• Title/Summary/Keyword: Earnings Predictability

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A Comparison of Earnings Quality Between KOSPI Firms and KOSDAQ Firms (상장기업과 코스닥기업의 회계이익의 질 비교)

  • Moon, Hyun-Ju
    • Journal of Digital Convergence
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    • v.15 no.1
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    • pp.129-141
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    • 2017
  • This study analyzed and compared the accounting earnings quality after the adoption of K-IFRS, targeting the stock exchange-listed firms (KOSPI, KOSDAQ). The analysis first revealed that KOSPI had higher quality accruals, and better persistence and predictability of the reported earnings and cash flows, compared to KOSDAQ. Second, in both KOSPI and KOSDAQ, the predictability of future cash flow showed that the accounting earnings was better than the cash flows. Third, for the persistence and predictability of earnings associated with the degree of accruals, in KOSPI and KOSDAQ both all, groups with better accruals quality had greater persistence and predictability of earnings, and a better future cash flow predictability of accounting earnings.

Earnings Attributes that Contribute to Analyst Forecasting Errors: Empirical Evidence from Korea

  • KIM, Joonhyun
    • 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.

Data-Mining Bootstrap Procedure with Potential Predictors in Forecasting Models: Evidence from Eight Countries in the Asia-Pacific Stock Markets

  • Lee, Hojin
    • East Asian Economic Review
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    • v.23 no.4
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    • pp.333-351
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    • 2019
  • We use a data-mining bootstrap procedure to investigate the predictability test in the eight Asia-Pacific regional stock markets using in-sample and out-of-sample forecasting models. We address ourselves to the data-mining bias issues by using the data-mining bootstrap procedure proposed by Inoue and Kilian and applied to the US stock market data by Rapach and Wohar. The empirical findings show that stock returns are predictable not only in-sample but out-of-sample in Hong Kong, Malaysia, Singapore, and Korea with a few exceptions for some forecasting horizons. However, we find some significant disparity between in-sample and out-of-sample predictability in the Korean stock market. For Hong Kong, Malaysia, and Singapore, stock returns have predictable components both in-sample and out-of-sample. For the US, Australia, and Canada, we do not find any evidence of return predictability in-sample and out-of-sample with a few exceptions. For Japan, stock returns have a predictable component with price-earnings ratio as a forecasting variable for some out-of-sample forecasting horizons.

K-IFRS Reconciliations and Predicting Future Earnings (K-IFRS 도입 시점의 전환조정이 이후 기간의 미래이익 예측력에 미치는 영향)

  • Ji, Sang-Hyun;Kwak, Young-Min
    • Journal of Digital Convergence
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    • v.15 no.12
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    • pp.283-291
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    • 2017
  • This Study analyzes the predictability of accounting information from mandatory K-IFRS adoption using the K-IFRS reconciliations information. We use the sample of 2,557 firm-year Korea listed companies belonging to non-financial corporate sector during 2010-2016. Specifically, we examine whether K-IFS reconciliation would improve or reduce the predicting power for future earnings after K-IFRS adoption. The results of empirical analyses show that reconciliation information from discretionary judgement tend to reduce the predicting power of K-IFRS based accounting earnings for future earnings. This result indicates that managers are likely to use the adjustments process to reconcile K-GAAP accounting numbers with corresponding K-IFRS as means to realize the various private utility. This study is expected to provide useful information by suggesting the need for more rigid screening schemes for the K-IFRS reconciliation process and also for adequate measures to be taken to ensure that the interests of the outside investors are properly protected.

A Study on the Calculation and Provision of Accruals-Quality by Big Data Real-Time Predictive Analysis Program

  • Shin, YeounOuk
    • International journal of advanced smart convergence
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    • v.8 no.3
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    • pp.193-200
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    • 2019
  • Accruals-Quality(AQ) is an important proxy for evaluating the quality of accounting information disclosures. High-quality accounting information will provide high predictability and precision in the disclosure of earnings and will increase the response to stock prices. And high Accruals-Quality, such as mitigating heterogeneity in accounting information interpretation, provides information usefulness in capital markets. The purpose of this study is to suggest how AQ, which represents the quality of accounting information disclosure, is transformed into digitized data in real-time in combination with IT information technology and provided to financial analyst's information environment in real-time. And AQ is a framework for predictive analysis through big data log analysis system. This real-time information from AQ will help financial analysts to increase their activity and reduce information asymmetry. In addition, AQ, which is provided in real time through IT information technology, can be used as an important basis for decision-making by users of capital market information, and is expected to contribute in providing companies with incentives to voluntarily improve the quality of accounting information disclosure.

The Effect of Management Forecast Precision on CEO Compensation -Focusing on Bad news Firm- (악재를 경험한 기업의 경영자 이익예측 정확성이 경영자 보상에 미치는 영향)

  • Lee, Eun-Ju;Kim, Ha-Eun
    • Journal of Digital Convergence
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    • v.17 no.4
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    • pp.107-114
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    • 2019
  • This study analyzes the effect of the accuracy of future management performance, which managers voluntarily announce in the previous year's disclosure, on managers compensation. In the case of a company that disclosed the bad news in the previous year, the ability to predict uncertain future will be more important, and expects executives with better predictability to receive more compensation. The results of this study show that there is a significant negative(-) relationship between the accuracy of the manager's earnings forecast and the performance - compensation of the firms that disclosed the bad news in the previous year. The accuracy of the manager's disclosure is important, and it is confirmed that the manager's compensation increases as the incentive of the manager's effort to reduce future uncertainty. The results of this study are as follows: there is a positive relationship between the managerial performance and the managerial competence of managers. It is important to note that there is a difference and that we have identified additional determinants of the manager compensation contract.

Level Shifts and Long-term Memory in Stock Distribution Markets (주식유통시장의 층위이동과 장기기억과정)

  • Chung, Jin-Taek
    • Journal of Distribution Science
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    • v.14 no.1
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    • pp.93-102
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    • 2016
  • Purpose - The purpose of paper is studying the static and dynamic side for long-term memory storage properties, and increase the explanatory power regarding the long-term memory process by looking at the long-term storage attributes, Korea Composite Stock Price Index. The reason for the use of GPH statistic is to derive the modified statistic Korea's stock market, and to research a process of long-term memory. Research design, data, and methodology - Level shifts were subjected to be an empirical analysis by applying the GPH method. It has been modified by taking into account the daily log return of the Korea Composite Stock Price Index a. The Data, used for the stock market to analyze whether deciding the action by the long-term memory process, yield daily stock price index of the Korea Composite Stock Price Index and the rate of return a log. The studies were proceeded with long-term memory and long-term semiparametric method in deriving the long-term memory estimators. Chapter 2 examines the leading research, and Chapter 3 describes the long-term memory processes and estimation methods. GPH statistics induced modifications of statistics and discussed Whittle statistic. Chapter 4 used Korea Composite Stock Price Index to estimate the long-term memory process parameters. Chapter 6 presents the conclusions and implications. Results - If the price of the time series is generated by the abnormal process, it may be located in long-term memory by a time series. However, test results by price fixed GPH method is not followed by long-term memory process or fractional differential process. In the case of the time-series level shift, the present test method for a long-term memory processes has a considerable amount of bias, and there exists a structural change in the stock distribution market. This structural change has implications in level shift. Stratum level shift assays are not considered as shifted strata. They exist distinctly in the stock secondary market as bias, and are presented in the test statistic of non-long-term memory process. It also generates an error as a long-term memory that could lead to false results. Conclusions - Changes in long-term memory characteristics associated with level shift present the following two suggestions. One, if any impact outside is flowed for a long period of time, we can know that the long-term memory processes have characteristic of the average return gradually. When the investor makes an investment, the same reasoning applies to him in the light of the characteristics of the long-term memory. It is suggested that when investors make decisions on investment, it is necessary to consider the characters of the long-term storage in reference with causing investors to increase the uncertainty and potential. The other one is the thing which must be considered variously according to time-series. The research for price-earnings ratio and investment risk should be composed of the long-term memory characters, and it would have more predictability.