Caught in an Expectations Trap: Risks of Giving Securities Analysts What They Expect

2023 | Organization Science | Citations: 0

Authors: Bascle, Guilhem; Jung, Jiwook

Abstract: Although recent research shows that there is mounting pressure on firms to achie ... Expand

Abstract: Although recent research shows that there is mounting pressure on firms to achieve earnings expectations of securities analysts, firms are far from being passive conformers; many firms proactively manage such pressure, particularly with earnings management tools. Yet why does the pressure to meet analyst expectations persist despite firms’ efforts to reduce it? To address the question, we develop an intertemporal model of the mutually reinforcing relationships between analyst expectations and firms’ strategic response, combining the behavioral theory of the firm and the concept of expectations trap. We argue that firms’ efforts to meet analyst expectations strengthen their salience as a predominant performance benchmark and, in doing so, ironically put them under greater pressure from analysts in three sequentially related steps—escalating future earnings expectations, imposing more severe penalties for failure to meet heightened expectations, and generating compensatory action for missed expectations. Our analysis, using data on more than 700 of the largest listed U.S. firms between 1986 and 2015, supports our arguments. Our study expands the scope of the behavioral theory of the firm, by demonstrating the increasing importance of performance feedback based on analyst expectations. Our study also contributes to the research on earnings pressure, by illuminating why the pressure persists despite firms’ efforts to reduce or evade it, and finally to the literature on strategic management of external expectations, by elaborating its unintended, long-term consequences. Supplemental Material: The e-companion is available at https://doi.org/10.1287/orsc.2021.1569. Collapse

Topics: strategic management organizational productivity Generally Accepted Accounting Principles IS downsizing accounting

Methods: longitudinal research statistical hypothesis test Compustat descriptive statistic robustness check

Theories: behavioral theory of the firm institutional theory

Mixed-methods research in the age of analytics, an exemplar leveraging sentiments from news articles to predict firm performance

2022 | International Journal of Information Management | Citations: 0

Authors: Raman, Raji; Aljafari, Ruba; Venkatesh, Viswanath; Richardson, Vernon

Abstract: Investors and companies have always aspired to make informed investment decision ... Expand

Abstract: Investors and companies have always aspired to make informed investment decisions by using diverse infor­ mation sources. With the explosion of information sources on the web and emergence of predictive analytics, many investors moved beyond traditional financial measures, as key predictors of firm performance, to textual content from analysts’ reports. Empirical research suggests that these information sources complement each other by providing a clear picture of firm performance, but remains silent on the role of additional textual content that continues to emerge and reach more potential investors on the web. We build on this line of research to examine the effect of textual content from business journals in conjunction with summary measures on cu­ mulative abnormal returns. We use sentiment analysis with machine learning and econometrics methods to examine content extracted from textual articles about S&P 500 index companies that are published in the Wall Street Journal (years 2013–2016). Textual analysis of business journals in conjunction with quantitative mea­ sures revealed direct and interaction effects on abnormal returns over time. We also tested for robustness by replicating the analysis with different variable operationalization and observe consistent patterns. Relative to positive sentiments, negative sentiments have more profound effects on cumulative abnormal returns. The effect of positive sentiments becomes weaker when past quantitative measures are high. As information sources continue to emerge on the web, this work makes key contributions to the practice of sentiment analysis in financial markets. Collapse

Topics: organizational productivity accounting Python financial performance word of mouth

Methods: machine learning computational algorithm econometric modeling sentiment analysis classification method

Theories: information theory

X-IM Framework to Overcome Semantic Heterogeneity Across XBRL Filings

2020 | Journal of the Association for Information Systems | Citations: 0

Authors: Liu, Dapeng; Etudo, Ugochukwu; Yoon, Victoria

Abstract: Semantic heterogeneity in XBRL precludes the full automation of the business rep ... Expand

Abstract: Semantic heterogeneity in XBRL precludes the full automation of the business reporting pipeline, a key motivation for the SEC’s XBRL mandate. To mitigate this problem, several approaches leveraging Semantic Web technologies have emerged. While some approaches are promising, their mapping accuracy in resolving semantic heterogeneity must be improved to realize the promised benefits of XBRL. Considering this limitation and following the design science research methodology (DSRM), we develop a novel framework, XBRL indexing-based mapping (X-IM), which takes advantage of the representational model of representation theory to map heterogeneous XBRL elements across diverse XBRL filings. The application of representation theory to the design process informs the use of XBRL label linkbases as a repository of regularities constitutive of the relationships between financial item names and the concepts they describe along a set of equivalent financial terms of interest to investors. The instantiated design artifact is thoroughly evaluated using standard information retrieval metrics. Our experiments show that X-IM significantly outperforms existing methods. Collapse

Topics: electronic data interchange knowledge representation accounting Python web page

Methods: ontological modelling machine learning experiment design artifact financial report

Theories: representation theory theory of ontological clarity sociotechnical systems theory

On computing probabilities of dismissal of 10b-5 securities class-action cases

2017 | Decision Support Systems | Citations: 0

Authors: Singha, Sumanta; Hillmer, Steve; Shenoy, Prakash P.

Abstract: The main goal of this paper is to propose a probability model for computing prob ... Expand

Abstract: The main goal of this paper is to propose a probability model for computing probabilities of dismissal of 10b-5 securities class-action cases filed in United States Federal district courts. By dismissal, we mean dismissal with prejudice in response to the motion to dismiss filed by the defendants, and not eventual dismissal after the discovery process. The proposed probability model is a hybrid of two widely-used methods: logistic regression, and naïve Bayes. Using a dataset of 925 10b-5 securities class-action cases filed between 2002 and 2010, we show that the proposed hybrid model has the potential of computing better probabilities than either LR or NB models. By better, we mean lower root mean square errors of probabilities of dismissal. The proposed hybrid model uses the following features: allegations of generally accepted accounting principles violations, allegations of lack of internal control, bankruptcy filing during the class period, allegations of Section 11 violations of Securities Act of 1933, and short-term drop in stock price. Our model is useful for those insurance companies which underwrite Directors and Officers liability policy. Collapse

Topics: missing data database system Generally Accepted Accounting Principles decision support system logistics management

Methods: logistic regression computational algorithm naïve bayes descriptive statistic regression analysis method

Impact of XBRL on Financial Statement Structural Comparability

2016 | International Conference on Information Systems | Citations: 0

Authors: Yang, Steve Y.; Liu, Fang-Chun

Abstract: The quality of corporate financial reporting has long been the interests of fina ... Expand

Abstract: The quality of corporate financial reporting has long been the interests of financial reporting users, such as investors, financial analysts, and regulators. Comparability is a key qualitative characteristic of accounting information that facilitates the comparison of financial statements. However, various reporting formats and accounting taxonomy standards result in inconsistent reporting structures that indirectly affect comparability. To improve information comparability, the U.S. Securities and Exchange Commission (SEC) mandates the adoption of the eXtensible Business Reporting Language (XBRL), a search-facilitating technology, to reduce the costs of information search and improve the efficiency of information processing. Leveraging on the XBRL adoption enforced by the SEC, this study investigates whether the comparability of financial statement structure has improved in the post-mandate XBRL period. The results show a significant, consistent comparability improvement in the post XBRL adoption period, providing empirical evidence of the positive impact of XBRL on enhancing financial statement structural comparability. Collapse

Topics: electronic data interchange accounting Generally Accepted Accounting Principles decision making open source

Methods: Mann Whitney U test nonparametric test financial report local outlier factor computational algorithm

Under Construction: How Commensuration and Management Fashion Affect Corporate Reputation Rankings

2014 | Organization Science | Citations: 8

Authors: Bermiss, Y. Sekou; Zajac, Edward J.; King, Brayden G

Abstract: This paper analyzes the antecedents of corporate reputation as a dynamic commens ... Expand

Abstract: This paper analyzes the antecedents of corporate reputation as a dynamic commensuration process in which management fashions influence audiences as they attempt to quantify corporate reputation. Using the context of Fortune reputation rankings over multiple decades, we find evidence consistent with our hypotheses that when asked to quantify corporate reputation, audiences rely heavily on traditional as well as emerging nontraditional measures of financial performance as they become more fashionable indicators of superior financial performance. However, audiences have recently begun to assess companies’ reputations based on indicators of social performance. We also examine how audience attention to these indicators is itself influenced by business press discourse. Collapse

Topics: financial performance business topic accounting database system organizational productivity

Methods: autoregressive moving average model autocorrelation analysis survey longitudinal research regression analysis method

Assessing the quality of large-scale data standards: A case of XBRL GAAP Taxonomy

2014 | Decision Support Systems | Citations: 0

Authors: Zhu, Hongwei; Wu, Harris

Abstract: Data standards are often used by multiple organizations to produce and exchange ... Expand

Abstract: Data standards are often used by multiple organizations to produce and exchange data. Given the high cost of developing data standards and their significant impact on the interoperability of data produced using the standards, the quality of data standards must be systematically measured. We develop a framework for systematically assessing the quality of large-scale data standards using automated tools. It consists of metrics for intrinsic and contextual quality dimensions, as well as effectual metrics that assess the extent to which a standard enables data interoperability. We evaluate the quality assessment framework using two versions of a large financial reporting standard, the US GAAP Taxonomy, and public companies' financial statements created using the Taxonomy. Evaluation results confirm the effectiveness of the framework. Findings from the evaluation also offer valuable insights to decision makers who develop and improve data standards, select and adopt data standards, or consume standards-based data. Collapse

Topics: Generally Accepted Accounting Principles electronic data interchange knowledge representation accounting user requirement

Methods: ontological modelling design principle design science usability testing financial report

The Accounting Standards Setting Process in the U.S.: Examination of the SEC–FASB Relationship

2011 | Group Decision and Negotiation | Citations: 0

Authors: Palmon, Dan; Peytcheva, Marietta; Yezegel, Ari

Abstract: In the U.S. there is a close relationship between the Securities and Exchange Co ... Expand

Abstract: In the U.S. there is a close relationship between the Securities and Exchange Commission (SEC), a governmental agency legally responsible for setting accounting standards, and the Financial Accounting Standards Board (FASB), a private sector body to whom the SEC has delegated this responsibility. In this paper we examine the influence of the SEC on the FASB as evidenced by all major statements issued by the FASB. Minor statements, amendments, and strictly technical pronouncements were omitted because of their limited exposure to the political process. Our analysis reveals that the SEC applied substantial pressure on the FASB in the standard setting process and has not adopted a position of benign neglect. Collapse

Topics: accounting accounting standard Generally Accepted Accounting Principles database system decision making

An Ontological Approach to XBRL Financial Statement Reporting

2011 | Americas Conference on Information Systems | Citations: 0

Authors: Wenger, Mitchell; Thomas, Manoj A; Jr, Jeffrey S Babb

Abstract: As a standard for the exchange, transmission, and reporting of accounting and fi ... Expand

Abstract: As a standard for the exchange, transmission, and reporting of accounting and financial data, XRBL goes a long way toward standardization. However, as the extent of contemporary financial markets is now global, XBRL reporting must transcend or accommodate differences in reporting standards. While XBRL has been of great help in standardizing the presentation of the U.S. GAAP and IASB standards, reconciling meaning between these standards is still a manual and error-prone affair. As a wide variety of stakeholders, spanning countries and cultures, will likely take part in digesting XBRL-formatted financial reports; how will they participate at an appropriate level that is meaningful for them? This paper focuses on an ontological approach towards solving this problem by offering an XBRL ontology architecture for translation between XBRL formats. The architecture is explained, evaluation criteria offered, and future research towards realizing artifacts which use this architecture are proffered. Collapse

Topics: electronic data interchange knowledge representation accounting Generally Accepted Accounting Principles extensible markup language

Methods: ontological modelling

Quality of data standards: framework and illustration using XBRL taxonomy and instances

2011 | Electronic Markets | Citations: 9

Authors: Zhu, Hongwei; Wu, Harris

Abstract: The primary purpose of data standards is to improve the interoperability of data ... Expand

Abstract: The primary purpose of data standards is to improve the interoperability of data in an increasingly networked environment. Given the high cost of developing data standards, it is desirable to assess their quality. We develop a set of metrics and a framework for assessing data standard quality. The metrics include completeness, relevancy, and a combined measure. Standard quality can also be indirectly measured by assessing interoperability of data instances. We evaluate the framework on a data standard for financial reporting in United States, the Generally Accepted Accounting Principles (GAAP) Taxonomy encoded in eXtensible Business Reporting Language (XBRL), and the financial statements created using the standard by public companies. The results show that the data standard quality framework is useful and effective. Our analysis also reveals quality issues of the US GAAP XBRL taxonomy and provides useful feedback to taxonomy users. The Securities and Exchange Commission has mandated that all publicly listed companies must submit their filings using XBRL. Our findings are timely and have practical implications that will ultimately help improve the quality of financial data and the efficiency of the data supply chain in a networked business environment. Collapse

Topics: Generally Accepted Accounting Principles electronic data interchange frequency of use accounting data quality

Methods: machine learning association rule learning qualitative interview computational algorithm