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http://dx.doi.org/10.13106/jafeb.2021.vol8.no4.0113

Do Words in Central Bank Press Releases Affect Thailand's Financial Markets?  

CHATCHAWAN, Sapphasak (Faculty of Commerce and Accountancy, Thammasat University)
Publication Information
The Journal of Asian Finance, Economics and Business / v.8, no.4, 2021 , pp. 113-124 More about this Journal
Abstract
The study investigates how financial markets respond to a shock to tone and semantic similarity of the Bank of Thailand press releases. The techniques in natural language processing are employed to quantify the tone and the semantic similarity of 69 press releases from 2010 to 2018. The corpus of the press releases is accessible to the general public. Stock market returns and bond yields are measured by logged return on SET50 and short-term and long-term government bonds, respectively. Data are daily from January 4, 2010, to August 8, 2019. The study uses the Structural Vector Auto Regressive model (SVAR) to analyze the effects of unanticipated and temporary shocks to the tone and the semantic similarity on bond yields and stock market returns. Impulse response functions are also constructed for the analysis. The results show that 1-month, 3-month, 6-month and 1-year bond yields significantly increase in response to a positive shock to the tone of press releases and 1-month, 3-month, 6-month, 1-year and 25-year bond yields significantly increase in response to a positive shock to the semantic similarity. Interestingly, stock market returns obtained from the SET50 index insignificantly respond to the shocks from the tone and the semantic similarity of the press releases.
Keywords
Central Bank Communication; Financial Markets; Text Mining;
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