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Background: Individuals' stress in responding to the current COVID-19 pandemic may be exacerbated by information uncertainty driven by inconsistent, unverified, and conflicting news from various sources. The current study aims to test if information uncertainty during the COVID-19 outbreak was related to acute stress disorder (ASD) over and above other psychosocial stressors., Methods: An anonymous online survey was conducted with 7800 college students throughout China from January 31 through February 11, 2020. Existing scales were modified to measure ASD and six potential stressors including information uncertainty during the COVID-19 outbreak. Hierarchical regression analysis was conducted to assess the unique association of information uncertainty with ASD. To minimize the effect of large sample size and also to get a sense of whether the effects of information uncertainty were similar to people at the center of the epidemic, we repeated the hierarchical regression among 10% of the students who were randomly selected from the entire sample ("10% random sample"; n = 780) and 226 students from Hubei Province where the outbreak started., Results: Information uncertainty was highly prevalent among the respondents (64%). It was significantly associated with ASD beyond other key variables and potential stressors across three samples. In the hierarchical regression among the entire sample, demographic variables accounted for 9.4% of the variance in ASD. The other five stressors added 5.1% of the variance. The information uncertainty (β = .159; p < .001) explained an additional 2.1% of the variance. Likewise, the information uncertainty explained an additional 2.1 and 3.4% of the variance in ASD beyond all other variables among the 10% random sample (β = .165; p < .001) and the Hubei sample (β = .196; p < .01), respectively., Conclusion: Information uncertainty is a unique correlate of psychological stress during the COVID-19 outbreak. Reducing information uncertainty is essential not only for halting virus transmission but also for mitigating negative impacts of the pandemic on people's psychosocial wellbeing. Transparent, timely, and accurate communication can reduce public confusion, fear, and stress. Capacity building in governments, communities, and media outlets to prevent, reduce and manage information uncertainty should be a critical part of the response to an emerging global health crisis such as the COVID-19 pandemic.

We examine and compare the extent to which the reaction of investors to earnings announcements is influenced by a firm's governance profile and prevailing market conditions. We find that firms with better governance characteristics experience a larger initial reaction to both good and bad earnings announcements regardless of the prevailing sentiment and uncertainty conditions. However, the influence of governance is constrained to the announcement period. We demonstrate that changes in market uncertainty and/or investor sentiment are related to the post-earnings announcement drift. We also find that a major channel through which greater corporate governance influences the market response to unexpected earnings news is by lowering information uncertainty and so providing greater clarity of the implication of the news for firm value. Finally, we establish that two types of uncertainties (market and information) have very different influence on investor's response to information signals. JEL Classification: D81, G10, G14, G30, G32 [ABSTRACT FROM AUTHOR]

The possibility and expediency of estimation of risk factors based on fundamental positions of information and entropy are grounded. In accordance with the principle of addiction, the possibility of using the H-criterion as an indicator of business uncertainty is shown. The algorithm of risk estimation of these investments is offered. [ABSTRACT FROM AUTHOR]

This paper examines two potential key drivers of the financial strength (F-Score) investment strategy: information uncertainty and liquidity. We use novel, direct measures of information uncertainty related to the variability of financial strength signals themselves. However, financial strength strategy returns are not generally strongly related to these information uncertainty proxies. We also examine two proxies for liquidity. Financial strength strategy returns are generally substantially larger for illiquid firms. A zero-cost arbitrage strategy based on F-Score generates a 20% return in illiquid UK stocks and 12% in liquid UK stocks. The enhanced F-Score effect is driven by a flight from illiquidity amongst financially weak stocks. Overall, the profitability of the F-Score investment strategy appears more closely related to liquidity than to information uncertainty. [ABSTRACT FROM AUTHOR]

This study examines the determinants of goodwill overstatement at the time of mergers in a Korean setting. In the Korean M&A market, there are two types of mergers: mergers between independent companies (non‐affiliated mergers) and mergers between companies under common control (affiliated mergers). This study extends the literature by examining the factors likely to cause goodwill overstatement in both types of mergers. The results reveal that in affiliated mergers, goodwill at the time of a merger tends to be overstated when controlling owners have higher equity ownership in the target than in the acquirer. By contrast, information uncertainty in the target value causes initial goodwill overstatement in non‐affiliated mergers. We also find that monitoring of independent institutional investors with concentrated holdings against overpaying for the target is more pronounced when controlling owners in affiliated mergers have incentives to overpay for the target. In affiliated mergers, acquirers tend to write off goodwill more frequently when controlling owners have higher equity ownership in the target than in the acquirer. In non‐affiliated mergers, information uncertainty in the target value is significantly associated with subsequent goodwill write‐offs. These results suggest that the type of merger has important consequences for initial goodwill recognition and subsequent impairment. [ABSTRACT FROM AUTHOR]

We investigate how firms use information technology (IT) implementation to mitigate an anomaly in capital markets: investors underreacting to new public information. The theory of information uncertainty (IU) suggests that the anomaly is amplified with IU; that is, with ambiguity in information about firm value. We theorize that a firm's IT in general—and enterprise systems (ES) in particular—can mitigate IU, thus reducing the IU-induced underreaction anomaly. Based on a difference-in-differences analysis of a sample of 572 ES implementations, our main finding is that ES implementation does reduce IU-induced underreaction anomaly. This is achieved through a reduction in the firm's fundamentals volatility and an improvement in information quality. We also find that firms with greater IT capability are better positioned to realize the anomaly-reducing benefits of ES implementation and that ES's anomaly-reducing effect is most pronounced when high levels of both functional and operational ES modules are implemented. We obtain remarkably consistent results when using alternate empirical design, samples, and measures of news. Such IT impacts are economically highly consequential because they improve capital market efficiency. This paper was accepted by Anandhi Bharadwaj, information systems. [ABSTRACT FROM AUTHOR]

The authors examine whether a cognitive bias influences dividend policy. They find that managers use a heaping heuristic when choosing the amount of their firm's dividend. Heaping is a human error or bias to round numbers even though precise values are desired. This bias leads to dividend distributions clustered at specific amounts. Dividend size and the level of information uncertainty faced by management help explain the likelihood of heaping. The authors also observe that heaped dividends are "sticky" and altered less frequently, and when there is a dividend change, heaped dividends are more often switched to another heaped amount. [ABSTRACT FROM AUTHOR]

This paper considers a problem of source data uncertainty concerning the technical state of gas supply systems. Decision-making in the region of managing and development planning of the gas supply systems (production, transport, distribution, storage), as a rule, occurs by lacking of information, and the validity of some data is questionable. We propose to formalize the information uncertainty in terms of membership functions of the fuzzy sets. Mathematical models and algorithms for solving the various modelling and optimization problems of the natural gas transport are worked out. The results of calculations demonstrate the potential of the technique. • Fuzzy models for the technical state parameters of pipelines and compressors. • An algorithm for calculating the maximum flow capacity of a gas-transport system with fuzzily-assigned parameters. • An optimization algorithm of the operation modes of a gas transport system with fuzzily-assigned parameters. • Application of the proposed models and algorithms to the illustrative and real-world gas transport systems. [ABSTRACT FROM AUTHOR]

Prior literature observes that information uncertainty exacerbates investor underreaction behavior. In this paper, I investigate whether, as professional investment intermediaries, sellside analysts suffer more behavioral biases in cases of greater information uncertainty. I show that greater information uncertainty predicts more positive (negative) forecast errors and subsequent forecast revisions following good (bad) news, which corroborates previous findings on the post-analyst-revision drift. The opposite effects of information uncertainty on forecast errors and subsequent forecast revisions following good versus bad news support the analyst underreaction hypothesis and are inconsistent with analyst forecast rationality or optimism suggested in prior literature. [ABSTRACT FROM AUTHOR]

In this paper, we introduced a new approach of combining multiple classifiers in a heterogeneous ensemble system. Instead of using numerical membership values when combining, we constructed interval membership values for each class prediction from the meta-data of observation by using the concept of information granule. In the proposed method, the uncertainty (diversity) of the predictions produced by the base classifiers is quantified by the interval-based information granules. The decision model is then generated by considering both bound and length of the intervals. Extensive experimentation using the UCI datasets has demonstrated the superior performance of our algorithm over other algorithms including six fixed combining methods, one trainable combining method, AdaBoost, bagging, and random subspace. [ABSTRACT FROM AUTHOR]

The design process involves multiple stages to provide the solution for an actual or perceived need. The process needs different information at different stages to generate the desired output, but most of the time, the information is uncertain. Information uncertainty almost always makes design decision critical. The present work aims to reduce this information uncertainty in product design by reusing previous design knowledge. Reusing an existing ontology is an obvious way to minimize information uncertainty, and consequently, it can shorten the manufacturing lead time. However, the existing techniques have a few gaps that are still unaddressed. To fill these gaps, a methodology based on bionic engineering is proposed in this work for the purpose of design reuse in product development. Here, for the representation and manipulation of the knowledge, bionic-based reasoning approach is used for the development of the new product with the help of bionic reverse engineering. The proposed methodology is validated by illustrating an example of shoe design suitable to maneuver ill-conditioned roads. This work would be useful to the design and manufacturing practitioner in product development and decision making. [ABSTRACT FROM AUTHOR]

A smartphone user’s personal hotspot (pH) allows him to share a cellular connection to another (e.g., a traveler) in the vicinity, but such sharing consumes the limited data quota in his two-part tariff plan and may lead to an overage charge. This paper studies how to motivate such pH-enabled data-plan sharing between local users and travelers in the ever-growing roaming markets, and proposes pricing incentive for a data-plan buyer to reward surrounding pH sellers (if any). The pricing scheme practically takes into account the information uncertainty at the traveler side, including the random mobility and the sharing cost distribution of selfish local users who potentially share their pHs. Though the pricing optimization problem is non-convex, we show that there always exists a unique optimal price to a tradeoff between the successful sharing opportunity and the sharing price. We further generalize the optimal pricing to the case of heterogeneous selling pHs who have diverse data usage behaviors in the sharing cost distributions, and we show such diversity may or may not benefit the traveler. Lacking selfish pHs’ information, the traveler’s expected cost is higher than that under the complete information, but the gap diminishes as the pHs’ spatial density increases. Finally, we analyze the challenging scenario that multiple travelers overlap for demanding data-plan sharing, by resorting to a near-optimal pricing scheme. We show that a traveler suffers as the travelers’ spatial density increases. [ABSTRACT FROM AUTHOR]

We provide evidence consistent with the notion that prudent use of financial derivatives improves firms' information environment. We show that firms with sophisticated and comprehensive derivatives use policies display lower levels of uncertainty about future cash flows, volatility of future income and sales growth, and equity mispricing than those that do not use derivatives. However, we also show that policies that consist of large positions in a single type of derivative contract are not likely to produce similar benefits. These results remain intact even after accounting for the endogenous nature of derivatives use policy and information risk and mispricing. [ABSTRACT FROM AUTHOR]

Using a battery of look-ahead-bias free measures of accruals quality (AQ), we find a strong and long-lasting negative relation between future returns and AQ. In decile portfolios that rank on AQ, a hedge portfolio that goes long in the lowest decile and short in the highest decile generates an annualized, risk-adjusted return of 4-12 % over 1-month to 5-year horizons, depending on the AQ measure and the portfolio weighting scheme. The return premiums associated with AQ are, (1) robust to a wide range of AQ measures, (2) robust to a battery of return-informative variables, and (3) not driven by low-priced or small stocks, earnings shocks, or the fourth-quarter effect. The documented premiums are consistent with the information uncertainty effect where firm uncertainty is negatively related to future returns . [ABSTRACT FROM AUTHOR]