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Monetary policy pronouncements by Federal Open Market Committee (FOMC) are a major driver of financial market returns.
Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, M. Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
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Finbert: Financial sentiment analysis with pre-trained language models
Dogu Araci. 2019 · 1908
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Do conference calls affect analysts’ forecasts?
Robert M Bowen, Angela K Davis, and Dawn A Matsumoto. 2002 · 2002
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Open versus closed conference calls: the determinants and effects of broadening access to disclosure
Brian J Bushee, Dawn A Matsumoto, and Gregory S Miller. 2003 · 2003
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Finbert: A pretrained language model for financial communications
Yi Yang, Mark Christopher Siy Uy, and Allen Huang. 2020 · 2006
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Quest for central bank communication: Does it pay to be “talkative”?
Marek Rozkrut, Krzysztof Rybiński, Lucyna Sztaba, and Radosław Szwaja. 2007 · 2007
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Natural language processing with Python: analyzing text with the natural language toolkit
Steven Bird, Ewan Klein, and Edward Loper. 2009 · 2009
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When is a liability not a liability? textual analysis, dictionaries, and 10-ks
Tim Loughran and Bill McDonald. 2011 · 2011
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Lost in discussion? tracking opinion groups in complex political discussions by the example of the FOMC meeting transcriptions
Cäcilia Zirn, Robert Meusel, and Heiner Stuckenschmidt. 2015 · 2015
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Tensorflow: A system for large-scale machine learning
Martin Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, Manjunath Kudlur, Josh Levenberg, Rajat Monga, Sherry Moore, Derek G. Murray, Benoit Steiner, Paul Tucker, Vijay Vasudevan, Pete Warden, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng. 2016 · 2016
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December doldrums, investor distraction, and stock market reaction to unscheduled news events
Sudheer Chava and Nikhil Paradkar. 2016 · 2016
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Shocking language: Understanding the macroeconomic effects of central bank communication
Stephen Hansen and Michael McMahon. 2016 · 2016
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Deciphering fedspeak: The information content of fomc meetings
Narasimhan Jegadeesh and Di Wu. 2017 · 2017
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Between hawks and doves: measuring central bank communication
Ellen Tobback, Stefano Nardelli, and David Martens. 2017 · 2017
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Deep learning for stock market prediction from financial news articles
Manuel R Vargas, Beatriz SLP De Lima, and Alexandre G Evsukoff. 2017 · 2017
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
Cited alongside, same era.
Transparency and deliberation within the fomc: a computational linguistics approach
Stephen Hansen, Michael McMahon, and Andrea Prat. 2018 · 2018
Cited alongside, same era.
High-frequency identification of monetary non-neutrality: the information effect
Emi Nakamura and Jón Steinsson. 2018 · 2018
Cited alongside, same era.
Big data: Deep learning for financial sentiment analysis
Sahar Sohangir, Dingding Wang, Anna Pomeranets, and Taghi M Khoshgoftaar. 2018 · 2018
Cited alongside, same era.
Natural language based financial forecasting: a survey
Frank Z Xing, Erik Cambria, and Roy E Welsch. 2018 · 2018
Cited alongside, same era.
Buzzwords?
The tone of the beige book and the pre-fomc announcement drift
Yasutomo Tsukioka and Takahiro Yamasaki. 2020 · 2020
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Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander M. Rush. 2020 · 2020
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The voice of monetary policy
Yuriy Gorodnichenko, Tho Pham, and Oleksandr Talavera. 2021 · 2021
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Using word embedding to reveal monetary policy explanation changes
Akira Matsui, Xiang Ren, and Emilio Ferrara. 2021 · 2021
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Benchmarking machine learning models to predict corporate bankruptcy
Emmanuel Alanis, Sudheer Chava, and Agam Shah. 2022 · 2022
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Sudheer Chava, Wendi Du, and Nikhil Paradkar. 2019 · 2019
Cited alongside, same era.
Stock returns over the fomc cycle
Anna Cieslak, Adair Morse, and Annette Vissing-Jorgensen. 2019 · 2019
Cited alongside, same era.
Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala. 2019 · 2019
Cited alongside, same era.
Does central bank tone move asset prices?
Maik Schmeling and Christian Wagner. 2019 · 2019
Cited alongside, same era.
Does central bank communication signal future monetary policy in a (post)-crisis era? the case of the ecb
Hamza Bennani, Nicolas Fanta, Pavel Gertler, and Roman Horvath. 2020 · 2020
Cited alongside, same era.
Oxford Guide to Plain English
M. Cutts. 2020 · 2020
Cited alongside, same era.
Starting from a blank page? semantic similarity in central bank communication and market volatility
Michael Ehrmann and Jonathan Talmi. 2020 · 2020
Cited alongside, same era.
Dario Caldara and Matteo Iacoviello. 2022 · 2022
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Measuring firm-level inflation exposure: A deep learning approach
Sudheer Chava, Wendi Du, Agam Shah, and Linghang Zeng. 2022 · 2022
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Monetary policy communications and their effects on household inflation expectations
Olivier Coibion, Yuriy Gorodnichenko, and Michael Weber. 2022 · 2022
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Fine-grained, aspect-based sentiment analysis on economic and financial lexicon
Sergio Consoli, Luca Barbaglia, and Sebastiano Manzan. 2022 · 2022
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Monopoly: Financial prediction from monetary policy conference videos using multimodal cues
Puneet Mathur, Atula Neerkaje, Malika Chhibber, Ramit Sawhney, Fuming Guo, Franck Dernoncourt, Sanghamitra Dutta, and Dinesh Manocha. 2022 · 2022
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When flue meets flang: Benchmarks and large pretrained language model for financial domain
Raj Sanjay Shah, Kunal Chawla, Dheeraj Eidnani, Agam Shah, Wendi Du, Sudheer Chava, Natraj Raman, Charese Smiley, Jiaao Chen, and Diyi Yang. 2022 · 2022
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Chatgpt survey: Performance on nlp datasets
Matúš Pikuliak. 2023 · 2023
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Closed ai models make bad baselines
Anna Rogers, Niranjan Balasubramanian, Leon Derczynski, Jesse Dodge, Alexander Koller, Sasha Luccioni, Maarten Sap, Roy Schwartz, Noah A. Smith, and Emma Strubell. 2023 · 2023
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The effects of the content of FOMC communications on US treasury rates
Christopher Rohlfs, Sunandan Chakraborty, and Lakshminarayanan Subramanian. 2016 · 2096
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