{"repo":"Fluxara-GOD/fluxara1-audit-verification-pack","free":true,"listed":false,"github":"https://github.com/Fluxara-GOD/fluxara1-audit-verification-pack","clone":"git clone https://github.com/Fluxara-GOD/fluxara1-audit-verification-pack.git","description":"FLUXARA-1 independent audit verification pack for peer review. Contains frozen engine outputs, replication scripts, and vBase blockchain temporal proofs (SR 11-7 / Basel IRB aligned).","language":null,"stars":26,"topics":["b2b-saas","benchmark-framework","black-swan","case-study","model-risk-management","peer-review","portfolio-protection","quantitative-finance","reproducibility","risk-management"],"license":null,"category":"trading","readme_excerpt":"FLUXARA-1 — Independent Audit Verification Pack Reproducible Benchmark Data for Peer Review 1. The Zero-History Mechanism FLUXARA-1 is a long-cycle structural risk engine built on a strict Zero-History Mechanism audited under SR 11-7 / Basel IRB / GIPS-adapted validation standards. Unlike traditional machine learning models or statistical systems that forecast by \"learning\" from past price returns—leaving them blind to unprecedented Black Swan events—FLUXARA-1 does not train on historical returns. Instead, it purely calculates momentum and phase tension across Space-Time coordinates through 5 physical weight layers, providing an objective framework for detecting structural fragility and phase transition boundaries. 2. Research Scope & Evaluation Dataset This repository contains the replication packs for a multi-cohort validation audit designed to test the engine's long-cycle forecasting limits and evaluate if ex-ante risk warnings align with ex-post realized stress. The benchmark study encompasses two primary research domains: Part 1: Financial Macro-Cycles: Audits the engine's core capability to predict structural macro-reversals and capital flow shifts across two highly divergent asset classes: Gold (2009–2018) and Bitcoin (2019–2025) . Under the bsi finance semantic rubric.md framework (included in the finance pack), verification is executed across three distinct methodology tracks: 1. BSI Proximity Alignment: Validates the ex-ante Black Swan Index (BSI%) —calculated via a","default_branch":null,"files":null,"tree":[],"storefront":"/r/Fluxara-GOD","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/Fluxara-GOD/fluxara1-audit-verification-pack/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}