Extracting the "dot plot" economic projections posted online by the Federal Open Market Committee
Real-time macroeconomic & financial markets dashboard featuring AI sentiment analysis , Fed Funds backtesting, and live multi-asset tracking
End-to-End Python implementation of "FedSight AI" multi-agent system for Federal Funds Target Rate prediction (NeurIPS 2025 Workshop). Simulates FOMC deliberations using LLMs with Chain-of-Draft reasoning and In-Context Learning. Integrates structured macro indicators with unstructured narratives (Beige Book, Dot Plots).
Open macro-cycle observatory for current regimes, long-wave history, official macro release ledgers, watchlists, and evidence-gated readings.
Agentic RAG system using LangGraph to analyse FOMC documents, detect monetary policy shifts, and identify contradictions across Federal Reserve meetings. Built with Pinecone, GPT-4o, FastAPI, and evaluated with RAGAS.
A command-line tool for analyzing Federal Reserve policy scenarios by finding historical analogues based on unemployment and inflation conditions.
Fully automated macro calendar — FOMC, BOE, ECB, BOJ, US CPI/PPI/NFP in Google Calendar. Completely free (no paid APIs).
Personal monitor of Federal Reserve communications: scrapes Board governor speeches and FOMC docs, scores hawk/dove tone via Claude, alerts on tone shifts.
美联储主席 Kevin Warsh 首场 FOMC 新闻发布会(2026 年 6 月 17 日)完整中英双语逐字稿。非官方,本地转录整理。
Projet de NLP appliqué aux conférences de presse du FOMC (2020–2025) visant à analyser l’évolution du discours monétaire de la Réserve fédérale américaine. À travers des méthodes de text mining, TF-IDF, clustering et analyse de sentiments, le projet étudie les thèmes macroéconomiques dominants et leurs corrélations avec les marchés financiers.
This repository automatically scrapes the past and future FOMC meeting statements & minutes - tracking US monetary policy changes through time.
Empirical macro-finance project on FOMC statement entropy and post-meeting VIX reactions
Study of the impact of monetary policy and central bank sentiment on gold price dynamics. Built a dataset combining quantitative market variables and qualitative FOMC-statement features, then evaluated predictive power through rolling Ridge regression and GARCH models.
Full-stack ML project predicting US Treasury yield moves after FOMC meetings: DistilBERT sentiment + macro regime classification + walk-forward gradient boosting, with a Next.js dashboard
Leakage-free real-time evaluation of open-weights LLMs for US CPI inflation forecasting. Introduces the memorization premium (seen vs. unseen forecast-error gap) and a three-role decomposition (direct forecaster, FOMC-text extractor, combiner). Reproduces every number in the IJF manuscript's Table 3 from the committed checkpoint.
Undergraduate thesis: measuring non-verbal cues in FOMC press conferences and testing them against high-frequency futures reactions.
FOMC sentiment resources linked to FinBERT aspect classification model
An evidence based monetary policy intelligence system. Combines FOMC communications with FRED economic data to detect policy shifts and narrative divergences.
以 FOMC 為 benchmark 的 AI 決策記憶系統:把每次重大決策存成可追溯的 DecisionTrace,並在第一個反證出現時重開討論。含離線 RAG 投票模擬(244 場會議、3,553 段原文,零安裝)
Output Federal Reserve FOMC Meeting Dates in a plain text ISO date format for further use elsewhere
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