Latent semantic analysis of the FOMC statements
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Abstract
Suggested Citation
DOI: 10.1108/RAF-10-2015-0149
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Cited by:
- Ewelina Osowska & Piotr Wójcik, 2020. "The impact of the content of Federal Open Market Committee post-meeting statements on financial markets – text mining approach," Working Papers 2020-33, Faculty of Economic Sciences, University of Warsaw.
- Amrendra Pandey & Jagadish Shettigar & Amarnath Bose, 2021. "Evaluation of the Inflation Forecasting Process of the Reserve Bank of India: A Text Analysis Approach," SAGE Open, , vol. 11(3), pages 21582440211, July.
- Ioanna Kountouri & Eleftherios Manousakis & Andrianos E. Tsekrekos, 2019. "Latent semantic analysis of corporate social responsibility reports (with an application to Hellenic firms)," International Journal of Disclosure and Governance, Palgrave Macmillan, vol. 16(1), pages 1-19, March.
- Ancil Crayton, 2018. "Central Bank Communication and the Yield Curve: A Semi-Automatic Approach using Non-Negative Matrix Factorization," Papers 1809.08718, arXiv.org.
More about this item
Keywords
Content analysis; Monetary policy; Latent semantic analysis; Fed wording; FOMC statements; Treasury market; E5; F3; G1;All these keywords.
JEL classification:
- E5 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit
- F3 - International Economics - - International Finance
- G1 - Financial Economics - - General Financial Markets
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