2016
DOI: 10.1016/j.sbspro.2016.11.039
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Central Banks’ Communication Strategy and Content Analysis of Monetary Policy Statements: The Case of Fed, ECB and CBRT

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Cited by 27 publications
(13 citation statements)
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“…As part of the prediction of market performance, we mention a study of annual reports of more than a thousand of firms (see Balakrishnan et al, 2010), and also the analysis of financial reports through the connection between the words and the financial risk of various companies and banks (see Tsai and Wang, 2017;Agarwal et al, 2019). Furthermore, it is worthy to mention the case of Kahveci and Odabaş (2016), in which the textual analysis has been employed to explore the semantic of monetary policy documents from the Federal Reserve Board, In a more general economic and financial framework we can evidence many works that deepen text mining on the analysis of stock markets, stock returns, trading and, more generally, on the ability of transforming qualitative variables into quantitative measures to improve financial fore-casts and market predictions (see, e.g. Blasco et al, 2005;Schumaker and Chen, 2009;Groth and Muntermann, 2011;Huang and Li, 2011;Loughran and McDonald, 2016;Mishra and Singh, 2018).…”
Section: Literature Reviewmentioning
confidence: 99%
“…As part of the prediction of market performance, we mention a study of annual reports of more than a thousand of firms (see Balakrishnan et al, 2010), and also the analysis of financial reports through the connection between the words and the financial risk of various companies and banks (see Tsai and Wang, 2017;Agarwal et al, 2019). Furthermore, it is worthy to mention the case of Kahveci and Odabaş (2016), in which the textual analysis has been employed to explore the semantic of monetary policy documents from the Federal Reserve Board, In a more general economic and financial framework we can evidence many works that deepen text mining on the analysis of stock markets, stock returns, trading and, more generally, on the ability of transforming qualitative variables into quantitative measures to improve financial fore-casts and market predictions (see, e.g. Blasco et al, 2005;Schumaker and Chen, 2009;Groth and Muntermann, 2011;Huang and Li, 2011;Loughran and McDonald, 2016;Mishra and Singh, 2018).…”
Section: Literature Reviewmentioning
confidence: 99%
“…In this context, central banks have started to implement unconventional monetary policy measures and to practice quantitative easing and s. 25). The post-crisis transition in Central Bank policy from mystery and inscrutability to the era of transparency and the importance of "forward guidance" is a demonstration of how rapidly and radically communication strategy has changed (Kahveci and Odabaş, 2016). Importantly, forward guidance is designed to contribute to monetary easing and to halt the decline in economic activity.…”
Section: Unconventional Policiesmentioning
confidence: 99%
“…The FOMC's communication strategy involves issuing a policy statement after each meeting while the minutes of the meetings are released to the public three weeks after the policy decision date. Similar monetary policy communication strategies are in place in several other central banks around the world, including the Bank of England, Bank of Japan, Bank of In line with the increased level of communication among central banks, a new but growing body of literature has focused on the extraction of useful insights from monetary policy documents using different text mining techniques (see Shirota, 2015;Bruno, 2016;Kahveci and Odabas, 2016;Luangaram and Wongwachara, 2017;Oshima and Matsubayashi, 2018;Park et al, 2019;Shapiro and Wilson, 2019;Omotosho, 2020). According to Blinder et al (2008), different methods are available for the analysis of central bank communication; including the indirect approach (whereby financial market reactions to policy announcements are measured using event windows), and a direct approach (whereby the researcher provides a subjective assessment of central bank communication by manually reading through the policy document and coding its contents into numerical scales).…”
Section: Introductionmentioning
confidence: 99%