• Asia-Pacific Journal of Business
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• v.13 no.4
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• pp.109-121
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• 2022

Purpose - This study investigates how earnings volatility influences current stock price informativeness about expectations of future earnings. Design/methodology/approach - I adopt the FERC model developed by Collins et al. (1994) and modified by Lundholm and Myers (2002) to investigate the connection between earnings volatility and future earnings reflected in current returns. I define five-year rolling standard deviations of earnings and components as earnings volatility measures and the degree of deviation of earnings from cash flows over the same five-year, which is developed by Jayaraman (2008). Finding - My results show that earnings volatility delays current stock price response to future operation expectations. They also verify that as earnings are more divergent from cash flows, current returns are less timely incorporating value-relevant future operation. Research implications or Originality This study shows that when volatile earnings deliver obscure and unreliable information about future operation expectations, they cause the market to be conflicting in understandings their implications and make it difficult in attaining correct future cashflow estimates.

• Journal of Distribution Science
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• v.20 no.12
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• pp.117-123
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• 2022

Purpose: This study investigates the relationship between earnings forecasts estimated from a cross-sectional earnings forecast model and firm characteristics such as firm size, sales volatility, and earnings volatility. Research design, data and methodology: The association between earnings forecasts and the aforementioned firm characteristics is examined using 214 firm-year observations with analyst following and 848 firm-year observations without analyst following for the period of 2011-2019. I estimate future earnings using a cross-sectional earnings forecast model, and then compare these model-based earnings forecasts with analysts' earnings forecasts in terms of forecast bias and forecast accuracy. The earnings forecast bias and accuracy are regressed on firm size, sales volatility, and earnings volatility. Results: For a sample with analyst following, I find that the model-based earnings forecasts are more accurate as the firm size is larger, whereas the analysts' earnings forecasts are less biased and more accurate as the firm size is larger. However, for a sample without analyst following, I find that the model-based earnings forecasts are more pessimistic and less accurate as firms' past earnings are more volatile. Conclusions: Although model-based earnings forecasts are useful for evaluating firms without analyst following, their accuracy depends on the firms' earnings volatility.

• Journal of Labour Economics
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• v.36 no.3
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• pp.65-96
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• 2013

Analysis based on the Korea Labor and Income Panel Survey data reveals that earnings have become less volatile since the exchange rate crisis, while they have become more unequal. The reduction in measured earnings volatility is not explained by changes in the composition of various economic/demographic groups but accounted for by within-group reduction in the measured earnings volatility, which in turn is attributed to the reduced earnings mobility during the sample period. It is also found that measured earnings volatility is countercyclical and earnings changes are symmetric even during recessions.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.647-658
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• 2021

Analysts' forecasts are important for providing useful guidance to investors, especially individual or small investors, and therefore it becomes critical to identify the elements which can potentially increase errors in analysts' forecasts. This study investigates potential factors which can lead to errors in forecasting by analysts, specifically in terms of the level and attributes of corporate earnings. Utilizing a sample of firms listed on the Korean stock markets, this study provides evidence that firms with more volatile and unpredictable earnings feature less accurate analyst forecasts. This study fills a void in the literature by conducting empirical tests for earnings attributes in terms of volatility and unpredictability that could potentially undermine the forecast accuracy. The negative association between the quality of earnings and forecast accuracy is more pronounced for firms with negative net income values. Additional analysis demonstrates that forecast accuracy is significantly lower for the fourth quarter than for other fiscal quarters and that fourth quarter earnings tend to be more volatile and unpredictable. This study contributes to the literature by providing new empirical evidence regarding the comprehensive effects of earnings quality and level on analysts' forecasting accuracy and further suggests potential factors contributing to the fourth quarter anomaly in analyst forecasts in terms of earnings attributes.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.3
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• pp.73-85
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• 2020

The study aims to provide better understanding of sustainable earnings by a comprehensive analysis of earnings persistence of business firms in Vietnam as an example of developing economies in South-East Asia. Dataset of 1,278 publicly listed firms (excluding banking and financial services firms) on Vietnam Stock Exchange for the period from 2008 to 2017 was collected. By applying fixed effect regression model, the empirical results provided the basis to measure the persistence index (Pers index) and find low level of their earnings persistence. The literature of earnings quality analysis in developed countries suggests earnings persistence as a noteworthy determinant of future earnings forecast and stock valuation. However, research of sustainable earnings in developing countries is still highly underdeveloped. For Vietnamese listed firms, the average Pers index was estimated for the period from 2008 to 2010, indicating low level of earnings persistence. We also incorporated earnings persistence level into future earnings forecast by running the quintile regression model divided the data into four equal levels and conducted each section independently to see the difference in each percentile, thence assessed the factors' influence on the specific model. The findings provide important information on the expected returns of firms, especially helping investors make sound decisions.

• The Korean Journal of Financial Studies
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• v.3 no.1
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• pp.233-265
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• 1996

We examine the impact of public and private information on price movements using the thirty DJIA stocks and twenty-one NASDAQ stocks. We find that the standard deviation of daily returns on information days (dividend announcement, earnings announcement, insider purchase, or insider sale) is much higher than on no-information days. Both public information matters at the NYSE, probably due to masked identification of insiders. Earnings announcement has the greatest impact for both DJIA and NASDAQ stocks, and there is some evidence of positive impact of insider asle on return volatility of NASDAQ stocks. There has been considerable debate, e.g., French and Roll (1986), over whether market volatility is due to public information or private information-the latter gathered through costly search and only revealed through trading. Public information is composed of (1) marketwide public information such as regularly scheduled federal economic announcements (e.g., employment, GNP, leading indicators) and (2) company-specific public information such as dividend and earnings announcements. Policy makers and corporate insiders have a better access to marketwide private information (e.g., a new monetary policy decision made in the Federal Reserve Board meeting) and company-specific private information, respectively, compated to the general public. Ederington and Lee (1993) show that marketwide public information accounts for most of the observed volatility patterns in interest rate and foreign exchange futures markets. Company-specific public information is explored by Patell and Wolfson (1984) and Jennings and Starks (1985). They show that dividend and earnings announcements induce higher than normal volatility in equity prices. Kyle (1985), Admati and Pfleiderer (1988), Barclay, Litzenberger and Warner (1990), Foster and Viswanathan (1990), Back (1992), and Barclay and Warner (1993) show that the private information help by informed traders and revealed through trading influences market volatility. Cornell and Sirri (1992)' and Meulbroek (1992) investigate the actual insider trading activities in a tender offer case and the prosecuted illegal trading cased, respectively. This paper examines the aggregate and individual impact of marketwide information, company-specific public information, and company-specific private information on equity prices. Specifically, we use the thirty common stocks in the Dow Jones Industrial Average (DJIA) and twenty one National Association of Securities Dealers Automated Quotations (NASDAQ) common stocks to examine how their prices react to information. Marketwide information (public and private) is estimated by the movement in the Standard and Poors (S & P) 500 Index price for the DJIA stocks and the movement in the NASDAQ Composite Index price for the NASDAQ stocks. Divedend and earnings announcements are used as a subset of company-specific public information. The trading activity of corporate insiders (major corporate officers, members of the board of directors, and owners of at least 10 percent of any equity class) with an access to private information can be cannot legally trade on private information. Therefore, most insider transactions are not necessarily based on private information. Nevertheless, we hypothesize that market participants observe how insiders trade in order to infer any information that they cannot possess because insiders tend to buy (sell) when they have good (bad) information about their company. For example, Damodaran and Liu (1993) show that insiders of real estate investment trusts buy (sell) after they receive favorable (unfavorable) appraisal news before the information in these appraisals is released to the public. Price discovery in a competitive multiple-dealership market (NASDAQ) would be different from that in a monopolistic specialist system (NYSE). Consequently, we hypothesize that NASDAQ stocks are affected more by private information (or more precisely, insider trading) than the DJIA stocks. In the next section, we describe our choices of the fifty-one stocks and the public and private information set. We also discuss institutional differences between the NYSE and the NASDAQ market. In Section II, we examine the implications of public and private information for the volatility of daily returns of each stock. In Section III, we turn to the question of the relative importance of individual elements of our information set. Further analysis of the five DJIA stocks and the four NASDAQ stocks that are most sensitive to earnings announcements is given in Section IV, and our results are summarized in Section V.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.3
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• pp.203-215
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• 2022

Bayesian Networks are multivariate probabilistic factor graphs that are used to assess underlying factor relationships. From January 2005 to December 2018, the study examines how Dynamic Bayesian Networks can be utilized to estimate portfolio risk and return as well as determine inter-factor relationships among reversal profit-generating components in Pakistan's emerging market (PSX). The goal of this article is to uncover the factors that cause reversal profits in the Pakistani stock market. In visual form, Bayesian networks can generate causal and inferential probabilistic relationships. Investors might update their stock return values in the network simultaneously with fresh market information, resulting in a dynamic shift in portfolio risk distribution across the networks. The findings show that investments in low net profit margin, low investment, and high volatility-based designed portfolios yield the biggest dynamical reversal profits. The main triggering aspects related to generation reversal profits in the Pakistan market, in the long run, are net profit margin, market risk premium, investment, size, and volatility factor. Investors should invest in and build portfolios with small companies that have a low price-to-earnings ratio, small earnings per share, and minimal volatility, according to the most likely explanation.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.1
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• pp.81-90
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• 2020

We examine the effects of the complexity of tax-related information on the issuance of analyst's pre-tax income forecast and its value relevance. If analysts respond adequately to the needs of investors, they are more likely to provide a pre-tax income forecast. The provision of a pre-tax income forecast may indicate analysts' confidence in assessing the quality of earnings. Thus, investors, in turn, would be more confident in the analysts' pre-tax income forecasts if analysts provide both pre-tax and earnings forecasts than only the latter. Using a sample of Korean listed companies for 2005-2014, we find that analysts are likely to provide an implicit tax forecast when the volatility of the effective tax rate is low and the book-tax differences are small. We also find that when analysts provide pre-tax and after tax income forecasts, the value relevance for unexpected earnings increases. These results indicate that analysts are likely to be interested in corporate tax information and the complexity of tax-related information affects the availability of implicit tax forecasts. Furthermore, this study provides empirical evidence that when analysts provide both pre-tax and after tax income forecasts, investors have more confidence in analysts' earnings forecasts, which results in greater investors' responses.

• Journal of Korea Trade
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• v.23 no.6
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• pp.66-92
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• 2019

Purpose - Foreign Exchange Rates (FER) have been one of the most significant factors for both Korean exporters and the economy of Korea. The purpose of this study is to evaluate whether exporters with a high level of Exchange Rate Elasticity of Sales (ERES) make the use of earnings management for Income Smoothing (IS). Design/methodology - Income smoothing was obtained using the methodology suggested by Leuz, Nanda and Wysocki (2003). Accruals-based Earnings Management (AEM) was estimated using Discretionary Accruals (DA) calculated by the operant Jones Model developed by Dechow, Sloan and Sweeney (1995). Real Earnings Management (REM) was obtained using the methodologies suggested by Roychowdhury (2006) and Cohen and Zarowin (2010). Data were 2,402 firm years of public listed companies on the KRX, which were not in the financial industry and had a settlement of accounts in December for the period from 2013 to 2017. Findings - Results of the evaluation are as follows. First, companies with higher levels of ERES have relatively lower levels of smoothing of reported income. This might be because a fluctuation in sales caused by an exchange rate fluctuation has a direct impact on the volatility of the reported income. Second, companies with high levels of both ERES and IS have a positive correlation with both AEM and REM. This might be because companies with high levels of IS engage in earnings management to smooth reported income. Specifically, it is possible to assume that for smoothing the reported income, not only AEM but also REM is practiced. Third, companies with high levels of ERES but low levels of IS have a negative correlation with both AEM and REM. This could be interpreted as companies exhibiting low levels of IS due to higher levels of ERES tend to control IS. In addition, such results were supported by firms relying highly on exporting, and are consequently sensitive to exchange rate fluctuation. Therefore, it may conclude that companies with high levels of ERES make the use of earnings management as a means of IS. Originality/value - This study can find its significance from the fact that it is the first study, empirically verifying that companies of Korea, where exportation is a large part, use both AEM and REM as a means for smoothing reported income upon facing exchange rate fluctuations. In addition, it is highly expected that the results of this study could be useful for participants of financial markets when making IS-related decisions.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.349-356
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• 2021

This study comprehensively investigates whether there is an impact of risk, size, profitability, earnings per share, dividend yield, and book-to-market equity on the stock prices of Jordanian banks listed on the Amman Stock Exchange (ASE) for the period 2006-2018. To mitigate endogeneity concerns and to control for within-bank dynamics, panel data fixed effects estimations are used. This study shows that size (SIZE), profitability (ROA), dividend yield (DY) and book-to-market equity (BE/ME) ratios are statistically significant determinants of stock prices. The risk (RISK) factor measured by volatility of ROA has a positive and significant effect on the stock prices, while earnings per share has minimum influence on the stock prices. The results show that ROA has a significant and positive effect and provides the largest effect among all variables used in this study, while the RISK factor has a positive and significant effect. In contrast, SIZE, DY, and BE/ME have a significant negative effect on stock prices. The paper presented new evidence showing that ROA is a better determinant of stock prices in Jordanian banks, and RISK significantly affects stock prices. The researcher recommends using a factor of profitability represented by ROA which has a significant positive effect on the stock prices in Jordanian banks and applying the ROA variable to other sectors.