Bringing the "self" into focus: conceptualising the role of self-experience for understanding and working with distressing voices

A primary goal of cognitive behavior therapy for psychosis (CBTp) is to reduce distress and disability, not to change the positive symptoms of psychosis, such as hearing voices. Despite demonstrated associations between beliefs about voices and distress, the effects of CBTp on reducing voice distress are disappointing. Research has begun to explore the role that the psychological construct of “self” (which includes numerous facets such as self-reflection, self-schema and self-concept) might play in causing and maintaining distress and disability in voice hearers. However, attempts to clarify and integrate these different perspectives within the voice hearing literature, or to explore their clinical implications, are still in their infancy. This paper outlines how the self has been conceptualised in the psychosis and CBT literatures, followed by a review of the evidence regarding the proposed role of this construct in the etiology of and adaptation to voice hearing experiences. We go on to discuss some of the specific intervention methods that aim to target these aspects of self-experience and end by identifying key research questions in this area. Notably, we suggest that interventions specifically targeting aspects of self-experience, including self-affection, self-reflection, self-schema and self-concept, may be sufficient to reduce distress and disruption in the context of hearing voices, a suggestion that now requires further empirical investigation

Jockeying for position in CEO letters: Impression management and sentiment analytics

This paper evidences the strategic positioning of positive and negative words within a CEO letter as a subtle form of impression management. We find that managers tend to present information in such an order that the reader of the CEO letter has a more positive perception of the underlying message. We uncover a smile in the frequency of positive words within the letter, and a half smile in the intratextual distribution of negative words, with a prevalence of negative words at the beginning of the letter. We also find a significant positive association between this qualitative impression management and the use of abnormal accruals in earnings management. We propose sentiment analytics that can compensate for the strategic management of narrative structure and find that the proposed position weighted sentiment has more predictive power for the firm performance over the next year

Unpacking the black box of ICO white papers: A topic modeling approach

We apply a novel topic modeling method to map Initial Coin Offerings' (ICOs') white paper thematic content to analyze its information value to investors. Using a sentence-based topic modeling algorithm, we determine and empirically quantify 30 topics in an extensive collection of 5,210 ICO white papers between 2015 and 2021. We find that the algorithm produces a semantically meaningful set of topics, which significantly improves the model performance in identifying successful projects. The most value-relevant topics concern the technical features of the ICO. However, we find that white paper's informativeness substantially diminishes after the token is listed. Moreover, we show that credibility-enhancing mechanisms (i.e., regulations and ICO analysts) reinforce the information value of ICO white papers. Overall, our results suggest that the topics discussed in white papers and the attention devoted to each topic are useful ICO performance indicators

Disclosure tone management and labor unions

By analyzing the influence of labor unions on the narrative content of corporate disclosures, we provide empirical evidence that managers deflate the tone of earnings press releases in order to convey to unions a less optimistic image of firm financial performance. We find that the tone of the qualitative information in earnings press releases is significantly less optimistic as the degree of unionization increases, and particularly when financial performance is strong. The results of quasi-natural experiments suggest that labor unions causally affect the use of tone deflation, and the deflation is stronger during labor negotiations. Our findings also indicate that labor unions lead to a significant weakening of the signaling value of the tone of earnings press releases in predicting future performance

Managers set the tone: Equity incentives and the tone of earnings press releases

Earnings press releases, as a timely vehicle for communicating a firm’s performance to third parties, can be used by managers to influence the perception of the firm’s achievements. Taking the stock price reaction to the tone of earnings press releases at earnings announcements into account, we argue that equity-based incentives induce managers to inflate the tone. We further posit that the impact of tone on the abnormal stock returns at the earnings announcements depends on the magnitude of the equity-based incentives. Based on over 26,000 earnings press releases of S&P1500 firms between 2004Q4 and 2012Q4, we find that the tone of earnings press releases tends to be more positive when the managerial portfolio value is more closely tied to the firm’s stock price. We also find that investors react proportionally less to the tone as managers’ equity incentives increase

When does the tone of earnings press releases matter?

The tone of a firm's financial disclosure is increasingly used as a variable in panel data regressions to predict future performance and explain investors' reaction at earnings announcement. We investigate when tone is informative, and argue that the informativeness of tone increases with the information asymmetry between firms and investors. Using a sample of over 50,000 earnings press releases of about 1800 U.S. public firms between 2004 and 2015, we find that firm growth, size, age, complexity and forecast inaccuracy are key drivers of tone informativeness. The effect is economically significant, since, compared to the reference case of a transparent firm, we find that the slope coefficient of tone doubles or even quadruples in panel data regressions when the firm operates in an environment with high information asymmetry

Contributions to the analysis of corporate information: Robustness, sustainability and textual analysis.

Investors are in the business of acquiring information and using that information to manage a portfolio of assets. Information asymmetry, however, plays a central role in investors' information acquisition and occurs when one group of participants has better or more timely information than other groups. Typically, the source of the information asymmetry is the superior knowledge that managers have about the firm's prospects, while the investors in the firm comprise the uninformed group. With examples such as the accounting scandals of Enron, Lernout & Hauspie, Worldcom, it is obvious today that information on capital markets is asymmetrically distributed and that information differential between the management and investors can lead to a suboptimal allocation of resources within the firm. Clearly, managers, investors and regulators concerned with financial supervision are in need of methods to manage information asymmetry problems.This Ph.D. dissertation contributes to the development of new methods to mitigate information asymmetry on capital markets and focuses on three specific sources of information, each of them corresponding to one part of the dissertation. In Part I, I define a prediction model that helps investors reduce information asymmetry by predicting financial analysts' forecast error. In Part II, I focus on the value of corporate social responsibility (CSR) information, provided by the Kinder, Lyndenberg and Domini Research and Analytics database (KLD). In Part III, the objective is to decrease information asymmetry by defining more accurate measures of tone (or sentiment) in the narrative sections of a firm's voluntary disclosures, such as earnings press releases and CEO letters to shareholders. Overall, we show that investors, managers and regulators can manage and reduce information asymmetries on capital markets by either using advanced econometric methods, new databases on a firm s stakeholder activities or the textual content of a firm's financial disclosures.nrpages: 227status: publishe

Spell It Right! The impact of linguistic accuracy on corporate investment decisions: The case Initial Coin Offering whitepapers

Drawing on language expectancy theory, we predict that linguistic errors in ICO white papers negatively impact investors’ willingness to financially contribute to ICO projects. We manually annotate a sample of 546 ICO white papers according to 13 different error subcategories related to spelling and grammar. The error-annotated data are subsequently submitted to regression analyses which confirm that linguistic errors discourage potential investments in ICOs. Specifically, our analyses reveal the presence of “high penalty” vs. “low penalty” errors which result in higher vs. lower financial investment losses for the ICOs. We further find that the negative impact of language errors is stronger for (1) ICOs that are written in native English-speaking countries and (2) ICOs from countries without cryptocurrency regulation. Results from an experiment confirm that this relationship is not driven by the entrepreneur- or investor-specific characteristics. Overall, we highlight that the reader identifies linguistic errors as a major ‘red flag’ that ultimately affects financial decision-making

Linguistic errors and investment decisions: the case of ICO white papers

peer reviewedDrawing on language expectancy theory, we predict that linguistic errors in ICO white papers negatively impact investors’ willingness to financially contribute to ICO projects. We manually annotate a sample of 546 ICO white papers according to 13 different error subcategories related to spelling and grammar. The error-annotated data are subsequently submitted to regression analyses which confirm that linguistic errors discourage potential investments in ICOs. Specifically, our analyses reveal the presence of ‘high penalty’ vs. ‘low penalty’ errors which result in higher vs. lower financial investment losses for the ICOs. The negative impact of language errors is stronger when ICO white papers are (1) written in native English-speaking countries and (2) from countries without cryptocurrency regulation. Results from an experiment confirm that this relationship is not driven by the entrepreneur- or investor-specific characteristics. Overall, we highlight that the reader identifies linguistic errors as a major ‘red flag’ that ultimately affects financial decision-makin

Spell it right! The impact of linguistic accuracy on business investment decisions

Drawing on language expectancy theory, we predict that linguistic errors in ICO white papers negatively impact investors’ willingness to financially contribute to ICO projects. We manually annotate a sample of 546 ICO white papers according to 13 different error subcategories related to spelling and grammar. The error-annotated data are subsequently submitted to regression analyses which confirm that linguistic errors discourage potential investments in ICOs. Specifically, our analyses reveal the presence of “high penalty” vs. “low penalty” errors which result in higher vs. lower financial investment losses for the ICOs. We further find that the negative impact of language errors is stronger for (1) ICOs that are written in native English-speaking countries and (2) ICOs from countries without cryptocurrency regulation. Results from an experiment confirm that this relationship is not driven by the entrepreneur- or investor-specific characteristics. Overall, we highlight that the reader identifies linguistic errors as a major ‘red flag’ that ultimately affects financial decision-making