scholarly journals Disclosure Dynamics and Investor Learning

2020 ◽  
Author(s):  
Frank S. Zhou

This paper examines whether investor learning about profitability (i.e., the mean of earnings distribution) leads to persistence in disclosure decisions. A repeated single-period model shows that persistent investor beliefs about profitability lead to persistent disclosure decisions. Using earnings forecast data, I structurally estimate the model and perform several counterfactual analyses. I find that, when investors are assumed to know profitability, the persistence of management forecast decisions significantly declines by 17%–27%. About 24% of firms would have disclosed differently, resulting in 3.9% net change in the amount of information (i.e., posterior variance) provided to the capital market. Collectively, the results indicate the importance of learning profitability in understanding disclosure decisions and the capital market consequences of disclosures. This paper was accepted by Shiva Rajgopal, accounting.

2020 ◽  
Vol 55 (03) ◽  
pp. 2050012
Author(s):  
Max Göttsche ◽  
Stephan Küster ◽  
Tobias Steindl

Prior studies on the relationship between culture and discretionary disclosure fail to account for concurrent managerial incentives to reveal private information to the capital market. Our study extends the literature by investigating whether these managerial incentives offset the cultural influence on managers’ discretionary disclosure decisions. To this end, we exploit a setting in which managers have the discretion to influence both the quantity and quality of disclosure and can thereby either conceal or reveal private information. For a sample of European firms, we find that despite incentives to reveal private information, managers’ culturally determined preference for secrecy leads them to provide a low quantity as well as a lower quality of disclosure. Our results are robust to several sensitivity checks and demonstrate the relative importance of cultural influence on discretionary disclosure decisions.


2016 ◽  
Vol 91 (4) ◽  
pp. 1023-1049 ◽  
Author(s):  
François Brochet ◽  
Patricia Naranjo ◽  
Gwen Yu

ABSTRACT We examine how language barriers affect the capital market reaction to information disclosures. Using transcripts from non-U.S. firms' English-language conference calls, we find that the calls of firms in countries with greater language barriers are more likely to contain non-plain English and erroneous expressions. For non-U.S. firms that hire an English-speaking manager, we find less use of non-plain English and fewer erroneous expressions. Calls with a greater use of non-plain English and more erroneous expressions show lower intraday price movement and trading volume. The capital market responses to non-plain English and erroneous expressions are more negative when the firm is located in a non-English-speaking country and has more English-speaking analysts participating in the call. Our results highlight that, when disclosure happens verbally, language barriers between speakers and listeners affect its transparency, which, in turn, impacts the market's reaction.


2014 ◽  
Vol 90 (4) ◽  
pp. 1395-1435 ◽  
Author(s):  
Long Chen ◽  
Jeff Ng ◽  
Albert Tsang

ABSTRACT Using a comprehensive dataset of international cross-listings spanning 34 (50) home (target) countries, we examine whether mandatory IFRS adoption facilitates firms' cross-listing activities. Our results using difference-in-differences analyses show that firms that mandatorily adopt IFRS exhibit significantly higher cross-listing propensity and intensity following IFRS adoption. We also find that firms from mandatory IFRS adoption countries are more likely to cross-list their securities in countries also mandating IFRS and countries with larger and more liquid capital markets. We further find that IFRS adoption has a greater effect on mandatory IFRS adopters from countries with larger accounting differences from IFRS, lower disclosure requirements, and less access to external capital prior to IFRS adoption. Our findings are consistent with the notion that mandatory IFRS adoption facilitates firms' cross-listing activities and highlight the importance of considering the change in cross-listings when examining the capital market consequences of mandatory IFRS adoption.


2021 ◽  
pp. 0148558X2110362
Author(s):  
Yutaro Murakami ◽  
Atsushi Shiiba

This paper considers how a manager decides to disclose or withhold segment information in a capital market setting. In particular, we develop a multi-period model in which a manager in each period decides how to allocate her effort between two businesses. The profit earned in each segment is determined by the manager’s effort and ability as well as each segment’s market profitability and inherent uncertainty. In this setting, in contrast to the expectation of segment disclosure being withheld due to conflicts of interest between managers and shareholders, we identify the conditions under which the manager rationally withholds segment information and achieves higher social welfare. In a setting where the manager is concerned about the current stock price, disclosing more disaggregated information to the stock market does not necessarily lead to more efficient monitoring. The capital market values various segment earnings differently, and in response to this valuation, a rational manager may greatly alter her behavior, leading to inefficient outcomes.


2003 ◽  
pp. 95-101
Author(s):  
O. Khmyz

Acording to the author's opinion, institutional investors (from many participants of the capital market) play the main role, especially investment funds. They supply to small-sized investors special investment services, which allow them to participate in the investment process. However excessive institutialization and increasing number of hedge-funds may lead to financial crisis.


2020 ◽  
Vol 2 (2) ◽  
pp. 454
Author(s):  
Julkifli Purnama ◽  
Ahmad Juliana

Investment in the capital market every manager needs to analyze to make decisions so that the right target to produce profits in accordance with what is expected. For that, we need a way to predict the decisions that will be taken in the future. The research objective is to find the best model and forecasting of the composite stock price index (CSPI). Data analysis technique The ARIMA Model time series data from historical data is the basis for forecasting. Secondary data is the closing price of the JCI on July 16 2018 to July 16 2019 to see how accurate the forecasting is done on the actual data at that time. The results of the study that the best Arima model is Arima 2.1.2 with an R-squared value of 0.014500, Schwarz criterion 10.83497 and Akaike info criterion of 10.77973. Results of forecasting actual data are 6394,609, dynamic forecast 6387,551 selisish -7,05799, statistics forecas 6400,653 difference of 6,043909. For investors or the public can use the ARIMA method to be able to predict or predict the capital market that will occur in the next period.


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