دانشگاه اصفهان مدیریت دارایی و تامین مالی 2383-1189 11 3 2023 09 23 42 سال یازدهم، شماره سوم، شماره پیاپی 42، پاییز 1402 28460 10.22108/amf.2023.28460 FA Journal Article 2024 05 27 https://amf.ui.ac.ir/article_28460_7d29105f6a1f952699eb6d4a05838e81.pdf

دانشگاه اصفهان مدیریت دارایی و تامین مالی 2383-1189 11 3 2023 09 23 The Relationship between Credit Rating and Stock Returns with an Emphasis on the Role of Investors' Emotions رابطه رتبه اعتباری و بازده سهام با تاکید بر نقش احساسات سرمایه‌گذاران 1 22 27491 10.22108/amf.2023.136083.1771 FA محمد مهدی باقری دانشجوی کارشناسی ارشد،گروه حسابداری، دانشکدۀ مدیریت و حسابداری، دانشگاه علامه طباطبایی، تهران، ایران. روح اله صدیقی استادیار گروه حسابداری، دانشکده مدیریت و حسابداری، دانشگاه علامه طباطبایی، تهران، ایران. Journal Article 2022 12 26 Conventionally, it is thought that stocks with a high risk should yield higher returns. However, this notion is empirically incorrect. The reason for such a contradiction can be investors' feelings. Therefore, the purpose of this study was to investigate the relationship between investors` sentiments, business credit, and stock returns. For this purpose, the data of 130 companies were collected monthly for the period 2013-2019 (10,920 months-companies). The results supported the view that credit risk has a negative relationship with future stock returns. In the same way, it was observed that the investors' sentiments in speculative stocks are were on average higher than the investment stocks. Also, the results of univariate analysis based on quantile regression showed that there was a negative relationship between credit rating and the investors' sentiments in all the quantiles. Crowdfunding has become a modern and favorite financing channel worldwide. Crowdfunding is a new financing method that helps entrepreneurs acquire the financial resources needed for their projects. This study aimed to investigate the factors affecting individuals' interest in participating and investing in crowdfunding projects. Using the Structural Equations Modeling (SEM) technique, the developed model was tested with the help of Amos software via the data obtained from 318 individuals. This paper examined the direct and indirect contextual variables: awareness of need, altruism, reputation, psychological benefits, efficacy, funder’s trust, and institution-based trust in the investment intention. Finally, it was observed that awareness of need, altruism, values, reputation, psychological benefits, efficacy, funder’s trust, and institution-based trust were the factors influencing people's intention to invest in crowdfunding projects. Keywords: Investors, Credit Rating, Equity Returns, Financial Distress, Cash. Introduction The relationship between credit rating and stock returns is a complex one that has been the subject of much research and debate in the field of finance. Credit ratings are is an important indicator of the credit worthiness of a company or entity, and can have a significant impact on its ability to borrow money and issue debt securities. At the same time, stock returns represent the performance of a company's equity, and are closely watched by investors as a key indicator of its financial health. Investor’s sentiment one is a factor that plays a significant role in the relationship between credit rating and stock returns is investor sentiment. Investor sentiment refers to the overall mood or attitude of an investor towards the markets, which can be influenced by a wide range of factors, including economic indicators, political events, and news headlines. When the investors` sentiment is positive, investors tend to be more willing to take risks and invest in stocks with lower credit ratings. This can lead to higher stock returns for companies with weaker credit ratings, as the demand for their shares increases. Conversely, when an investor’s sentiment turns negative, he may become more risk-averse and focus on investing in companies with stronger credit ratings. This can result in lower stock returns for companies with weaker credit ratings, as the demand for their shares decreases. Overall, while credit ratings play an important role in determining a company's ability to raise capital and issue debt, their impact on stock returns is often mediated by investor’s sentiment. Understanding this complex relationship is essential for investors that looking to make informed investment decisions in today's dynamic financial markets. Method and Data The dependent and independent variables were spending on the stock risk and company’s credit rating, respectively. Investors' sentiment was also a moderating variable. The first hypothesis stated that credit rating had a positive and significant effect on excess stock returns. The second hypothesis stated that investor’s sentiment had a moderating role in the relationship between credit rating and excess stock returns. To collect the data based on the systematic elimination method, 130 companies (10,920 company-month observations) for the time period of 2013-2019 were selected from among the companies admitted to the Tehran Stock Exchange. Also, to test the research hypotheses, the multivariate regression model with panel data, and Ordinary Least Squares (OLS) approach and robust standard errors were used. Research Findings: The results of the univariate quantile regression analysis showed that there was a negative relationship between credit rating and the investors' sentiments in all the quantiles. Also, the results of the first hypothesis revealed that increasing the credit ratings of companies led to an increase in future returns. Also, the second hypothesis demonstrated that stocks with positive sentiments in the past tended to underperform in the next month. In line with investigating the interactive effects of company’s credit rating and investor’s sentiments, it was observed that the investors' sentiments strengthened the effect of credit ratings of the companies' on future returns. In fact, the estimates showed that optimistic sentiments formed by individual investors helped explain the positive relationship between excess returns and credit rating. Discussion of Results and Conclusion: The results of the present research revealed that increasing the credit ratings of the companies led to an increase in future stock returns. These results were against the theoretical background of the view that "higher risk is associated with higher returns". In fact, it could be argued that stocks with low credit ratings were traded because retail investors favored stocks that were speculative in nature, i.e., stocks that had the potential for extraordinary excess returns. Since retail investors bought these stocks for speculative purposes, they overpriced them. However, after increasing the yield over the coming years, the yield decreased and the prices returned to their real values. Therefore, the reason for such a relationship had to be sought in the retail investors’ feelings. Also, it was observed that the investors' sentiments strengthened the effect of the credit ratings of the companies on future returns. In fact, the estimates showed that optimistic sentiments formed by individual investors helped explain the positive relationship between excess returns and credit rating. These results were also confirmed by examining each dimension of the investors' feelings. Therefore, we could confirm the hypothesis that the investors' feelings were the reason for the positive/negative relationship between the credit rating (credit risk) and future stock returns. اهداف: به‌طور متعارف تصور می‌شود، سهام با ریسک زیاد باید بازدۀ بیشتری به‌همراه داشته باشد؛ با این حال، این تصور ازنظر تجربی نادرست است. دلیل چنین تناقضاتی به‌احتمال احساسات سرمایه‌گذاران است؛ بنابراین هدف این پژوهش، بررسی ارتباط احساسات سرمایه‌گذار، اعتبار تجاری و بازدۀ سهام است. روش: احساسات سرمایه‌گذاران براساس شاخصی که ترکیبی از قدرت نسبی، خط روان‌شناسی، حجم معاملات و نرخ تعدیل‌شدۀ گردش سهام اندازه‌گیری شده است. برای این منظور داده‌های ۱۳۰ شرکت به‌صورت ماهانه برای دورۀ ۱۳۹۳ تا ۱۳۹۹ (۱۰۹۲۰ ماه-شرکت) جمع‌آوری شد. نتایج: نتایج به‌دست‌آمده، از این دیدگاه حمایت می‌کند که ریسک اعتباری با بازدۀ آتی سهام رابطۀ منفی دارد. به همین ترتیب مشاهده شد که احساسات سرمایه‌گذاران در سهام سفته‌بازی به‌طور میانگین بیشتر از سهام سرمایه‌گذاری است؛ همچنین نتایج حاصل از تحلیل تک متغیره براساس رگرسیون کوانتایل نشان‌دهندۀ آن بود که در تمامی کوانتایل‌ها بین رتبۀ اعتباری و احساسات سرمایه‌گذاران رابطۀ منفی وجود دارد

https://amf.ui.ac.ir/article_27491_a4fd897938e109a8f2ae6a4dd9f797e9.pdf

دانشگاه اصفهان مدیریت دارایی و تامین مالی 2383-1189 11 3 2023 09 23 Exploratory Analysis of the Heterogeneity in the Relationship between Information Asymmetry and the Cost of Equity Capital: A Meta-Analytic Approach تحلیل اکتشافی دلایل واگرایی رابطه عدم تقارن اطلاعاتی و هزینۀ سرمایۀ سهام: رویکرد فراتحلیلی 23 46 28110 10.22108/amf.2023.137982.1802 FA فرزاد ناصح پور دانشجوی دکتری، گروه حسابداری، واحد نجف آباد، دانشگاه آزاد اسلامی، نجف آباد، ایران مهدی ابزری استاد، گروه حسابداری، واحد نجف آباد، دانشگاه آزاد اسلامی، نجف آباد، ایران احسان کمالی استادیار، گروه حسابداری، واحد نجف آباد، دانشگاه آزاد اسلامی، نجف آباد، ایران Journal Article 2023 06 09 Several empirical studies have tested the relationship between information asymmetry and the cost of equity capital and have reported conflicting results. Some studies evaluate this relationship as positive, some as negative, and some as insignificant. The discovery of divergence factors has an effective role in managing information asymmetry, the cost of equity capital, and shareholder wealth. In this study, this issue is followed by the meta-analysis approach. This meta-analysis was carried out in seven stages. For this meta-analysis, 36 studies published between 1986 and 2022 from journals with an H index at least equal to 1 of SCOPUS were used. The number of samples is 260 tests which were extracted from the mentioned studies. Using CME2 software, divergence test, and one-sample t-test with random effects approach in addition to testing 12 hypotheses, the robustness check of the results was tested based on 18 categories of analysis, of which 15 categories confirmed the robustness. The results showed that information asymmetry affects the cost of equity capital. All dimensions of information asymmetry affect the cost of equity capital, except analysts’ quality and income volatility. In addition, information asymmetry has a positive effect on all dimensions of the cost of equity capital. Keywords: Information Asymmetry, Cost of Capital, Meta-Analysis, Divergence, Effect Size. Introduction The contribution of this study is to discover the reasons for the conflict in empirical studies using meta-analysis. Information asymmetry exposes shareholders to risk and therefore demands higher returns. Companies can reduce the cost of equity capital by reducing information asymmetry. Some theoretical and experimental studies regarding the relationship between information asymmetry and the cost of equity capital have reported this relationship as positive, some negative, and some non-significant. The purpose of this study is to meta-analyze the effect of information asymmetry on the cost of equity capital to clarify the divergence of empirical studies and its reasons. Hypothesis 1 is about the relationship between information asymmetry and the cost of equity capital. To check the robustness, this hypothesis was tested in different conditions. The next eleven hypotheses are related to the influence of the dimensions of the cost of equity capital on information asymmetry and the impact of the dimensions of information asymmetry on the cost of equity capital. Method and Data This meta-analysis was performed in seven stages. In the first stage, as the research problem, the independent variable is information asymmetry and the dependent variable is the cost of equity capital. In the second stage, after determining keywords and databases, 188 empirical studies were downloaded. In the third stage, the studies of the previous stage were screened based on three criteria: 1) the subject of the study should be in accordance with hypothesis 1 of this meta-analysis, 2) the information related to effect size calculation should be reported in the paper, and 3) the study analysis method should be correlational. After the screening, 36 studies published between 1986 and 2022 including 260 tests (the statistical sample of this meta-analysis) were meta-analyzed. In the fourth stage the general data, the data related to effect sizes, and the data for robustness check were extracted. In the fifth stage, the effect size was calculated for each of the samples, and in the sixth stage, the cumulative effect size was calculated for each hypothesis. To test each hypothesis, z-statistic, and a significance level were obtained for each cumulative effect size, which shows the significance of the difference between the cumulative effect size and zero. In the seventh step, the homogeneity of the effect sizes was tested for each hypothesis. For hypotheses with heterogeneous/homogeneous effect sizes, the cumulative effect size was calculated with the fixed/random effects model. Finally, in the eighth stage, the divergence reasons were explored. Findings The results related to the first hypothesis test are reported in Table 1. Table (1). The results of hypothesis 1; The effect of information asymmetry on the cost of equity capital Model Cumulative effect size One-sample t-test Homogeneity test Z statistic P-value Q statistic P-value Fixed effects 0.004 17.08 0.000 6373 0.000 Random effects 0.021 12.58 0.000 In the test of all hypotheses, the random effects model was used to calculate the cumulative effect size. In hypothesis 1, at the 1% significance level, the null hypothesis of the test is rejected, which means that the cumulative effect size is significantly different from zero. Hypothesis 1 is robust in most of the robustness tests. The test results of hypotheses 2 to 9 are reported in Table 2. Table (2) Test Results of Sub-hypotheses (Dependent variable of the cost of equity capital) Independent variable Cumulative effect size One-sample t-test Homogeneity test Z statistic P-value Q statistic P-value Analysts` quality 0.043 1.555 0.120 22.246 0.000 Disclosure 0.017** 1.833 0.067 177.720 0.000 Accruals 0.007*** 2.826 0.004 7720.056 0.000 Liquidity 0.089*** 4.725 0.000 307.206 0.000 PIN 0.015*** 7.852 0.000 1802.694 0.000 Bid-ask spread 0.020*** 7.362 0.000 1090.235 0.000 Transparency 0.023*** 3.665 0.000 1180.044 0.000 Income volatility 0.087 0.520 0.603 5663.344 0.000 According to the results in Table 2, the null hypothesis is rejected in all hypotheses except for the independent variables of analysts’ quality and income volatility, and the common effect size is significantly different from zero; that is, apart from the quality of analysts and the income volatility, other independent variables have a significant effect on the cost of equity capital. The test results of hypotheses 10 to 12 are reported in Table 3. Table 3. The results of the Sub-hypotheses test (Independent variable of information asymmetry) Dependent variable Cumulative effect size One-sample t-test Homogeneity test Z statistic P-value Q statistic P-value CAPM required return 0.07*** 9.138 0.000 2994.169 0.000 Implied equity cost of capital 0.020*** 2.717 0.007 756.205 0.000 Historical return 0.008*** 5.792 0.000 1979.782 0.000 According to the results in Table 3, information asymmetry has a significant and positive effect on all three dimensions of the cost of equity capital (CAPM expected return, implied cost of capital, and historical return). Conclusion and discussion The cost of equity capital is particularly important because of its role in shareholder wealth. For this reason, managers try to reduce it as much as possible. One of the ways to reduce capital cost is to reduce information asymmetry. The breadth of literature indicates conflicting results regarding the relationship between information asymmetry and the cost of equity capital. The general relationship between the cost of equity capital and information asymmetry is positive and significant. In other words, the less information is transferred to the market (that is, the difference of information between managers and the market or the information difference between two shareholders), the risk causes the market to increase the discount rate used in stock valuation and the intrinsic value, and finally, the shareholder's wealth will decrease below the optimal value. To check the robustness of hypothesis 1, this hypothesis was tested in different conditions of number of observations, length of period, presence or absence of control variable, publication year, and H index in different studies and it was found that the change in these conditions does not affect the results of the meta-anlaysis and the result of hypothesis 1 is robust. According to past empirical studies, different criteria for measuring information asymmetry and the cost of equity capital are the reasons for the conflicting results. In the test of these relationships, the results showed that except for the analysts’ quality and income volatility, other dimensions of information asymmetry have a positive effect on the cost of equity capital, and information asymmetry has a significant and positive effect on various dimensions of the cost of equity capital. This study is limited to the publication years 1986 to 2022. The dimensions of information asymmetry and the cost of equity capital are limited to the indicators that have been used in previous empirical studies. Future authors are suggested to test the results of this study with an experimental approach, to analyze the reason for the lack of influence of analysts’ quality and income volatility on the cost of equity capital, and the reason for the non-significant relationship between the cost of equity capital and information asymmetry in the years 1981 to 2000, and finally compare the results of this studt in developing and developed countries. اهداف: مطالعات تجربی متعددی رابطۀ عدم تقارن اطلاعاتی و هزینۀ سرمایۀ سهام را آزموده‌ و نتایج متناقضی گزارش کرده‌اند. برخی مطالعات این رابطه را مثبت، برخی منفی و برخی آن را غیرمعنی‌دار ارزیابی می‌کنند. کشف عوامل واگرایی جایگاه مؤثری در مدیریت عدم تقارن اطلاعاتی، هزینۀ سرمایۀ سهام و ثروت سهام‌دار دارد. در این پژوهش این موضوع بارویکرد فراتحلیل دنبال می‌شود. روش: فراتحلیل این پژوهش در هفت مرحله اجرا شد. برای این فراتحلیل 36 مطالعۀ منتشرشده بین سال‌های 1986 تا 2022 از نشریات با شاخص H حداقل برابر 1 پایگاه اسکوپوس استفاده شد. تعداد نمونۀ پژوهش 260 آزمون است که از مطالعات مذکور استخراج شده ‌است. با استفاده از نرم‌افزار سی ام ای 2 و آزمون‌های میانگین تک‌نمونه با رویکرد اثرات تصادفی و آزمون واگرایی علاوه‌بر آزمون 12 فرضیۀ نیرومندی نتایج براساس 18 طبقه تحلیل و 15 طبقۀ آن تأیید شد. نتایج: نتایج نشان داد عدم تقارن اطلاعاتی بر هزینۀ سرمایۀ سهام تأثیر دارد. به‌جز متغیرهای کیفیت تحلیل‌گران و نوسان درآمد، همۀ ابعاد عدم تقارن اطلاعاتی بر هزینۀ سرمایۀ سهام تأثیر دارند. به‌علاوه عدم تقارن اطلاعاتی بر همۀ ابعاد هزینۀ سرمایۀ سهام تأثیر مثبت دارد.

https://amf.ui.ac.ir/article_28110_5a4fdacccdc499ce224075b559857e7d.pdf

دانشگاه اصفهان مدیریت دارایی و تامین مالی 2383-1189 11 3 2023 09 23 Supply Chain Agility as a Strategic Asset and Its Effect on Financial Performance with the Moderating Role of Industry Type: A Meta-Analysis Study چابکی زنجیره تأمین به‌عنوان یک دارایی راهبردی و تأثیر آن بر عملکرد مالی با نقش تعدیل‌گری نوع صنعت : یک مطالعه‌ی فراتحلیل 47 68 27968 10.22108/amf.2023.138122.1805 FA الله یار بیگی فیروزی دانشجوی دکتری، گروه مدیریت بازرگانی، دانشکدۀ علوم اجتماعی، دانشگاه محقق اردبیلی، اردبیل، ایران محمد باشکوه دانشیار، گروه مدیریت بازرگانی، دانشکدۀ علوم اجتماعی، دانشگاه محقق اردبیلی، اردبیل، ایران ناصر سیف اللهی استاد، گروه مدیریت بازرگانی، دانشکدۀ علوم اجتماعی، دانشگاه محقق اردبیلی، اردبیل، ایران قاسم زارعی دانشیار، گروه مدیریت بازرگانی، دانشکدۀ علوم اجتماعی، دانشگاه محقق اردبیلی، اردبیل، ایران Journal Article 2023 06 19 Since the emergence of the concept of supply chain agility as the primary management asset for gaining a competitive edge in the dynamic and uncertain business environment, extensive studies have been conducted in this area. A significant portion of this studies has focused on the impact of supply chain agility on financial performance. Analysis of empirical studies reveals that the influence of a strategic asset like supply chain agility is varied across different studies, often yielding contradictory results. Therefore, it is imperative to aggregate and compare the findings of experimental studies using a meta-analysis approach. Consequently, the current research was undertaken to investigate the impact of supply chain agility on financial performance, employing a meta-analysis approach and examining the moderating role of industry type. In this study, 18 final studies were identified in accordance with the PRISMA protocol and their data was inputted into the CMA2 software. The results of the meta-analysis demonstrated that supply chain agility does indeed affect financial performance. Furthermore, the analysis of moderator variables revealed that supply chain agility has a more pronounced effect on financial performance in single industries. Keywords: Supply Chain Agility, Financial Performance, Meta-Analysis, CMA2 Software Introduction In today's business landscape, companies are encountering significant upheavals driven by evolving customer demands and the advent of new technologies. The accelerated product life cycles, swift obsolescence of existing industry technologies, and complex customer-company relationships characterize these volatile environmental conditions. In this fiercely competitive setting, companies that can swiftly and adeptly respond to these environmental disruptions are better positioned to endure in the competitive arena and capture market share. However, the ability of companies to respond to environmental changes alone does not ensure survival or confer a competitive advantage in a turbulent environment; they also require agility throughout their supply chain. Supply chain agility is regarded as an intangible asset. To attain agility, companies must rapidly adapt their supply chain strategies and operations to effectively and promptly address market fluctuations and associated uncertainties. Numerous studies have explored the impact of supply chain agility on financial performance, introduced diverse indicators to measure financial performance, and at times arrived at conflicting conclusions. The extensive array of studies, the diverse financial performance indicators utilized, and the contradictory findings across different industries underscore the need for a meta-analysis study. Consequently, the present study was undertaken to investigate the influence of supply chain agility on financial performance, considering the moderating role of industry type. Materials and Methods This study was undertaken with the objective of conducting a systematic review via meta-analysis to explore the impact of supply chain agility assets on financial performance. To achieve this, the PRISMA protocol was employed to identify high-quality studies, ensuring that the endpoint of the studies included in this analysis was 2023, thereby addressing existing discrepancies. Following a systematic search for relevant studies, a total of 18 studies met the criteria for inclusion in the final meta-analysis dataset. The necessary information for each study, including the authors' names, publication year, sample size, research methodology, country of origin, industry type, performance outcome measures, and relevant statistics, was extracted. Findings In this section, the results of the research hypotheses were analyzed. To this end, the degree of homogeneity or heterogeneity among the research studies and the type of analysis model (fixed or random) were determined. The research findings indicated that the heterogeneity among the studies did not support the research hypothesis and the level of heterogeneity was lower than the average. Consequently, owing to the homogeneity of the research hypothesis studies, the model of fixed effects was employed to assess the hypotheses and present the effect coefficients. The test of the research hypothesis using the mentioned model revealed that the impact coefficient of supply chain agility on financial performance was 0.384, which was confirmed at a significance level of 99%. Discussion & Conclusion The meta-analysis of previous studies revealed the positive impact of supply chain agility on financial performance. In today's fiercely competitive markets, few advantages endure over extended periods. Given the rapid pace of technological advancements and the escalating trend of globalization, current advantages quickly become obsolete, necessitating a continuous quest for new forms of advantage through ongoing adaptation. The findings of this study demonstrated that supply chain agility empowered companies to effectively and promptly address such uncertainties. The meta-analysis results also indicated that the variable of "type of industry" moderated the influence of supply chain agility on financial performance. Notably, companies operating within specific industries exhibited a higher level of supply chain agility. In light of this outcome, it could be inferred that the coordination and collaboration among companies operating within a specific supply chain and specializing in an industry enabled them to better comprehend and anticipate the changes and developments within their market. از زمان معرفی مفهوم چابکی زنجیره تأمین به‌عنوان یگانه دارایی مدیریت در دستیابی به مزیت رقابتی در محیط متغیر و ناپایدار کسب‌وکارها، پژوهش‌های زیادی پیرامون آن انجام گرفته است. بخش گسترده‌ای از پژوهش‌های این حوزه بر تأثیر چابکی زنجیره تأمین بر عملکرد مالی متمرکز شده است. بررسی مطالعات تجربی نشان‌دهندۀ آن است که تأثیر یک دارایی راهبردی نظیر چابکی زنجیره تأمین در پژوهش‌های مختلف پراکنده بوده است و در بسیاری از موارد نتایج متناقضی دارند. در این راستا ضروری است که نتایج مطالعات تجربی با استفاده از رویکرد فراتحلیل، تجمیع و با هم مقایسه شود؛ بنابراین پژوهش حاضر با هدف مطالعۀ تأثیر چابکی زنجیره تأمین بر عملکرد مالی با استفاده از رویکرد فراتحلیل: نقش تعدیل‌گری نوع صنعت انجام گرفت. در این مطالعه تعداد 18 مطالعۀ نهایی مطابق با پروتکل پریزما شناسایی و اطلاعات آن وارد نرم‌افزار CMA2 شد. نتایج فراتحلیل نشان‌دهندۀ آن بود که چابکی زنجیره تأمین بر عملکرد مالی تأثیر می‌گذارد. تحلیل متغیر تعدیل‌گر نشان داد که چابکی زنجیره تأمین در صنایع منحصربه‌فرد اثر قوی‌تری بر عملکرد مالی دارد.

https://amf.ui.ac.ir/article_27968_e2c89b54933a2bf60799cc99a566a30a.pdf

دانشگاه اصفهان مدیریت دارایی و تامین مالی 2383-1189 11 3 2023 09 23 Application of recommendation systems in the development of Robo Advisors: A Bibliometrics Method کاربرد سامانه‌های توصیه‌کننده در تکوین ربات‌های هوشمند مالی: رویکرد نگاشت دانش 69 94 27921 10.22108/amf.2023.138681.1812 FA فاطمه زارعی استادیار گروه مدیریت، دانشکده علوم انسانی، دانشگاه میبد، میبد، ایران مرضیه نوراحمدی دکتری، گروه حسابداری و مالی، دانشکده اقتصاد، مدیریت و حسابداری، دانشگاه یزد، یزد، ایران حجت الله صادقی استادیار، گروه حسابداری و مالی، دانشکده اقتصاد، مدیریت و حسابداری، دانشگاه یزد، یزد، ایران 0000-0001-5852-4198 Journal Article 2023 08 08 Recognizing customers` requests and offering them personal investment suggestions is an essential aspect of a useful and effective consulting strategy. Many households trust financial advisors for investment guidance. Intelligent data analysis is one of the fields of artificial intelligence that solves the problem of learning automated systems without an explicit program. Financial companies have found that they need to adapt quickly to the environment and use automated systems to save money on the cost and accuracy of financial advice to investors. In recent years, a type of technology-based counseling has been introduced as an alternative to Robo Advisors. Robo Advisors is a financial advisor who can assist through machine learning algorithms to automatically analyze the financial product risk level and provide portfolio advice. Robo Advisors are digital platforms that offer algorithm-based and automated financial planning services such as investing. In this study, a systematic review of the empirical studies done on Robo Advisors is given and at the end, a proposed framework for designing Robo Advisors is presented. Keywords: Recommender Systems, Robo Advisors, Consulting, Wealth Management, Bibliometrics Method Introduction The objective of this study is to understand customers` requests and provide personalized investment recommendations to them, which is an essential component of an influential advisory strategy. Families and investors trust financial advisors for guidance in the field of investment. In the modern world, to leverage artificial intelligence data, financial companies must adapt to a compatible environment and provide financial recommendations more accurately and efficiently through their automated systems. Recently, a technology-based alternative form of consultation called "robo-advisory" has emerged. Robo-advisory is a financial recommendation system that analyzes the risk levels of financial products and offers recommended stock portfolios through machine learning algorithms. These intelligent digital platforms provide financial planning and investment services based on algorithms and do so automatically. Methodology This study employs A Bibliometrics Method to investigate studies conducted in the field of intelligent robots, providing an overview of robo-advisory research over the past decade. The Bibliometrics Method is a powerful tool in systematic reviews and scientific data analysis, assisting authors in receiving quantitative feedback on their studies. It automatically collects bibliometric and scientometric data from various sources and analyzes them. By using bibliometrics, authors can obtain important information such as the number of papers related to the topic, citation counts, references, collaborative network diagrams, and academic growth over time. The results are derived from data from sources like Scopus, WoS, and are subject to analysis. The main aim of this study is to utilize Bibliometrics Method tools and highlight various indicators currently used in the literature. In this study, the Bibliometrics Method is employed systematically to investigate empirical studies conducted in the field of intelligent robots. Additionally, this study identifies and categorises the most relevant studies in this domain based on articles, authors, journals, institutions, and countries. Results Robo-advisors hold significant importance in the financial sector, as these systems possess the capability to analyze data accurately and logically. They assist individuals in making better, information-based financial decisions. In other words, robo-advisors are powerful tools for enhancing the efficiency and practicality of wealth management and investment. As a final outcome, a proposed framework for designing intelligent robots in Iran is presented. This research can help enhance the knowledge of researchers regarding research trends and the importance of these issues. The Bibliometrics method, by providing precise and quantitative information, aids authors in improving the quality of their stdies, analyzing their impact, and selecting the best solutions in scientific writing. اهداف: شناخت مشتریان و ارائۀ پیشنهادهای سرمایه‌گذاری شخصی به آنها جنبه‌ای ضروری از یک استراتژی مشورتی سودمند و مؤثر است. بسیاری از خانوارها برای راهنمایی سرمایه‌گذاری به مشاوران مالی اعتماد می‌کنند. تجزیه‌‌و‌تحلیل داده‌های هوشمند یکی از زمینه‌های هوش مصنوعی است که مسئلۀ یادگیری سیستم‌های اتوماتیک را بدون برنامۀ صریح حل می‌کند. شرکت‌های مالی دریافته‌اند که باید خودشان را به‌سرعت با محیط سازگار و با استفاده از سیستم‌های خودکار در هزینه و دقت توصیه‌های مالی به سرمایه‌گذاران صرفه‌جویی کنند. در سال‌های اخیر نوعی مشاوره مبتنی بر فناوری به‌عنوان روش جایگزین با نام مشاورۀ روبو معرفی ‌شده است. مشاورۀ روبو توصیه‌گری مالی است که از طریق الگوریتم‌های یادگیری ماشینی برای تجزیه‌و‌تحلیل خودکار سطح ریسک محصول مالی و ارائۀ سبد سرمایه‌گذاری پیشنهادی کمک می‌کند. ربات‌های هوشمند، پلتفرم‌های دیجیتالی هستند که خدمات برنامه‌ریزی مالی و سرمایه‌گذاری را مبتنی بر الگوریتم و به‌طور خودکار ارائه می‌دهند. روش: در این پژوهش با استفاده از روش نگاشت دانش به ‌مرور سیستماتیک پژوهش‌های انجام‌شده درخصوص ربات‌های هوشمند توجه ‌شده است. سپس مرتبط‌ترین پژوهش‌ها در این زمینه شناسایی و طبقه‌بندی آنها براساس مقالات، نویسندگان، مجلات، مؤسسات و کشورها انجام شده است. نتایج: در انتها چارچوبی به‌منظور طراحی ربات‌های هوشمند در ایران پیشنهاد شده است. این پژوهش دیدی کلی به پژوهشگران درخصوص‌ روند پژوهش‌های انجام‌شده و اهمیت موضوع می‌دهد. روش نگاشت دانش با ارائۀ اطلاعات کمی و دقیق، نویسندگان را در بهبود کیفیت مقاله‌ها، تحلیل تأثیر آنها و انتخاب بهترین راهکار در نگارش مقالات علمی یاری می‌کند.

https://amf.ui.ac.ir/article_27921_3fc06c6b377e99db1eed210830cc1647.pdf

دانشگاه اصفهان مدیریت دارایی و تامین مالی 2383-1189 11 3 2023 09 23 The Role of Corporate Governance in the Relation between Tax Avoidance and Managerial Empire Building نقش راهبری شرکتی در رابطۀ بین اجتناب مالیاتی و تشکیل امپراتوری توسط مدیران 95 112 28120 10.22108/amf.2024.139307.1829 FA محمد مصطفائی کارشناس ارشد، گروه حسابداری، دانشکدۀ مدیریت و اقتصاد، دانشگاه تربیت مدرس، تهران، ایران جواد رضازاده دانشیار، گروه حسابداری، دانشکدۀ مدیریت و اقتصاد، دانشگاه تربیت مدرس، تهران، ایران سحر سپاسی دانشیار، گروه حسابداری، دانشکدۀ مدیریت و اقتصاد، دانشگاه تربیت مدرس، تهران، ایران محمد امری اسرمی استادیار، گروه حسابداری، دانشکده اقتصاد، مدیریت، و علوم اداری، دانشگاه سمنان، سمنان، ایران. Journal Article 2023 10 01 The aim of this study was to explore the impact of corporate governance on the link between tax avoidance and managerial empire building. According to the theory of managers' personal considerations, managers may not always prioritize decisions that benefit shareholders, but rather focus on maximizing their own interests. The existing literature suggests that managerial aspirations for power can be heightened through corporate tax avoidance activities. Tax avoidance and corporate governance are identified as influential factors in the formation of managerial empires. To test the hypotheses, a sample of 119 companies listed on the Tehran Stock Exchange between 2015 and 2021 was selected. A multivariable regression model was employed in this study using the composite data method. The findings indicated that tax avoidance did not significantly contribute to the formation of managerial empires and corporate governance did not mediate the impact of tax avoidance on managerial empire building. Consequently, managers may refrain from tax avoidance and pursue alternative strategies for power acquisition in order to avoid negative perceptions. It is also noted that corporate governance guidelines were not fully implemented in the companies under study. Keywords: Managerial Empire Building, Tax Avoidance, Corporate Governance. Introduction Enhancing available funds through tax avoidance can either generate wealth for shareholders or exacerbate agency issues (Hanlon & Heitzman, 2010). By avoiding taxes, the company retains more income, thereby potentially increasing stock value (Wilson, 2009; Shams et al., 2022). Tax strategies resemble investment decisions that generate economic resources for the company through tax avoidance (Francis et al., 2014). However, high levels of tax avoidance can prompt managers to undertake costly activities to conceal tax avoidance, diminishing financial statement transparency and leading to opportunistic behavior (Desai & Dharmapala, 2007). Separation of management from ownership results in conflicting interests and representation issues with different stakeholder groups seeking to maximize their conflicting interests. Corporate governance mechanisms are designed to reconcile these conflicting interests (Mashayekhi & Seyyedi, 2015). Consequently, companies are motivated to establish and uphold corporate governance mechanisms to minimize costs. This study aimed to investigate whether managers employing tax avoidance strategies allocate company resources to build their business empires and the role corporate governance mechanisms play in either facilitating or impeding this process. Materials & Methods To test the hypotheses, a sample of 119 companies listed on the Tehran Stock Exchange between 2016 and 2021 was selected. The panel data model with fixed effects was deemed suitable for the research models based on Chow and Hausman tests and panel regression models with Generalized Least Squares (GLS) were employed. Research Findings The results indicated that tax avoidance did not have a significant relationship with the formation of managers' empires. Consequently, the managers might refrain from tax avoidance or opt for alternative strategies for empire building in order to avoid negative perceptions. Furthermore, corporate governance was found to have no impact on the relationship between tax avoidance and empire building by the managers. It could not be concluded that corporate governance mechanisms mitigated the impact of tax avoidance on the managers' empire building. Conversely, weaknesses in corporate governance increased the likelihood of tax avoidance and the formation of the managers' empires. In other words, in companies with weak governance and inadequate supervisory mechanisms, the executives wielded greater power and engaged in more tax avoidance to build empires. Discussion of Results & Conclusion Managers are sufficiently incentivized to utilize company resources for their own commercial gain, aiming to fulfill their desires for higher rewards and attainment of position, power, and prestige, essentially building a managerial empire. This study examined the influence of corporate governance on the relationship between tax avoidance and empire building by managers. According to the findings, the managers did not resort to tax avoidance as a means to build their empires. This outcome could be attributed to the circumstances surrounding the companies; tax avoidance measures elicited a negative response from the market and other stakeholders toward company managers, tarnishing their reputation. Consequently, managers refrained from tax avoidance and pursued alternative strategies for power acquisition in order to avert this negative perception. Furthermore, the research indicated that corporate governance did not impact the adoption of a tax avoidance strategy for empire building by managers. Therefore, it could not be concluded that corporate governance mechanisms mitigated the influence of tax avoidance on the construction of managers' empires. Conversely, deficiencies in corporate governance increased the likelihood of tax avoidance and establishment of the managers' empires. In other words, in companies with weak governance and inadequate supervisory mechanisms, the executives wielded greater power and engaged in more tax avoidance to build empires. One possible reason for rejecting this hypothesis could be related to CEO-related criteria where the interests of the CEO might not align with those of the shareholders. Instead of effectively monitoring tax avoidance behaviors, they might align with the executives and seek to build empires and increase their own interests. اهداف: براساس نظریۀ نمایندگی، مدیران لزوما تصمیماتی نمی‌گیرند که به بهترین نتیجه برای سهامداران منجر شود، بلکه آنها گرایش به حداکثر رساندن منافع خویش دارند. قدرت‌طلبی مدیریتی از طریق فعالیت‌های اجتناب مالیاتی شرکت‌ها تشدید می‌شود. از عوامل مؤثر بر ایجاد امپراتوری مدیریتی، اجتناب مالیاتی و راهبری شرکتی است. این پژوهش نقش راهبری شرکتی را در رابطۀ بین اجتناب مالیاتی با تشکیل امپراتوری توسط مدیران بررسی کرده است. روش: به‌منظور آزمون فرضیه‌های‌ پژوهش با استفاده از روش حذف سیستماتیک، نمونه‌ای متشکل از 119 شرکت از بین شرکت‌های پذیرفته‌شده در بورس اوراق بهادار تهران طی سال‌های 1395 تا 1400 انتخاب شده است. به‌علاوه، الگوهای رگرسیونی چند متغیره به روش داده‌های ترکیبی به کار برده ‌شد. نتایج: نتایج نشان‌دهندۀ آن است که اجتناب مالیاتی با تشکیل امپراتوری توسط مدیران رابطۀ معناداری ندارد و راهبری شرکتی در میزان اثرگذاری اجتناب مالیاتی بر تشکیل امپراتوری توسط مدیران نقشی ندارد؛ بنابراین مدیران برای ممانعت از نگرش منفی نسبت به آنها دست به اجتناب مالیاتی نمی‌زنند یا اینکه سیاست‌های دیگری را برای قدرت‌طلبی خود برمی‌گزینند.

https://amf.ui.ac.ir/article_28120_4d8fb4960044545676381c31b211430f.pdf

دانشگاه اصفهان مدیریت دارایی و تامین مالی 2383-1189 11 3 2023 09 23 A Novel Approach to Predicting Financial Distress by Using Financial Network-Based Information and the Integrated Method of Gradient Boosting Decision Tree رویکردی نوین در پیشبینی درماندگی مالی با به‌کارگیری اطلاعات مبتنی‌بر شبکۀ مالی و روش ترکیبی درخت تصمیم تقویت گرادیان 113 140 27821 10.22108/amf.2023.138909.1818 FA عزت اله عباسیان دانشیار، گروه مهندسی مالی، دانشکده حسابداری و علوم مالی، دانشگاه تهران، تهران، ایران کاوه شهرکی دانشجوی دکترا، گروه مدیریت مالی و بیمه، پردیس البرز، دانشگاه تهران، تهران، ایران سعید فلاح پور دانشیار، گروه مدیریت مالی، دانشکده مدیریت، دانشگاه تهران، تهران، ایران علی نمکی استادیار، گروه مدیریت مالی، دانشکده مدیریت، دانشگاه تهران، تهران، ایران 0000-0003-4167-6472 Journal Article 2023 08 26 This study aimed to evaluate the performance of the gradient boosting decision tree model, the parameters of which were optimized with the improved Gray Wolf Algorithm (GWO) by adding financial network-related variables via the selected models of predicting financial distress. The proposed model of this study was implemented on the data of 123 manufacturing companies admitted to the Tehran Stock Exchange and Iran Fara Bourse Co. (IFB) from 2014 to 2021. Initially, the financial network was formed and then, the financial distress of companies was predicted by integrating the network-based variables with financial ratios and using a gradient boosting decision tree model. The model of the gradient boosting decision tree had better performance in terms of precision and Type I error by adding Financial Network Indicators (FNI) compared to the two models of K-Nearest Neighbor (KNN) and Logistic Regression (LR). Companies with betweenness centrality and high degree centrality were found to be less prone to financial distress and vice versa. This is the first study to predict financial distress by using financial network-related variables integrated with financial ratio variables through the novel gradient boosting decision tree method, the parameters of which were optimized with the improved GWO. Keywords: Financial Distress, Financial Network, Gradient Boosting Decision Tree, Improved Gray Wolf Algorithm (GWO), Centrality Criteria. Introduction Previous studies on predicting financial distress have mainly adopted financial variables in financial statements as explanatory variables, while ignoring some other potentially useful information, such as financial network-related information. Disregarding such information for predicting financial distress is one of the significant gaps in the literature. Therefore, the present study aimed to evaluate the performance of the gradient boosting decision tree model, the parameters of which were optimized with the improved Gray Wolf Algorithm (GWO), along with the financial network-related variables, which showed another gap in the literature, and then compare its findings with the two recently widely used models of K-Nearest Neighbor (KNN) and Logistic Regression (LR). The following questions were posed in the present study. Can the integrated IGWO-GBDT model provide a better prediction of financial distress compared to the widely selected models of LR and KNN? Does the inclusion of financial network variables improve the performance of the integrated IGWO-GBDT model for predicting financial distress? Does the inclusion of financial network variables improve the performance of the widely used models of LR and KNN for predicting financial distress? Materials & Methods The sample of this study included all the manufacturing companies listed in the Tehran Stock Exchange and Iran Fara Bourse Co. (IFB) from 2014 to 2021, of which 123 companies were selected. The information of the last 30 trading days in each fiscal year was used to form the financial network variables. Finally, 8 financial variables were selected based on those adopted by Ebrahimi Sarvolia et al. (2018), including current ratio, net ratio of working capital to total asset, ratio of current asset to total asset, profit margin, return on assets, return on equity, book to market ratio, and size of company. Furthermore, the total debt ratio, a widely used variable in previous studies, was added to the financial variables. Regarding the financial network variables, the 4 variables of degree centrality, betweenness centrality, eigenvector centrality, and closeness centrality were selected similar to those selected by Montasheri and Sadeqi (2020) and Liu et al. (2019). More than one criterion was applied to measure financial distress in this study. Any companies that met at least one of the four mentioned criteria were considered distressed in that year. These criteria were subject to Article 141 of the Commercial Law, suffering losses for 3 consecutive years (Damoori & Hozhabrie, 2019), subject to Article 412 of the Commercial Law, referring to a debt ratio higher than 1 (Poorheidari & Koopaei, 2011), and had negative equity. Findings The findings indicated that the mean degree of centrality for companies with financial health was 0.203, while it was 0.193 for the distressed companies. Betweenness centrality was 0.007 for the distressed and non-distressed companies. Regarding eigenvector centrality, the means of healthy companies and those with financial distress were 0.083 and 0.104, respectively. Also, the values of closeness centrality were 0.525 and 0.496 for the mentioned companies, respectively. Table 5 shows that all the 3 models have performed quite well in terms of prediction of the class of healthy companies, while the error was below 10%. Still, the distinguished performances of these models were revealed when they could accurately and appropriately predict the class of financially distressed companies, which included only 12% of observations. The type I errors in the LR and KNN models were respectively 20 and 40%, bearing huge costs. In other words, these two models mistakenly predicted distressed companies as healthy ones in 20 and 40% of cases. However, the type I error of the proposed research model was only 5%, indicating high accuracy of the model. Table 5. Comparison of the performances of the 3 studied models with and without financial network variables FN-GBDT GBDT FN-KNN KNN FN-LR LR 0.982 0.96 0.895 0.906 0.907 0.901 Accuracy 0.05 0.11 0.40 0.31 0.20 0.24 Error 1 0.013 0.033 0.065 0.011 0.078 0.086 Error 2 0.933 0.989 0.907 0.916 0.959 0.932 AUC 0.968 0.927 0.748 0.826 0.858 0.833 G-mean Discussion and Conclusion (1) Financial network variables can be employed to explore useful information in the financial network and improve the prediction performances of classifiers. (2) According to the definition of centrality, companies with high centrality, especially betweenness centrality and degree centrality, are less prone to financial distress and vice versa. (3) The improved GWO is a practical method for selecting the parameters of the gradient boosting model. (4) The gradient boosting decision tree model is highly efficient when the frequency ratio of the samples of each class is significantly different from those of other classes. The experimental findings revealed that the proposed model outperformed the other two models in predicting financial distress. This was confirmed by the adopted evaluation criteria. هدف: این پژوهش بر آن است که با اضافه‌کردن متغیرهای مربوط‌به شبکۀ مالی، عملکرد الگوی درخت تصمیم تقویت گرادیان را که شاخص‌هایش با الگوریتم بهبودیافتۀ گرگ خاکستری بهینه شده است، با الگو‌های منتخب در حوزۀ پیش‌بینی درماندگی مالی ارزیابی کند. روش: الگوی پیشنهادی این پژوهش روی داده‌های 123 شرکت تولیدی پذیرفته‌شده در بورس و فرابورس ایران در بازۀ زمانی 2015 تا 2021 اجرا‌ شد. ابتدا شبکۀ مالی تشکیل شد و سپس با ترکیب متغیرهای مبتنی‌بر شبکه با برخی نسبت‌های مالی و با استفاده از الگوی درخت تصمیم تقویت گرادیان که شاخص‌های آن با الگوریتم بهبودیافتۀ گرگ خاکستری بهینه شده است، درماندگی مالی شرکت‌ها پیش‌بینی شد. نتایج: الگوی درخت تصمیم تقویت گرادیان با اضافه‌شدن متغیرهای مربوط‌به شبکۀ مالی هم ازنظر دقت و هم ازنظر خطای نوع یک عملکرد بهتری در مقایسه با دو الگوی k نزدیک‌ترین همسایه و رگرسیون لجستیک از خود نشان داد. شرکت‌های با مرکزیت بینابینی و مرکزیت درجۀ زیاد، کمتر مستعد قرارگرفتن در شرایط درماندگی مالی هستند و برعکس. در شرایطی که نسبت فراوانی نمونه‌های هر طبقه از طبقات دیگر بسیار متفاوت باشد، استفاده از روش درخت تصمیم تقویت گرادیان بسیار کارآمد خواهد بود. نوآوری: برای نخستین‌بار متغیرهای مربوط‌به شبکۀ مالی با نسبت‌های مالی، ترکیب شد و ازطریق روش نوین درخت تصمیم تقویت گرادیان که شاخص‌هایش با الگوریتم گرگ خاکستری بهبودیافته بهینه شده، درماندگی مالی پیش‌بینی شد.

https://amf.ui.ac.ir/article_27821_714c89e909f132bd01f983e676f8d9df.pdf