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We analyze the market reaction to the sentiment of the CEO speech at the Annual General Meeting (AGM). As the AGM is typically preceded by several information disclosures, the CEO speech may be expected to contribute only marginally to investors’ decision-making. Surprisingly, however, we observe from the transcripts of 338 CEO speeches of German corporates between 2008 and 2016 that their sentiment is significantly related to abnormal stock returns and trading volumes following the AGM. Using a novel business-specific German dictionary based on Loughran and McDonald (2011), we find a negative association of the post-AGM returns with the speeches’ negativity and a positive association with the speeches’ relative positivity (i.e. positivity relative to negativity). Relative positivity moreover corresponds with a lower trading volume in a short time window surrounding the AGM. Investors hence seem to perceive the sentiment of CEO speeches at AGMs as a valuable indicator of future firm performance.
We extend the classical ”martingale-plus-noise” model for high-frequency prices by an error correction mechanism originating from prevailing mispricing. The speed of price reversal is a natural measure for informational efficiency. The strength of the price reversal relative to the signal-to-noise ratio determines the signs of the return serial correlation and the bias in standard realized variance estimates. We derive the model’s properties and locally estimate it based on mid-quote returns of the NASDAQ 100 constituents. There is evidence of mildly persistent local regimes of positive and negative serial correlation, arising from lagged feedback effects and sluggish price adjustments. The model performance is decidedly superior to existing stylized microstructure models. Finally, we document intraday periodicities in the speed of price reversion and noise-to-signal ratios.
What processes transform (im)mobile individuals into ‘migrants’ and geographic movements across political-territorial borders into ‘migration’? To address this question, the article develops the doing migration approach, which combines perspectives from social constructivism, praxeology and the sociologies of knowledge and culture. ‘Doing migration’ starts with the processes of social attribution that differentiate between ‘migrants’ and ‘non-migrants’. Embedded in institutional, organizational and interactional routines these attributions generate unique social orders of migration. By illustrating these conceptual ideas, the article provides insights into the elements of the contemporary European order of ‘migration’. Its institutional routines contribute to the emergence of a European migration regime that involves narratives of economization, securitization and humanitarization. The organizational routines of the European migration order involve surveillance and diversity management, which have disciplining effects on those defined as ‘migrants’. The routines of everyday face-to-face interactions produce various micro-forms of doing ‘migration’ through stigmatization and othering, but they also provide opportunities to resist a social attribution as ‘migrant’.
In this paper we propose a way forward towards increased financial resilience in times of growing disagreement concerning open borders, free trade and global regulatory standards. In light of these concerns, financial resilience remains a highly valued policy objective. We wish to contribute by suggesting an agenda of concrete, do-able steps supporting an enhanced level of resilience, combined with a deeper understanding of its relevance in the public domain.
First, remove inconsistencies across regulatory rules and territorial regimes, and ensure their credibility concerning implementation. Second, discourage the use of financial regulatory standards as means of international competition. Third, give more weight to pedagogically explaining the established regulatory standards in public, to strengthen their societal backing.
Optimal trend inflation
(2017)
We present a sticky-price model incorporating heterogeneous Firms and systematic firm-level productivity trends. Aggregating the model in closed form, we show that it delivers radically different predictions for the optimal inflation rate than canonical sticky price models featuring homogenous Firms:
(1) the optimal steady-state inflation rate generically differs from zero and,
(2) inflation optimally responds to productivity disturbances.
Using micro data from the US Census Bureau to estimate the inflation-relevant productivity trends at the firm level, we find that the optimal US inflation rate is positive. It was slightly above 2 percent in the year 1986, but continuously declined thereafter, reaching about 1 percent in the year 2013.