https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
This dataset contains the text from Federal Reserve FOMC (Federal Open Market Committee) meeting minutes and statements, collected by scraping the Federal Reserve's website. The data spans a specific period of time, providing insights into the central bank's monetary policy decisions and discussions.
The dataset consists of the following columns:
The data is collected from the official Federal Reserve website (https://www.federalreserve.gov) using a custom Python scraper built with BeautifulSoup.
This dataset can be used for various purposes, such as:
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The benchmark interest rate in the United States was last recorded at 4.50 percent. This dataset provides the latest reported value for - United States Fed Funds Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.
https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for FOMC Summary of Economic Projections for the Fed Funds Rate, Median (FEDTARMD) from 2025 to 2027 about projection, federal, median, rate, and USA.
MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
FOMC Meeting Policy Statements Dataset (Year 2000+, updated monthly)
Overview
This dataset contains the policy statements released by the Federal Open Market Committee (FOMC) following each of its meetings from year 2000 onwords. The FOMC, a component of the U.S. Federal Reserve System, determines monetary policy in the United States. The statements provide insights into the committee’s policy decisions, economic outlook, and forward guidance.
Background on Policy… See the full description on the dataset page: https://huggingface.co/datasets/Coding-Fish/fomc-statements.
The Senior Loan Officer Opinion Survey on Bank Lending Practices (SLOOS) surveys up to 80 large domestic banks and 24 U.S. branches and agencies of foreign banks. The Federal Reserve generally conducts the survey quarterly, timing it so that results are available for the January/February, April/May, August, and October/November meetings of the Federal Open Market Committee (FOMC). The Federal Reserve occasionally conducts one or two additional surveys during the year. Questions cover changes in the standards and terms of the banks' lending and the state of business and household demand for loans. The survey often includes questions on other topics of current interest. The survey results are released on Mondays after the FOMC meeting.
Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
License information was derived automatically
Label Interpretation
LABEL_2: NeutralLABEL_1: HawkishLABEL_0: Dovish
Citation and Contact Information
Cite
Please cite our paper if you use any code, data, or models. @inproceedings{shah-etal-2023-trillion, title = "Trillion Dollar Words: A New Financial Dataset, Task {&} Market Analysis", author = "Shah, Agam and Paturi, Suvan and Chava, Sudheer", booktitle = "Proceedings of the 61st Annual Meeting of the Association for… See the full description on the dataset page: https://huggingface.co/datasets/gtfintechlab/fomc_communication.
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https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
This dataset contains the text from Federal Reserve FOMC (Federal Open Market Committee) meeting minutes and statements, collected by scraping the Federal Reserve's website. The data spans a specific period of time, providing insights into the central bank's monetary policy decisions and discussions.
The dataset consists of the following columns:
The data is collected from the official Federal Reserve website (https://www.federalreserve.gov) using a custom Python scraper built with BeautifulSoup.
This dataset can be used for various purposes, such as: