Words Matter: Effects of Semantic Similarity of Monetary Policy Committee's Decision on Financial Market Volatility
Sapphasak Chatchawan ()
PIER Discussion Papers from Puey Ungphakorn Institute for Economic Research
The objective of the paper is to study the effects of semantic similarity of the Bank of Thailand's press releases on volatility of financial markets in Thailand from 2010-2018. The Natural Language Processing (NLP) is employed to construct the semantic similarity from 72 press releases. The semantic similarity represents the public signal that the central bank delivers to the public in the framework of a Keynesian beauty contest game. The semantic similarity of MPC press releases significantly reduce the volatility in 1-month, 3-month, 10-year and 15-year government debt securities. Findings imply that relatively similar language in the MPC press releases reduces the volatility in short-term and long-term bonds. Effects of semantic similarity matter most in the volatility of 10-year bond yield. However, effects of semantic similarity are insignificant in both equity and foreign exchange markets.
Keywords: Bank; Volatility; Financial Markets; Monetary Policy; Natural Language Processing (search for similar items in EconPapers)
JEL-codes: E52 E58 (search for similar items in EconPapers)
Pages: 17 page
Date: 2019-12, Revised 2019-12
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Persistent link: https://EconPapers.repec.org/RePEc:pui:dpaper:121
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