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ECB communication on Monetary Policy (I M P

ECB communication on Monetary Policy (I M P

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Article
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We develop a field-specific dictionary to measure the stance of the European Central Bank (ECB) monetary policy (dovish, neutral, hawkish) and the state of the Eurozone economy (positive, neutral, negative) through the content of ECB press conferences. In contrast with traditional textual analysis, we propose a novel approach using term-weighting a...

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Citations

... In this context, the sentiment indexes based on textual analysis can be used to measure expectations and confidence or to evaluate the economic shocks (Algaba et al., 2020). Sentiment analysis is a strong topic in behavioural economics, the main research questions being related to determinants of sentiments and impact of sentiments (Picault and Renault, 2017). ...
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Considering the necessity to have accurate inflation forecasts in a pandemic period with hyperinflation in many countries, the aim of this study is to improve the quarterly inflation forecasts provided by the National Bank of Romania using sentiment analysis. The sentiment forecasts based on narratives in the official reports of the central banks outperformed the numerical predictions of the central bank and various combined forecasts on the horizon 2008:Q1–2021:Q4. In addition, more forecasting models based on machine learning, sentiment indices and various forecasts provided by the National Bank of Romania were proposed. The forecasting model that used signals based on Fourier transform as inputs in artificial neural network and support vector machine performed better than all the other models in terms of forecast accuracy.
... The dependent variables employed typically include some short-term reactions by financial markets around monetary policy announcements. 4 Other studies quantify the content of these announcements through text-mining techniques and investigate communication of various central banks, e.g., the ECB (e.g., Picault and Renault, 2017), the FOMC (e.g., Shapiro and Wilson, 2019), the Bundesbank (e.g., Tillmann and Walter, 2018), and the Riksbank (e.g., Apel and Grimaldi, 2014). ...
Article
We empirically examine how the complexity of ECB communications affects financial market trading based on high-frequency data from European stock index futures trading between 2009 and 2017. Analysing the linguistic complexity of the ECB’s introductory statements and differentiating between press conferences with and without announcements of unconventional monetary policy measures (UMPM), we find that more complex communication, i.e. high linguistic complexity and UMPM-announcement, is associated with a lower level of contemporaneous trading activity. Moreover, complex communication leads to a temporal shift in trading activity towards the subsequent Q&A session, which suggests that Q&A sessions facilitate market participants’ information processing.
... Decoding of messages is most effective when the language used is stable, homogeneous, and represented in its richness. The current string in the central bank communication literature uses pre-defined dictionaries, such as Loughran and Mc-Donald (2011), Apel and Grimaldi (2014), and Picault and Renault (2017) for counting terms (for example, positive and negative words) to extract a single dimension (for example, sentiment) from a document. Such a practice equates to an extreme prior of the informativeness of the vast majority of communicated terms, which may only suffice for simple messages, thereby falling short of capturing the domain-specific richness of the representation. ...
... In fact, dictionaries have been explicitly designed for the use in financial and central bank context (e.g. Loughran and Mc-Donald, 2011;Apel and Grimaldi, 2014;Picault and Renault, 2017;Correa et al., 2021). The peculiarity of the terminology spoken in the central bank context necessitates the usage of such central bank-specific dictionaries. ...
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Dictionary approaches are at the forefront of current techniques for quantifying central bank communication. This paper proposes embeddings-a language model trained using machine learning techniques-to locate words and documents in a multidimensional vector space. To accomplish this, we utilize a text corpus that is unparalleled in size and diversity in the central bank communication literature, as well as introduce a novel approach to text quantification from computational linguistics. This enables us to provide high-quality central bank-specific text-representations and demonstrate their applicability through a variety of examples in the fields of central bank objectives, financial uncertainty, and gender bias. JEL: C45, C53, E52, Z13
... The second refers to the various communications (e.g., media interviews, testimonies, conference talks) of the ECB Governing Council members, during which they usually express their views on the future stance of the ECB monetary policy and on the economic outlook. For press conference communications, we gather an exhaustive database containing all the textual content of the ECB press conferences and build quantitative measures for the policy inclination (hawkish versus dovish) and for the economic outlook content inclination (positive economic outlook versus negative) of each communication using the central bank-specific dictionary of Picault and Renault (2017) developed specifically for that purpose. Appendix C provides further details. ...
... We measure their qualitative content in terms of monetary policy inclination (hawkish versus dovish) and communication vis-à-vis the economic outlook (positive versus negative). To do so, we apply the field-specific dictionary developed in Picault and Renault (2017), which aims at capturing these two aspects of the ECB member's speeches, and is exactly built from the ECB members communications' wording. In contrast to standard methods, it uses contiguous sequence of words and a specific term-weighting approach to quantify the content of communication. ...
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We construct a new indicator to capture media sentiment about the European Central Bank monetary policy and its relevant environment by analyzing 25,000 articles from five major international newspapers. Using named entity recognition and part-of-speech tagging, we propose a methodology to dissociate the dissemination of official communications of the central bank from the media comments. The resulting (daily) index correlates with some (monthly) standard measures of economic sentiment but reveals idiosyncratic information on monetary policy. Analyzing the determinants of our index, we find that both press conference and inter-meeting communications of the President significantly affect media sentiment. We then show that, controlling for a large range of factors, daily changes in media sentiment have predictive power for financial market inflation expectations.
... The second refers to the various communications (e.g., media interviews, testimonies, conference talks) of the ECB Governing Council members, during which they usually express their views on the future stance of the ECB monetary policy and on the economic outlook. For press conference communications, we gather an exhaustive database containing all the textual content of the ECB press conferences and build quantitative measures for the policy inclination (hawkish versus dovish) and for the economic outlook content inclination (positive economic outlook versus negative) of each communication using the central bank-specific dictionary of Picault and Renault (2017) developed specifically for that purpose. Appendix C provides further details. ...
... Net economic outlook view (EC) inclination of the ECB President press conference speech, measured using Picault and Renault (2017). ...
... We measure their qualitative content in terms of monetary policy inclination (hawkish versus dovish) and communication vis-à-vis the economic outlook (positive versus negative). To do so, we apply the field-specific dictionary developed in Picault and Renault (2017), which aims at capturing these two aspects of the ECB member's speeches, and is exactly built from the ECB members communications' wording. In contrast to standard methods, it uses contiguous sequence of words and a specific term-weighting approach to quantify the content of communication. ...
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We construct a new indicator to capture media sentiment about the European Central Bank monetary policy and its relevant environment by analyzing 25,000 articles from five major international newspapers. Using named entity recognition and part-of-speech tagging, we propose a methodology to dissociate the dissemination of official communications of the central bank from the media comments. The resulting (daily) index correlates with some (monthly) standard measures of economic sentiment but reveals idiosyncratic information on monetary policy. Analyzing the determinants of our index, we find that both press conference and inter-meeting communications of the President significantly affect media sentiment. We then show that, controlling for a large range of factors, daily changes in media sentiment have predictive power for financial market inflation expectations.
... Hubert and Labondance (2017) find that it compares favorably to others. Picault and Renault (2017), on the other hand, find that the Bennani and Neunkirch (2017) extension of the dictionary does a worse job of predicting the ECB's policy decisions after mid-2011. They instead propose an approach where the single dove-hawk index is replaced by two indexesone for monetary policy and one for the economic outlook. ...
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The purpose of central bank minutes is to give an account of monetary policy meeting discussions to outside observers, thereby enabling them to draw informed conclusions about future policy. However, minutes are by necessity a shortened and edited representation of a broader discussion. Consequently, they may omit information that is predictive of future policy decisions. To investigate this, we compare the predictive content of the Federal Open Market Committee's (FOMC) minutes and transcripts, focusing on dimensions that are likely to be excluded from the minutes, such as the committee's degree of hawkishness, the chairperson's degree of hawkishness, and the level of agreement between committee members. We measure committee and chairperson hawkishness with a new dictionary that is constructed using the FOMC's minutes and transcripts. Agreement is measured using a technique we import from the machine learning literature. We also show that transcripts contain predictive content that is not included in FOMC minutes, macroeconomic variables, financial variables, forecasts, or federal funds rate futures.
... It also includes "dovish" signals such as "high unemployment," "high debt-to-GDP ratio," etc., so the problem here is the ambivalent choice of words in the lexicon on the one hand, and the intention that is motivating the central banker's policy decision on the other. Picault and Renault (2017) assess "low inflationary pressure" from a monetary policy point of view as "dovish," but "high inflation expectations" ("expected annual inflation") as cyclically positive. This study differentiates between monetary policy and macroeconomic developments without, however, distinguishing between the various member states of the euro zone. ...
... Text analytic studies of central bank communication use different methods to quantify the tone of communications. Most studies use standardized dictionaries such as the "financial dictionary" by Loughran and McDonald (2011), the central bank dictionaries by Apel and Grimaldi (2012) or Bennani and Neuenkirch (2017), the Harvard IV psychological dictionary, or the central bank communication index dictionary by Picault and Renault (2017). These dictionaries classify certain words or groups of words as negative, positive and sometimes neutral expressions. ...
... Renault & Picault 2017). This process searches each of the 3071 speeches and interviews for words and counts number of positive or negative words in each speech. ...
Thesis
This dissertation examines the role of monetary trust in monetary theory and policy and its implications for an empirical study on central bank communications. The first part critically examines the role monetary trust has played in economic theory in order to distinguish between two schools of thought. In the first school, monetary trust is defined as a horizontal relation between individuals, an approach to monetary trust that was developed by the neoclassical tradition and that continues to influence monetary theory and policy to this day. In the second approach, monetary trust is viewed from a vertical perspective, focusing on the institutional context and social embeddedness of trust relationships. The conclusion that monetary trust is fundamentally hierarchical drawn from this analysis, motivates the empirical study of the second part. This part analyzes whether German and French central bankers are able to efficiently manage the communicative challenge of pandering to the different demands of their three distinct target audiences—the markets, the state, and the public at large. The empirical methodology for this analysis builds on the growing literature analyzing central bank communications to better understand the political and financial implications of monetary policy. I hope to contribute to this field of research by 1) creating a new database of 21 years of speeches and interviews of the Banque de France, the Bundesbank and the ECB (1999-2019), 2) devising a new method for analyzing communications that takes into account different audiences and 3) providing empirical evidence for the observation that monetary policy is not neutral, i.e., that communications are biased in favor of some economic groups over others. The results of this analysis show that French and German central bankers communicate differently at home and at the European level, and deliver a preliminary confirmation of the hypothesis that central bank communications distinguish between audience groups according to the hypothesized hierarchical taxonomy.
... These analyses use a combination of methods including news search (Baker et al., 2016;Caldara and Iacoviello, 2018;Demiralp et al., 2019;Shapiro et al., 2020), Latent Dirichlet Allocation (Hansen and McMahon, 2016;Hansen et al., 2017;Larsen and Thorsrud, 2019), dictionary methods (Loughran and McDonald, 2011;Sharpe et al., 2017;Banerjee et al., 2019;Shapiro et al., 2020), or semantic orientation (Lucca and Trebbi, 2009). We contribute to this literature by developing a Federal Reserve-specific dictionary to sign FOMC statements and demonstrating that it works better than using the general dictionary of financial market positive and negative words of Loughran and Mc-Donald (2011), consistent with the findings of Picault and Renault (2019). ...
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While the literature has already widely documented the effects of macroeconomic news announcements on asset prices, as well as their asymmetric impact during good and bad times, we focus on the reaction to news based on the description of the state of the economy as painted by the Federal Open Market Committee (FOMC) statements. We develop a novel FOMC sentiment index using textual analysis techniques, and find that news has a bigger (smaller) effect on equity prices during bad (good) times as described by the FOMC sentiment index. Our analysis suggests that the FOMC sentiment index offers a reading on current and future macroeconomic conditions that will affect the probability of a change in interest rates, and the reaction of equity prices to news depends on the FOMC sentiment index which is one of the best predictors of this probability.
... Consequently, a substantial body of literature has emerged that developed methods for quantifying different aspects of such communication. The literature is still primarily driven by dictionary approaches, in which pre-defined dictionaries, such as Loughran and McDonald (2011), Apel and Grimaldi (2014), and Picault and Renault (2017), are used to count terms (for example, positive and negative) to extract a single dimension (for example, sentiment) from a text corpus. However, these methods fall short of incorporating the language's richness, its multidimensionality, and its context-dependence. ...
... In fact, dictionaries have been explicitly designed for the use in financial and central bank context (e.g. Loughran and Mc-Donald, 2011;Apel and Grimaldi, 2014;Picault and Renault, 2017;Correa et al., 2021). The peculiarity of the terminology spoken in the central bank context necessitates the usage of such central bank-specific dictionaries. ...
Preprint
Full-text available
Dictionary approaches are at the forefront of current techniques for quantifying central bank communication. This paper proposes embeddings-a language model trained using machine learning techniques-to locate words and documents in a multidimensional vector space. To accomplish this, we gather a text corpus that is unparalleled in size and diversity in the central bank communication literature, as well as introduce a novel approach to text quantification from computational linguistics. Utilizing this novel text corpus of over 23,000 documents from over 130 central banks we are able to provide high quality text-representations-embeddings-for central banks. Finally, we demonstrate the applicability of embeddings in this paper by several examples in the fields of monetary policy surprises, financial uncertainty, and gender bias. JEL: C45, C53, E52, Z13
... Using speeches and interviews she finds that by the usage of the Securities Market Program and 'doing whatever it takes' ECB presidents Jean-Claude Trichet and Mario Draghi exercised transformative leadership during the crisis. Picault and Renault (2017) use ngram and term-weighing approach to quantify ECB communication and analyze its impact on market return and volatility. Claeys et al. (2018) analyze the monetary policy framework of the ECB in light of declining long-term rates in advanced countries and the flattening of the Phillips curve. ...
Article
We quantify the tone from the speeches of the ECB as well as that from the national central banks of six leading European nations, and analyze its role in explaining the returns of their respective stock market indices. Using innovations in financial text analysis introduced in ?, we find evidence that except for France, all nations’ stock indices are significantly associated with the tone of speeches delivered by either the national or the European Central Bank (or both). For France, the national stock index volatility is found to be associated with its national central bank speech tone. This article is protected by copyright. All rights reserved.