• Title/Summary/Keyword: Logit Regressions

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A Study on the Enterprise Value Analysis using AHP and Logit Regressions (AHP와 로짓회귀분석을 활용한 기업가치 분석방법)

  • Gu, Seung-Hwan;Shin, Tack-Hyun;Yuldashev, Zafar
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.16 no.9
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    • pp.5810-5818
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    • 2015
  • The dissertation presents the portfolio construction method using the score sheet so that general investors can utilize it easily. This study draws the significant variables to contribute the enterprise value and suggests the combined models by applying the single methodology, which private investors can easily utilize. The results of the research can be classified into 2 areas. Firstly, the significantly affecting variables were selected for analyzing the enterprise value. The variables and the method for the enterprise value analysis were studied from the existing researches to choose the optimal variables. The variables were identified by using AHP method and the structure equation method from the investigation of the previous researches. And the critical variables were added extracted from the common denominator of variables which the 3 grue investors used for their investment. The final variables identified are dividend yield, PER, PBR, PCR, EV/EBITDA, ROE, net income, sales growth rate, net current asset, debt ratio, current ratio, rate of operating profits, ratio of operating profit to net sales, ratio of net income to net sales, net profit to total assets, EPS growth rate, inventory turnover ratio, and receivables turnover. Second, the new methodologies for forecasting enterprise value modifying the existing methods were developed. The result of the Logistic regression analysis for forecasting showed that the equation could not be suitable as the accuracy with 91.98%.

The Relationship Between Family Ownership, CEO Demographic Characteristics and Dividend Policy: Evidence from Indonesia

  • MADYAN, Muhammad;SETIAWAN, Wulan Rahmadani;SETIANTO, Rahmat Heru;AL-ISLAMI, Moch. Ali Fudin;SHIDIQ, Hasbi Ash
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.12
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    • pp.159-167
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    • 2021
  • The objective of this study is to examine the effect of family ownership and family CEO on the dividend policy of family firms by using the demographic characteristics of the CEO as a moderator. Dividend policy is a decision taken by the firm in determining whether the profits earned by the firm will be distributed to shareholders in the form of dividends or will be reinvested in the company as retained earnings for future internal resources. Using samples from non-financial family firms listed on the Indonesian Stock Exchange in 2013-2017, 93 firms were selected based on adequate data. We also used logit regressions to provide robustness. The results show that family ownership and family CEO have a positive effect on the dividend payout ratio. This finding supports the family income hypothesis. Among CEO demographic characters, CEO age significantly strengthens the positive effect of family CEO on dividend payout ratio. While CEO tenure does not significantly strengthen the positive effect of family CEOs on dividend payout ratios. Meanwhile, leverage, ROA, and firm size significantly affect the dividend payout ratio, but firm age does not significantly affect the dividend payout ratio.

Corporate Cash Shortfalls and External Financing: Evidence from Korea (현금부족이 외부자본 조달 결정에 미치는 영향)

  • So-Yeon Kim;Meiyan Jin;Saeyeul Park
    • Asia-Pacific Journal of Business
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    • v.14 no.1
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    • pp.215-229
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    • 2023
  • Purpose - Based on the funding-horizon theory, this study aims to test the effects of cash needs and the persistence of external funding needs on firms' external financing. Design/methodology/approach - Financial data of Korean listed companies were collected from DataGuide. Immediate and near-term cash shortfalls are defined using the methodology of Haung and Ritter (2021). We estimate multinomial logit regressions for the financing choice. Findings - First, all three cash depletion variables used in our study increase the likelihood of external financing. Second, firms prefer to issue debt to meet immediate spending and equity to meet long-lived cash needs. Third, this effect is more pronounced for high R&D firms. Fourth, chaebol firms with internal capital markets defer raising external capital for immediate and near-term cash needs. Research implications or Originality - This paper provide empirical evidence that immediate and near-term cash needs induce external financing, and the persistence of cash needs affects the choice between debt and equity, the finding which is consistent with the funding-horizon theory of financing decisions. Being the first paper to test the funding-horizon theory using Korean data, this paper contributes to the literature on the capital structure of Korean firms.

Illegal Cash Accommodation Detection Modeling Using Ensemble Size Reduction (신용카드 불법현금융통 적발을 위한 축소된 앙상블 모형)

  • Lee, Hwa-Kyung;Han, Sang-Bum;Jhee, Won-Chul
    • Journal of Intelligence and Information Systems
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    • v.16 no.1
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    • pp.93-116
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    • 2010
  • Ensemble approach is applied to the detection modeling of illegal cash accommodation (ICA) that is the well-known type of fraudulent usages of credit cards in far east nations and has not been addressed in the academic literatures. The performance of fraud detection model (FDM) suffers from the imbalanced data problem, which can be remedied to some extent using an ensemble of many classifiers. It is generally accepted that ensembles of classifiers produce better accuracy than a single classifier provided there is diversity in the ensemble. Furthermore, recent researches reveal that it may be better to ensemble some selected classifiers instead of all of the classifiers at hand. For the effective detection of ICA, we adopt ensemble size reduction technique that prunes the ensemble of all classifiers using accuracy and diversity measures. The diversity in ensemble manifests itself as disagreement or ambiguity among members. Data imbalance intrinsic to FDM affects our approach for ICA detection in two ways. First, we suggest the training procedure with over-sampling methods to obtain diverse training data sets. Second, we use some variants of accuracy and diversity measures that focus on fraud class. We also dynamically calculate the diversity measure-Forward Addition and Backward Elimination. In our experiments, Neural Networks, Decision Trees and Logit Regressions are the base models as the ensemble members and the performance of homogeneous ensembles are compared with that of heterogeneous ensembles. The experimental results show that the reduced size ensemble is as accurate on average over the data-sets tested as the non-pruned version, which provides benefits in terms of its application efficiency and reduced complexity of the ensemble.

Further Empirical Analysis on Corporate R&D Intensity for KOSDAQ Listed SMEs in the Era of the Post Global Economic Crisis (국제금융위기 이후의 코스닥 상장 중소기업들의 연구개발비에 대한 실증적 심층분석)

  • Kim, Hanjoon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.2
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    • pp.248-258
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    • 2021
  • The study analyzed the financial determinants of corporate R&D intensity that require more attention from academics and practitioners in the Korean capital market. Domestic small and medium enterprises (SMEs) may face with developing substitutes by making more R&D investments in scale and scope, given the unprecedented economic conditions such as the limitation of importing core components and materials from other nation(s). KOSDAQ-listed SMEs were selected as sample data, whose R&D expenditures may be less than those of large firms during the post-global financial turmoil period (2010~2018). Static panel data model was applied, along with Tobit and stepwise regression models, for examining the validity of results. Logit, probit, and complementary log-log regressions were also employed for a relative analysis. R&D expenditures in the prior year, the interaction effect between the previous R&D intensity and high-tech sector, firm size, and growth rate were significant to determine R&D intensity. Moreover, a majority of explanatory variables were found to change between the years 2011 and 2018, while time-lagged effects between the R&D intensity and growth rate exist. Results of the study are expected to be used for future research to detect optimal levels of R&D expenditures for the value maximization of SMEs.

Factors Associated with Relapse to Smoking Behavior Using Health Belief Model (건강믿음모형을 이용한 금연성공자의 재흡연에 영향을 미치는 요인 분석: 금연클리닉 등록자를 중심으로)

  • Kim, Hee-Suk;Bae, Sang-Soo
    • Journal of agricultural medicine and community health
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    • v.36 no.2
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    • pp.87-100
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    • 2011
  • Objectives: This study aimed to identify factors associated with smoking relapse. Methods: The study sample was recruited among subjects who were enrolled in the smoking cessation clinic of a public health center and had succeeded in quitting smoking for at least six months. A total of 159 male subjects were followed via mail survey one year later. The independent variables in the analyses were socio-demographic characteristics, smoking history and behavior, receipt of smoking cessation aids, health behaviors and components of the health belief model (HBM). The dependent variable was smoking relapse assessed one year after quitting. Ordered logit regressions were used to identify factors associated with smoking relapse. Results: The relapse rate of the ex-smokers in our sample was 25.8%, and the occasional smoking rate was 17.0%. Univariate analyses revealed that only factors related to the HBM, such as perceived susceptibility to diseases (p<0.01), perceived severity of diseases (p<0.01), perceived health benefits of not smoking (p<0.01), perceived barriers to quitting smoking due to increasing stress and difficulty in social life (p<0.01), and self-efficacy (p<0.01) were associated with the likelihood of relapse for ex-smokers. Ordered logit analyses yielded two significant factors affecting the likelihood of relapse, the perceived barriers to quitting smoking and self-efficacy. Conclusions: Our results indicate that higher levels of barriers to quitting smoking and lower levels of self-efficacy were significantly related to risk of smoking relapse. These findings may be useful for identifying those at highest risk for relapse and choosing the optimal strategies for prevention of relapse for ex-smokers.