The impact of the content of Federal Open Market Committee post-meeting statements on financial markets – text mining approach

Ewelina Osowska and Piotr Wójcik
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Ewelina Osowska: Data Science Lab WNE UW, University of Warsaw

No 2020-33, Working Papers from Faculty of Economic Sciences, University of Warsaw

Abstract: This article examines the impact of FOMC statements on stock and foreign exchange markets with the use of text mining and modelling methods including linear and non-linear algorithms. Proposed methodology is based on calculating the FOMC statements’ tone called as sentiment and incorporate it as a potential predictor in the modelling process. Additionally, we incorporate the market surprise component as well as two financial indicators namely Purchasing Managers' Index and Consumer confidence index that gauge for corporate managers and retail customers assessment of the economic situation and potential fluctuations. Eight event windows around the event are considered: 60-minute and 20-minute windows before the event and also 15-minute, 20-minute, 25-minute, 30-minute, 60-minute and 120-minute windows after the event. Research has shown that given linear models the sentiment of FOMC statements does not generate a significant response in any of the analyzed event windows neither for the S&P 500 Index nor for the spot price on the EUR/USD currency pair. However, significant predictors occurred to be market shock in case of both S&P 500 Index and EUR/USD spot price, PMI in case of EUR/USD spot price and also CCI in case of EUR/USD spot price. Given non-linear models, the negative relation of statement’s sentiment score and the model prediction is observed for EUR/USD spot price.

Keywords: FOMC Statements; event arbitrage; sentiment analysis; financial markets prediction (search for similar items in EconPapers)
JEL-codes: C14 G14 G15 (search for similar items in EconPapers)
Pages: 46 pages
Date: 2020
New Economics Papers: this item is included in nep-mac and nep-ore
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