysts, equity researchers, independent traders, and academic or industry scientists who need rigorous, self‑contained tools and peer‑reviewed research for finance or physical science projects.
Features
- DCF modeler with three scenario sets (Bear, Base, Bull) and integrated Monte Carlo simulation for probability‑weighted valuation distributions
- Portfolio tracker built on a lightweight Python web server, offering real‑time P&L, sector allocation charts, and an on‑demand S&P 500 screener with 12 simultaneous filter criteria
- SEC filing analyzer that parses 10‑K, 10‑Q, 8‑K and proxy documents, extracts financial metrics, and generates summary reports automatically
- Trading signal backtester (in development) for historical strategy testing with performance analytics such as Sharpe ratio and drawdown
- AI‑powered text‑to‑speech desktop app (Vox Codex) that converts manuscripts to narrated MP3s locally, with multiple voice options and no per‑minute charges
- All software runs offline, requires no cloud services, and is distributed as a one‑time purchase with free updates
- Open‑access research papers covering dividend behavior, RSI backtests, Higgs‑induced gravity, antimatter theory, and other advanced scientific topics