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<link>https://fif.hebis.de/xmlui/handle/123456789/984</link>
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<pubDate>Sun, 05 Apr 2026 23:11:55 GMT</pubDate>
<dc:date>2026-04-05T23:11:55Z</dc:date>
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<title>Market impact of government communication: The case of presidential tweets</title>
<link>https://fif.hebis.de/xmlui/handle/123456789/2435</link>
<description>Market impact of government communication: The case of presidential tweets
"We propose the ""President reacts to news"" channel of stock returns by studying the financial market impact of the Twitter account of the 45th president of the United States, Donald Trump. We use machine learning algorithms to classify topic and textual sentiment of 1,400 economy-related tweets to investigate whether they contain relevant information for financial markets. Analyzing high-frequency data, we find that after controlling for past market movements, most tweets are reactive and predictable, rather than novel and informative. The exceptions are tweet topics where the president has direct policy authority and his negative sentiment could adversely affect economic outcomes."
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<pubDate>Wed, 06 Oct 2021 00:00:00 GMT</pubDate>
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<dc:date>2021-10-06T00:00:00Z</dc:date>
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<title>The salience of ESG ratings for stock pricing: Evidence from (potentially) confused investors</title>
<link>https://fif.hebis.de/xmlui/handle/123456789/2434</link>
<description>The salience of ESG ratings for stock pricing: Evidence from (potentially) confused investors
We exploit a modification to Sustainalytics' environmental, social, and governance (ESG) rating methodology, which is subsequently adopted by Morningstar, to study whether ESG ratings are salient for stock pricing. We show that the inversion of the rating scale but not new information leads some investors to make incorrect assessments about the meaning of the change in ESG ratings. They buy (sell) stocks they misconceive as ESG upgraded (downgraded) even when the opposite is true. This trading behavior exerts transitory price pressure on affected stocks. Our paper highlights the importance of ESG ratings for investors and consequently for asset prices.
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<pubDate>Fri, 08 Oct 2021 00:00:00 GMT</pubDate>
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<dc:date>2021-10-08T00:00:00Z</dc:date>
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<title>OTC Discount</title>
<link>https://fif.hebis.de/xmlui/handle/123456789/2433</link>
<description>OTC Discount
We document a sizable OTC discount in the interdealer market for German sovereign bonds where exchange and over-the-counter trading coexist: the vast majority of OTC prices are favorable compared to exchange quotes. This is a challenge for theories of OTC markets centered around search-and-bargaining frictions but consistent with models of hybrid markets based on information frictions. We find support for this explanation. Distinguishing between bilateral and broker-intermediated OTC trades, differences in OTC discount across protocols are consistent with their relative informedness. Within each protocol, the difference in OTC discount is explained not only by information but also by search-and-bargaining frictions.
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<pubDate>Fri, 08 Oct 2021 00:00:00 GMT</pubDate>
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<dc:date>2021-10-08T00:00:00Z</dc:date>
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<title>The Value of Firm Networks: A Natural Experiment on Board Connections</title>
<link>https://fif.hebis.de/xmlui/handle/123456789/2432</link>
<description>The Value of Firm Networks: A Natural Experiment on Board Connections
We present causal evidence on the effect of boardroom networks on firm value and compensation policies. We exploit a ban on interlocking directorates of Italian financial and insurance companies as exogenous variation and show that firms that lose centrality in the network experience negative abnormal returns around the announcement date. The key driver of our results is the role of boardroom connections in reducing asymmetric information. The complementarities with the input-output and cross-ownership networks are consistent with this channel. Using hand-collected data, we also show that network centrality has a positive effect on directors' compensation, providing evidence of rent sharing.
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<pubDate>Tue, 03 Aug 2021 00:00:00 GMT</pubDate>
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<dc:date>2021-08-03T00:00:00Z</dc:date>
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