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  • 1
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    Accrual-based and cash-based earnings management in Algeria : substitution or complementary (2022)
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    UID:
    (DE-627)1810799937
    ISSN: 2459-5616
    Content: Managers are often employed many alternatives for earnings management following their objectives or the financial reporting objectives; the commonly used are the accrual-based and cash-based earnings management. The literature reveals that managers adopt the two strategies in different ways, suggesting a mixed relationship between them. Hence, this study investigates the relationship between the two strategies of earnings management in Algeria, whether it is a substitute or complementary. The study included 30 Algerian companies during 2011-2019, so a total of 270 firm-year observations were employed. Accrual-based earnings management was measured through the modified-Jones model, while cash-based earnings management was measured through the abnormal cash flows model. According to the results, Algerian companies engage more in accrual-based earnings management and employ the two strategies as substitutes, which explains the strong and negative effect of accrual-based on cash-based earnings management. We argue that companies engage first in accrual-based earnings management, and then they shift towards cash-based earnings management due to auditors' scrutiny. Furthermore, we found a positive and a medium effect of return on equity on cash-based earnings management, which reflects the managers' desire to adjust operating cash flows consistent with the reported earnings. Finally, the results indicated that company ownership, company listing, and the nature of financial statements do not affect cash-based earnings management.
    In: Croatian review of economic, business and social statistics, Warsaw : De Gruyter Open, 2015, 8(2022), 1, Seite 1-17, 2459-5616
    In: volume:8
    In: year:2022
    In: number:1
    In: pages:1-17
    Language: English
    Keywords: Aufsatz in Zeitschrift
    DOI: 10.2478/crebss-2022-0001
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  • 2
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    ANOVA bootstrapped principal components analysis for logistic regression (2022)
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    UID:
    (DE-627)1810800234
    ISSN: 2459-5616
    Content: Principal components analysis (PCA) is often used as a dimensionality reduction technique. A small number of principal components is selected to be used in a classification or a regression model to boost accuracy. A central issue in the PCA is how to select the number of principal components. Existing algorithms often result in contradictions and the researcher needs to manually select the final number of principal components to be used. In this research the author proposes a novel algorithm that automatically selects the number of principal components. This is achieved based on a combination of ANOVA ranking of principal components, the bootstrap and classification models. Unlike the classical approach, the algorithm we propose improves the accuracy of the logistic regression and selects the best combination of principal components that may not necessarily be ordered. The ANOVA bootstrapped PCA classification we propose is novel as it automatically selects the number of principal components that would maximise the accuracy of the classification model.
    In: Croatian review of economic, business and social statistics, Warsaw : De Gruyter Open, 2015, 8(2022), 1, Seite 18-31, 2459-5616
    In: volume:8
    In: year:2022
    In: number:1
    In: pages:18-31
    Language: English
    Keywords: Aufsatz in Zeitschrift
    DOI: 10.2478/crebss-2022-0002
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  • 3
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    Application of statistical methods in Internet financial information analysis (2020)
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    UID:
    (DE-627)1728070740
    ISSN: 2459-5616
    Content: In today's modern globalised world, we are faced with numerous data which form the basis for many crucial decisions. The ability to perform the analysis and interpret data correctly is, therefore, of essential importance in practically every field. The field of financial Information is one of such fields, especially the segment of information that is used by companies in corporate communication. This article is focused solely on the information that refers to the Internet financial reporting, which is important particularly for the external stakeholders. The research was made on the basis of the Internet Financial Reporting (IFR) Index for 27 Slovenian companies listed on the Ljubljana Stock Exchange. The article demonstrates the methodological approach to the creation of the IFR Index, which served as the new variable in the following steps of this research, for which various statistical analyses were performed (univariate, bivariate, and multivariate). Based on the descriptive statistics, the main characteristics of the IFR Index are identified, and, by using the t-test for two independent samples, it was found out that there is a difference among the companies listed in the two different listings. Moreover, through the use of the correlation analysis, the correlation between the IFRC and the IFR-P variables was verified, and, in the end, through the use of the multiple regression analysis, it was discovered that the size of the company is the factor which influences the level of the IFR Index. The purpose of this article is to show the awareness of the alternative research methods, and to facilitate the selection of the most appropriate method for addressing particular research questions in the Internet Financial Reporting.
    In: Croatian review of economic, business and social statistics, Warsaw : De Gruyter Open, 2015, 6(2020), 1 vom: Mai, Seite 43-55, 2459-5616
    In: volume:6
    In: year:2020
    In: number:1
    In: month:05
    In: pages:43-55
    Language: English
    Keywords: Aufsatz in Zeitschrift
    DOI: 10.2478/crebss-2020-0004
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  • 4
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    Assesing efficiency of targeting in social services in Federation of Bosnia and Herzegovina (2020)
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    UID:
    (DE-627)1728071194
    ISSN: 2459-5616
    Content: This paper analyses the inefficiency of social services targeting in the Federation of Bosnia and Herzegovina (FB&H). Using official statistics microdata of the Household Budget Survey 2015, three models of social minimum in FB&H were constructed: extreme and general poverty, and the model with multidimensional poverty aspects. The analysis of features of poor household categories showed that the most vulnerable residents of FB&H are not beneficiaries of permanent financial assistance. The reason for such an inefficient targeting was recognized in the Federal Law on Principles of Social Care, Care for the War-Disabled Civilians and Care for Families with Children that stipulates that only persons and families that (cumulatively): are incapable for work, have insufficient income, and there are no family members who are legally obligated to support them. The results indicated a high inconsistency in the legal criteria for qualification, and also in the amounts of permanent social assistance among cantons. The Proxy Means Test (PMT) Model is offered as one of the possible solutions for the improvement of social services targeting in FB&H. Given the importance of efficiency of targeting in social services, the research results could be useful, for both, vulnerable segments of the society and federal and cantonal ministries of labour and social affairs, in the process of targeting the households qualified for social support programmes.
    In: Croatian review of economic, business and social statistics, Warsaw : De Gruyter Open, 2015, 6(2020), 1 vom: Mai, Seite 56-74, 2459-5616
    In: volume:6
    In: year:2020
    In: number:1
    In: month:05
    In: pages:56-74
    Language: English
    Keywords: Aufsatz in Zeitschrift
    DOI: 10.2478/crebss-2020-0005
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  • 5
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    Auction theory and a note on game mechanisms (2021)
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    UID:
    (DE-627)1798133091
    ISSN: 2459-5616
    Content: This paper will review important topics on the subject of auction theory and mechanism design, these include: efficiency first and foremost, also revenue comparison between different types of auctions and the issue of incentive compatibility, individual rationality with the general idea and proof that bilateral trade is inefficient. Mechanism design theory tells us that if buyers and sellers both have private information full efficiency is impossible, however Vickrey auction (single unit auction) will be efficient i.e. will put the goods in the hands of the buyers that value them most. However, the conclusion from this paper is that because of overvaluation of bidders the main result is inefficient, i.e. bids are too high. When weak and strong bidders are compared the main conclusion is that strong bidders’ expected payoff is higher in second price auction (SPA), while weak bidder prefers first price auction (FPA) bid.
    In: Croatian review of economic, business and social statistics, Warsaw : De Gruyter Open, 2015, 7(2021), 1 vom: Mai, Seite 43-59, 2459-5616
    In: volume:7
    In: year:2021
    In: number:1
    In: month:05
    In: pages:43-59
    Language: English
    Keywords: Aufsatz in Zeitschrift
    DOI: 10.2478/crebss-2021-0004
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  • 6
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    Business and economics students' self-reports on academic reading in English as L2 : a factor analysis (2021)
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    UID:
    (DE-627)1798132737
    ISSN: 2459-5616
    Content: Adequate reading behaviour is vital for text comprehension across fields. In today's professional environment, a well-developed reading skill is also expected in English as a second language (EL2), which happens already in college, although transition to college-level reading may be difficult even in the first language. It is therefore useful to analyse students’ use of reading strategies to facilitate their academic progress. This study investigates the reading behaviour of junior students of business/economics when reading academic texts in EL2. We conducted an exploratory factor analysis (N=134) of a 45-item questionnaire about students' awareness of reading strategies and their reading confidence (i.e. self-perceived competence in text retelling). The majority of the items were based on self-reports found in the literature (Kolić-Vehovec, Bajšanski, 2001; Mokhtari, Reichard, 2002; Taraban, Kerr, Rynearson, 2004) and several items were added to the questionnaire (e.g. questions related to note taking). Five factors were interpretable: four factors related to Metacognitive Awareness of Reading Strategies (Repeated Reading, Monitoring/Regulation, Note Taking and Elaboration) and the fifth factor covering self-perceived competence in text retelling (Reading Confidence). Internal consistency of the factors indicated by standardized Cronbach's alphas were 0.83 (Repeated Reading), 0.80 (Monitoring and Regulation), 0.77 (Note Taking), 0.63 (Elaboration) and 0.75 (Reading Confidence). Three strategies positively correlated with each other (Repeated Reading, Monitoring/Regulation and Elaboration), while negative correlation was found between Note Taking and Reading Confidence. The results provide valuable information on the patterns in student reading as a baseline for further analysis of L2 text comprehension in college.
    In: Croatian review of economic, business and social statistics, Warsaw : De Gruyter Open, 2015, 7(2021), 1 vom: Mai, Seite 31-42, 2459-5616
    In: volume:7
    In: year:2021
    In: number:1
    In: month:05
    In: pages:31-42
    Language: English
    Keywords: Aufsatz in Zeitschrift
    DOI: 10.2478/crebss-2021-0003
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  • 7
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    Comparative analysis of stock selection using a hybrid MCDM approach and modern portfolio theory (2020)
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    UID:
    (DE-627)1745171827
    ISSN: 2459-5616
    Content: The problem of selecting an optimal set of investment stocks is of a huge interest for both individual and institutional investors. This paper compares the hybrid multiple criteria decision making (MCDM) approach to selecting the best stock to invest in, with the stock selection using modern portfolio theory (MPT). When selecting stocks, it is very important to thoroughly analyse stocks, according to multiple criteria, including their equity market indicators, as well as financial indicators. The objective of the research is to compare the stock selection using a hybrid MCDM approach and MPT, which includes only the equity market indicators. The analysed sample includes 18 stocks, which are CROBEX components on the Croatian capital market from January 2017 to January 2019. The rankings of stocks were calculated using five MCDM methods. These were then used to obtain the final hybrid stock ranking, which was compared to the MPT stock selection. The results show that there is a significant difference in the stock rankings. However, the stocks which have not entered any portfolio in MPT selection were ranked as lowest according to the hybrid MCDM approach, which confirms that those stocks are the worst to invest in. The research can serve as a guidance for investors to use all available stock information in their decision making process of investment.
    In: Croatian review of economic, business and social statistics, Warsaw : De Gruyter Open, 2015, 6(2020), 2 vom: Dez., Seite 58-68, 2459-5616
    In: volume:6
    In: year:2020
    In: number:2
    In: month:12
    In: pages:58-68
    Language: English
    Keywords: Aufsatz in Zeitschrift
    DOI: 10.2478/crebss-2020-0011
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  • 8
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    Comparing classification algorithms for prediction on CROBEX data (2020)
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    UID:
    (DE-627)1745149805
    ISSN: 2459-5616
    Content: The main objective of this analysis is to evaluate and compare the various classification algorithms for the automatic identification of favourable days for intraday trading using the Croatian stock index CROBEX data. Intra-day trading refers to the acquisition and sale of financial instruments on the same trading day. If the increase between the opening price and the closing price of the same day is substantial enough to earn a profit by purchasing at the opening price and selling at the closing price, the day is considered to be favourable for intra-day trading. The goal is to discover relation between selected financial indicators on a given day and the market situation on the following day i.e. to determine whether a day is favourable for day trading or not. The problem is modelled as a binary classification problem. The idea is to test different algorithms and to give greater attention to those that are more rarely used than traditional statistical methods. Thus, the following algorithms are used: neural network, support vector machine, random forest, as well as k-nearest neighbours and naïve Bayes classifier as classifiers that are more common. The work is an extension of authors' previous work in which the algorithms are compared on resamples resulting from tuning the algorithms, while here, each derived model is used to make predictions on new data. The results should add to the increasing corpus of stock market prediction research efforts and try to fill some gaps in this field of research for the Croatian market, in particular by using machine learning algorithms.
    In: Croatian review of economic, business and social statistics, Warsaw : De Gruyter Open, 2015, 6(2020), 2 vom: Dez., Seite 4-11, 2459-5616
    In: volume:6
    In: year:2020
    In: number:2
    In: month:12
    In: pages:4-11
    Language: English
    Keywords: Aufsatz in Zeitschrift
    DOI: 10.2478/crebss-2020-0007
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  • 9
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    A comparison of multilevel ordinal regression models in the analysis of police force ratings (2024)
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    UID:
    (DE-627)1899299971
    ISSN: 2459-5616
    In: Croatian review of economic, business and social statistics, Warsaw : De Gruyter Open, 2015, 10(2024), 1, Seite 1-12, 2459-5616
    In: volume:10
    In: year:2024
    In: number:1
    In: pages:1-12
    Language: English
    Keywords: Aufsatz in Zeitschrift
    DOI: 10.62366/crebss.2024.1.001
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  • 10
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    Conceptual understanding of linear regression among economics students at the university center of Tipaza, Algeria (2022)
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    UID:
    (DE-627)1848776829
    ISSN: 2459-5616
    Content: Solving problems related to econometrics requires a good knowledge of regression analysis concepts. The objective of this study is to evaluate students' difficulties resulting from the lack of knowledge of regression analysis concepts among economics students enrolled in the Master's cycle at the institute of economics at the university center of Tipaza (Algeria). In order to analyze students' answers, a typical correction was prepared based on professors' answers to this questionnaire. The procedure consists of comparing students' key answers with their corresponding typical answers to see how near or far it is from the right answer. In order to see whether the difficulties are originated from the same students, we analyzed the association between answers based on Multiple Correspondence Analysis (MCA) method. The principal results showed that difficulties resulting from the lack of knowledge of regression analysis concepts were prevalent among students. Their main causes were strongly related to misunderstanding, misconceptions and confusions. MCA analysis indicated that students can be categorized according to their answers into four groups: a very weak group, a weak group, an average group and a good group. We concluded that the difficulty of solving problems in the context of linear regression among students is the result of a lack of knowledge of regression concepts coupled with the inability to explain them.
    In: Croatian review of economic, business and social statistics, Warsaw : De Gruyter Open, 2015, 8(2022), 2, Seite 66-83, 2459-5616
    In: volume:8
    In: year:2022
    In: number:2
    In: pages:66-83
    Language: English
    Keywords: Aufsatz in Zeitschrift
    DOI: 10.2478/crebss-2022-0011
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