University of Isfahan Journal of Asset Management and Financing 2383-1189 12 4 2024 12 21 47 47 29002 10.22108/amf.2024.29002 FA Journal Article 2024 11 16 https://amf.ui.ac.ir/article_29002_99942ee8a83fec9351adaba1376de4f9.pdf

University of Isfahan Journal of Asset Management and Financing 2383-1189 12 4 2024 12 21 Examining the Long-Run and Short-Run Effects of Technical and Financial Factors on Bitcoin Blockchain Network Transaction Fees Examining the Long-Run and Short-Run Effects of Technical and Financial Factors on Bitcoin Blockchain Network Transaction Fees 1 18 28488 10.22108/amf.2024.141264.1877 FA Amin Rostami Assistant professor, Department of Accounting, Faculty of Administrative Sciences and Economics, University of Isfahan, Isfahan, Iran Mahdi Safaei M. A. Student of Accounting, Faculty of Administrative Sciences and Economics, Isfahan University, Isfahan, Iran Journal Article 2024 04 27 In recent years, Bitcoin has garnered increasing public and media attention, as well as investment in this field. This cryptocurrency currently has the highest market value among existing virtual currencies that can operate in a decentralized manner based on defined incentives. These incentives include a fixed mining reward for each block and a variable reward resulting from transaction fees in the blockchain network. The transaction fee in the Bitcoin network is unstable and is determined in real-time. Due to the reduction of the fixed mining reward, the transaction fees have become the primary source of income for miners. This study examined the long-term and short-term effects of technical and financial factors on user behavior in determining Bitcoin transaction fees. The autoregressive distributed lag (ARDL) model was used for this analysis. The dataset spanned from April 10, 2018, to July 24, 2023. The technical factors examined included the average daily block size in bytes, network difficulty, and daily transaction volume. The financial factors included the average daily value of transactions sent to Bitcoin and the average daily Bitcoin price in dollars. The results showed that the technical factor of network difficulty had the greatest long-term impact on transaction processing fees. Additionally, the average daily block size in bytes had a significant long-term impact on transaction fees. However, the Bitcoin price did not have a significant long-term impact on transaction fees. These findings can help users make more informed decisions when setting transaction fees. Additionally, the results can assist miners in adopting better strategies to maximize their earnings. In recent years, Bitcoin has garnered increasing public and media attention, as well as investment in this field. This cryptocurrency currently has the highest market value among existing virtual currencies that can operate in a decentralized manner based on defined incentives. These incentives include a fixed mining reward for each block and a variable reward resulting from transaction fees in the blockchain network. The transaction fee in the Bitcoin network is unstable and is determined in real-time. Due to the reduction of the fixed mining reward, the transaction fees have become the primary source of income for miners. This study examined the long-term and short-term effects of technical and financial factors on user behavior in determining Bitcoin transaction fees. The autoregressive distributed lag (ARDL) model was used for this analysis. The dataset spanned from April 10, 2018, to July 24, 2023. The technical factors examined included the average daily block size in bytes, network difficulty, and daily transaction volume. The financial factors included the average daily value of transactions sent to Bitcoin and the average daily Bitcoin price in dollars. The results showed that the technical factor of network difficulty had the greatest long-term impact on transaction processing fees. Additionally, the average daily block size in bytes had a significant long-term impact on transaction fees. However, the Bitcoin price did not have a significant long-term impact on transaction fees. These findings can help users make more informed decisions when setting transaction fees. Additionally, the results can assist miners in adopting better strategies to maximize their earnings.

https://amf.ui.ac.ir/article_28488_467a9cf39b516fd09cd1cef77cfb5cbd.pdf

University of Isfahan Journal of Asset Management and Financing 2383-1189 12 4 2024 12 21 Analyzing the Influence of Company's Business Strategy and Its Components as a Factor of Information Risk on Excess Stock Returns Analyzing the Influence of Company's Business Strategy and Its Components as a Factor of Information Risk on Excess Stock Returns 19 38 28658 10.22108/amf.2024.141071.1872 FA Alireza Rahrovi Dastjerdi Assistant Professor, Department of Accounting, Faculty of Administrative Sciences and Economics, University of Isfahan, Isfahan, Iran 0000-0001-6874-8398 Daryoosh Forooghi Professor, Department of Accounting, Faculty of Administrative Sciences and Economics, University of Isfahan, Isfahan, Iran 0000-0002-7164-6728 Zahra Moradi M.A. Department of Accounting, Faculty of Administrative Sciences and Economics, University of Isfahan, Isfahan, Iran Journal Article 2024 03 28 This study investigates the impact of a company's business strategy and its underlying components as information risk factors on the excess return of firms listed on the Tehran Stock Exchange (TSE). To address this objective, two hypotheses were formulated. A sample of 236 companies listed on the TSE from 2011 to 2022 was selected and Ordinary Least Squares (OLS) regression was employed to test the hypotheses. The findings indicate that the business strategy as an information risk factor has a significant and positive impact on excess return. Moreover, six out of eight different combinations of business strategy criteria also showed a positive and significant effect on companies' excess returns. This suggested that the components of the business strategy influenced excess stock returns in a similar manner to the overall business strategy. The results implied that investors positively priced business strategy as a risk factor. This study filled a gap in the existing literature by exploring the use of a business strategy index in pricing information risk, contributing to the finance research domain. Keywords: Business Strategy, Pricing, Information Risk, Excess Stock Returns. Introduction In the dynamic capital market environment, understanding the various risk factors that influence investment returns is crucial for investors and stakeholders. One such prominent factor is information risk, which pertains to the uncertainty arising from the quality, accuracy, and comprehensiveness of information available to investors. This uncertainty can significantly impact decision-making processes and market performance. This studey focused on analyzing the influence of a company's business strategy and its underlying components as factors of information risk on excess stock returns. By examining companies listed on the Tehran Stock Exchange (TSE), this study aimed to elucidate how investors perceived business strategies and how these perceptions were reflected in stock market performance. Through this lens, the study sought to contribute to the broader financial literature by integrating the concept of business strategy into the framework of information risk pricing. Exploring the relationship between business strategy, information risk, and excess returns is crucial as it can provide valuable insights for investors, stakeholders, and financial decision-makers. Understanding how the various elements of a company's business strategy are priced by the market can help investors make more informed decisions and enhance their overall investment strategies. Materials & Methods To address the research objectives, two hypotheses were formulated to investigate the relationship between a company's business strategy and its excess stock returns, considering information risk as a key factor. The sample comprised 236 companies listed on the TSE over the period from 2011 to 2022. The study employed the Ordinary Least Squares (OLS) regression technique to analyze the data and test the hypotheses. The business strategy was quantified using a comprehensive index that incorporated various strategic components, enabling a nuanced examination of its impact on stock returns. This approach allowed for a detailed analysis of how the different elements of a company's business strategy were perceived and priced by investors in the market. The methodology involved rigorous statistical analysis to ensure the reliability and validity of the findings, providing a robust basis for drawing meaningful conclusions. The analytical process adhered to established econometric principles and best practices, ensuring the integrity and credibility of the research. By adopting this comprehensive and rigorous approach, the study aimed to contribute to the existing financial literature by elucidating the role of business strategy as an information risk factor and its influence on excess stock returns in the context of the TSE. Findings The empirical analysis revealed that a company's business strategy significantly and positively influenced its excess stock returns, confirming the research hypotheses. Specifically, the overall business strategy emerged as a positive and significant factor in determining excess returns. Further examination of the individual components of the business strategy index showed that six out of eight combinations had a similarly positive and significant effect on excess returns. These findings indicated that not only did the holistic business strategy impact investor perceptions and stock performance, but specific strategic elements also played a crucial role in this relationship. The results suggested that investors appeared to price the business strategy favorably, reflecting its perceived value in the context of information risk. Investors seemed to view a company's business strategy as a vital factor in assessing the quality, accuracy, and comprehensiveness of the available information and consequently determining the appropriate risk-adjusted returns. These findings contribute to the existing financial literature by providing empirical evidence on the role of business strategy as an information risk factor and its impact on excess stock returns. The nuanced understanding of how specific strategic components influence investor perceptions and market performance can offer valuable insights for corporate decision-makers, investors, and financial analysts. Discussion and Conclusion The study's findings highlighted the critical role of business strategy in the context of information risk and stock market performance. The positive relationship between business strategy and excess stock returns suggested that investors valued strategic clarity and transparency, which could help reduce information asymmetry and associated risks. By decomposing the business strategy into its constituent elements, the study provided granular insights, into which specific aspects of strategy were most influential in determining excess returns. These results had significant implications for both corporate management and investors. For corporate managers, the findings underscored the importance of strategic planning and effective communication in enhancing investor confidence and market performance. By aligning their business strategies with investor expectations and ensuring transparent disclosure of strategic information, companies could positively influence their excess stock returns. From an investor's perspective, understanding the strategic direction of a company could serve as a crucial tool for making informed investment decisions. By incorporating an assessment of a firm's business strategy into its risk-return analysis, investors could potentially gain a more comprehensive understanding of the information risk inherent in their investment decisions. Overall, this study contributed to the financial literature by integrating the concept of business strategy into the analysis of information risk, offering a novel perspective on its impact on excess stock returns. The findings suggested that investors positively price business strategy as a risk factor, reflecting its perceived value in the context of information risk. Future research could further explore this relationship across different markets and economic conditions to generalize the findings and enhance their applicability. Extending the analysis to other geographical contexts and time periods could provide valuable insights into the generalizability and robustness of the observed patterns. This study investigates the impact of a company's business strategy and its underlying components as information risk factors on the excess return of firms listed on the Tehran Stock Exchange (TSE). To address this objective, two hypotheses were formulated. A sample of 236 companies listed on the TSE from 2011 to 2022 was selected and Ordinary Least Squares (OLS) regression was employed to test the hypotheses. The findings indicate that the business strategy as an information risk factor has a significant and positive impact on excess return. Moreover, six out of eight different combinations of business strategy criteria also showed a positive and significant effect on companies' excess returns. This suggested that the components of the business strategy influenced excess stock returns in a similar manner to the overall business strategy. The results implied that investors positively priced business strategy as a risk factor. This study filled a gap in the existing literature by exploring the use of a business strategy index in pricing information risk, contributing to the finance research domain. Keywords: Business Strategy, Pricing, Information Risk, Excess Stock Returns. Introduction In the dynamic capital market environment, understanding the various risk factors that influence investment returns is crucial for investors and stakeholders. One such prominent factor is information risk, which pertains to the uncertainty arising from the quality, accuracy, and comprehensiveness of information available to investors. This uncertainty can significantly impact decision-making processes and market performance. This studey focused on analyzing the influence of a company's business strategy and its underlying components as factors of information risk on excess stock returns. By examining companies listed on the Tehran Stock Exchange (TSE), this study aimed to elucidate how investors perceived business strategies and how these perceptions were reflected in stock market performance. Through this lens, the study sought to contribute to the broader financial literature by integrating the concept of business strategy into the framework of information risk pricing. Exploring the relationship between business strategy, information risk, and excess returns is crucial as it can provide valuable insights for investors, stakeholders, and financial decision-makers. Understanding how the various elements of a company's business strategy are priced by the market can help investors make more informed decisions and enhance their overall investment strategies. Materials & Methods To address the research objectives, two hypotheses were formulated to investigate the relationship between a company's business strategy and its excess stock returns, considering information risk as a key factor. The sample comprised 236 companies listed on the TSE over the period from 2011 to 2022. The study employed the Ordinary Least Squares (OLS) regression technique to analyze the data and test the hypotheses. The business strategy was quantified using a comprehensive index that incorporated various strategic components, enabling a nuanced examination of its impact on stock returns. This approach allowed for a detailed analysis of how the different elements of a company's business strategy were perceived and priced by investors in the market. The methodology involved rigorous statistical analysis to ensure the reliability and validity of the findings, providing a robust basis for drawing meaningful conclusions. The analytical process adhered to established econometric principles and best practices, ensuring the integrity and credibility of the research. By adopting this comprehensive and rigorous approach, the study aimed to contribute to the existing financial literature by elucidating the role of business strategy as an information risk factor and its influence on excess stock returns in the context of the TSE. Findings The empirical analysis revealed that a company's business strategy significantly and positively influenced its excess stock returns, confirming the research hypotheses. Specifically, the overall business strategy emerged as a positive and significant factor in determining excess returns. Further examination of the individual components of the business strategy index showed that six out of eight combinations had a similarly positive and significant effect on excess returns. These findings indicated that not only did the holistic business strategy impact investor perceptions and stock performance, but specific strategic elements also played a crucial role in this relationship. The results suggested that investors appeared to price the business strategy favorably, reflecting its perceived value in the context of information risk. Investors seemed to view a company's business strategy as a vital factor in assessing the quality, accuracy, and comprehensiveness of the available information and consequently determining the appropriate risk-adjusted returns. These findings contribute to the existing financial literature by providing empirical evidence on the role of business strategy as an information risk factor and its impact on excess stock returns. The nuanced understanding of how specific strategic components influence investor perceptions and market performance can offer valuable insights for corporate decision-makers, investors, and financial analysts. Discussion and Conclusion The study's findings highlighted the critical role of business strategy in the context of information risk and stock market performance. The positive relationship between business strategy and excess stock returns suggested that investors valued strategic clarity and transparency, which could help reduce information asymmetry and associated risks. By decomposing the business strategy into its constituent elements, the study provided granular insights, into which specific aspects of strategy were most influential in determining excess returns. These results had significant implications for both corporate management and investors. For corporate managers, the findings underscored the importance of strategic planning and effective communication in enhancing investor confidence and market performance. By aligning their business strategies with investor expectations and ensuring transparent disclosure of strategic information, companies could positively influence their excess stock returns. From an investor's perspective, understanding the strategic direction of a company could serve as a crucial tool for making informed investment decisions. By incorporating an assessment of a firm's business strategy into its risk-return analysis, investors could potentially gain a more comprehensive understanding of the information risk inherent in their investment decisions. Overall, this study contributed to the financial literature by integrating the concept of business strategy into the analysis of information risk, offering a novel perspective on its impact on excess stock returns. The findings suggested that investors positively price business strategy as a risk factor, reflecting its perceived value in the context of information risk. Future research could further explore this relationship across different markets and economic conditions to generalize the findings and enhance their applicability. Extending the analysis to other geographical contexts and time periods could provide valuable insights into the generalizability and robustness of the observed patterns.

https://amf.ui.ac.ir/article_28658_4b7e089cb4a06deed7c4274e7c46a2d1.pdf

University of Isfahan Journal of Asset Management and Financing 2383-1189 12 4 2024 12 21 Impact of COVID-19 on Corporate Cash Holdings and Speed of Adjustment Impact of COVID-19 on Corporate Cash Holdings and Speed of Adjustment 39 60 28619 10.22108/amf.2024.139959.1842 FA Abbas Aflatooni Associate Professor, Department of Accounting, Faculty of Economics and Social Sciences, Bu-Ali Sina University, Hamadan, Iran Mohammad Khatiri Assistant Professor, Department of Accounting, Takestan Branch, Islamic Azad University, Takestan, Iran Farzad Eivani Assistant Professor, Department of Accounting, Faculty of Social Sciences, Razi University, Kermanshah, Iran Journal Article 2023 11 29 Cash management is critical for firm value as both cash surpluses and deficits can diminish value. Consequently, firms aim to maintain optimal cash levels by adjusting their actual cash ratios towards target ratios. Various factors influence cash holdings and the speed of these adjustments. This study examined the impact of the COVID-19 pandemic, which had heightened the precautionary motive for firms to hold cash. The analysis used observations from 159 firms from 2008 to 2022, applying Generalized Least Squares (GLS) regression and the system Generalized Method of Moments (system-GMM) while controlling for industry and year effects. The results indicated that during the COVID-19 period, firms' cash holdings ratios became increased than doubled and the speed of cash ratio adjustment increased by nearly 40% compared to previous years. These findings are consistent with the predictions of pecking order and trade-off theories, extending the existing literature by highlighting the pandemic's role in intensifying firms' financial pressures. The results suggested that the increased cash adjustment speed represented a strategic response to avoid the financial consequences of the COVID-19 crisis. Keywords: Precautionary Motive, Speed of Adjustment, COVID-19, Trade-off Theory, Cash Holding. JEL classification codes: G31, G32 Introduction Cash management is a critical aspect of firm liquidity and performance. The precautionary motive is considered the primary driver for holding cash as it becomes more important when firms face greater cash flow uncertainty or limited access to external financing during crises (Opler et al., 1999; Almeida et al., 2004). Global crises, such as the COVID-19 pandemic, can lead to heightened financing constraints for firms (Zubair et al., 2020). Based on pecking order theory, firms are expected to increase their cash holdings to preserve investment opportunities during such periods of crisis. Additionally, the trade-off theory suggests that the uncertainty induced by global crises may increase adjustment costs, leading to slower cash holdings adjustments. However, the benefits of moving more quickly towards target cash levels could potentially outweigh the higher adjustment costs, resulting in faster cash holdings adjustments (Melgarejo & Stephen, 2023). To investigate the impact of the COVID-19 pandemic on corporate cash holdings and their adjustment dynamics in Iran, this study examined the following hypotheses: H1: Compared to other years, firms held higher cash balances during the COVID-19 pandemic. H2: Compared to other years, the speed of cash holdings adjustments was higher during the COVID-19 pandemic. Materials & Methods This study utilized data from 159 firms (2,226 firm-years) in Iran for the period of 2008-2022. The data were primarily collected from the Rahvard Nowin database and any missing information was supplemented using reports published on the Codal website. For the analysis, the study period was divided into two sub-periods: the pre-COVID-19 period (2008-2018, 1,749 firm-years) and the COVID-19 pandemic period (2019-2021, 477 firm-years). The COVID-19 pandemic was considered to have started in the winter of 2018, affecting the financial reporting of that year, and continued through the end of 2021. To test the research hypotheses, the study employed a two-pronged approach. First, the static models were estimated using the Generalized Least Squares (GLS) estimator to examine the first hypothesis regarding the impact of COVID-19 on firms' cash holdings levels. Second, the dynamic models were estimated using the Blundell and Bond’s (1998) system Generalized Method of Moments (system-GMM) estimator to measure the speed of cash holdings adjustments and test the second hypothesis. To address potential statistical issues, the standard errors of the coefficients in the static models were corrected using cluster-robust standard errors at the firm level. For the dynamic models, the standard errors were corrected using Windmeijer’s approach (2005). Additionally, the study conducted robustness tests by considering the years 2020-2021 (318 firm-years) as the COVID-19 pandemic period and employing the two-stage approach suggested by Orlova and Rao (2018). These additional analyses aimed to ensure the reliability and consistency of the main findings. The data analysis was performed using Stata software and tabular data presentations. Findings The empirical analysis yielded several key findings. First, the positive and statistically significant coefficient of the COVID-19 dummy variable in the static models indicated that, after controlling for the determinants of cash holdings, as well as year and industry fixed effects, firms held a higher ratio of cash to non-cash assets (4.52-percentage point) during the COVID-19 pandemic period compared to the pre-pandemic years. This supported the first hypothesis that firms increased their cash holdings during the COVID-19 crisis. The dynamic model results provided further insights. Prior to the COVID-19 outbreak, the estimated speed of cash holdings adjustment was around 50%, suggesting that firms removed half of the deviation from their target cash ratio over a 12-month period. However, during the COVID-19 pandemic, the speed of adjustment increased to approximately 68.5%, implying that firms removed half of the deviation from their target cash ratio in about 7 months. These findings suggested that the speed of cash holdings adjustments increased by around 40% during the COVID-19 period compared to the pre-pandemic years and this was in line with the second research hypothesis. Overall, the results demonstrated that firms in Iran increased their cash holdings and exhibited faster cash holdings adjustments in response to the heightened uncertainty and financing constraints imposed by the COVID-19 crisis. These findings are consistent with the predictions of the pecking order and trade-off theories, highlighting the importance of precautionary cash management during periods of global economic turmoil. Discussion & Conclusion: The existing literature on the determinants and adjustment dynamics of corporate cash holdings has expanded considerably in recent years. Among the various motivations for holding cash, the precautionary motive has emerged as a key focus of scholarly attention. Theoretical frameworks, such as the trade-off theory, have been instrumental in explaining firms' cash management behaviors. Prior studies have investigated the impacts of firm-level, industry-level, and macroeconomic factors on cash holdings and their adjustment speeds. More recently, researchers have examined the effects of global systemic shocks, such as the COVID-19 pandemic, on corporate cash policies. However, evidence from the context of firms listed on the Tehran Stock Exchange (TSE) has been lacking. The current research helped to fill this gap by investigating the impacts of the COVID-19 crisis on the cash holdings and adjustment speeds of Iranian firms. The findings indicated that during the pandemic period, firms' cash-to-non-cash asset ratios increased by 4.52-percentage points compared to the pre-pandemic years. Moreover, the speed of cash holdings adjustments accelerated by around 40% during the COVID-19 crisis, with firms removing half of the deviation from their target cash ratios in about 7 months compared to 12 months in the pre-pandemic period. These results are consistent with the precautionary motive for holding cash and align with the predictions of the pecking order and trade-off theories. The observed increases in cash holdings and adjustment speeds suggested that Iranian firms adopted more aggressive cash management strategies to navigate the heightened uncertainty and financing constraints imposed by the COVID-19 pandemic. The findings of this study contribute to the growing body of literature on corporate cash policies in the context of global systemic shocks. The insights generated may also have practical implications for financial managers in developing economies, highlighting the importance of dynamic and proactive cash management practices during periods of economic turmoil. Cash management is critical for firm value as both cash surpluses and deficits can diminish value. Consequently, firms aim to maintain optimal cash levels by adjusting their actual cash ratios towards target ratios. Various factors influence cash holdings and the speed of these adjustments. This study examined the impact of the COVID-19 pandemic, which had heightened the precautionary motive for firms to hold cash. The analysis used observations from 159 firms from 2008 to 2022, applying Generalized Least Squares (GLS) regression and the system Generalized Method of Moments (system-GMM) while controlling for industry and year effects. The results indicated that during the COVID-19 period, firms' cash holdings ratios became increased than doubled and the speed of cash ratio adjustment increased by nearly 40% compared to previous years. These findings are consistent with the predictions of pecking order and trade-off theories, extending the existing literature by highlighting the pandemic's role in intensifying firms' financial pressures. The results suggested that the increased cash adjustment speed represented a strategic response to avoid the financial consequences of the COVID-19 crisis. Keywords: Precautionary Motive, Speed of Adjustment, COVID-19, Trade-off Theory, Cash Holding. JEL classification codes: G31, G32 Introduction Cash management is a critical aspect of firm liquidity and performance. The precautionary motive is considered the primary driver for holding cash as it becomes more important when firms face greater cash flow uncertainty or limited access to external financing during crises (Opler et al., 1999; Almeida et al., 2004). Global crises, such as the COVID-19 pandemic, can lead to heightened financing constraints for firms (Zubair et al., 2020). Based on pecking order theory, firms are expected to increase their cash holdings to preserve investment opportunities during such periods of crisis. Additionally, the trade-off theory suggests that the uncertainty induced by global crises may increase adjustment costs, leading to slower cash holdings adjustments. However, the benefits of moving more quickly towards target cash levels could potentially outweigh the higher adjustment costs, resulting in faster cash holdings adjustments (Melgarejo & Stephen, 2023). To investigate the impact of the COVID-19 pandemic on corporate cash holdings and their adjustment dynamics in Iran, this study examined the following hypotheses: H1: Compared to other years, firms held higher cash balances during the COVID-19 pandemic. H2: Compared to other years, the speed of cash holdings adjustments was higher during the COVID-19 pandemic. Materials & Methods This study utilized data from 159 firms (2,226 firm-years) in Iran for the period of 2008-2022. The data were primarily collected from the Rahvard Nowin database and any missing information was supplemented using reports published on the Codal website. For the analysis, the study period was divided into two sub-periods: the pre-COVID-19 period (2008-2018, 1,749 firm-years) and the COVID-19 pandemic period (2019-2021, 477 firm-years). The COVID-19 pandemic was considered to have started in the winter of 2018, affecting the financial reporting of that year, and continued through the end of 2021. To test the research hypotheses, the study employed a two-pronged approach. First, the static models were estimated using the Generalized Least Squares (GLS) estimator to examine the first hypothesis regarding the impact of COVID-19 on firms' cash holdings levels. Second, the dynamic models were estimated using the Blundell and Bond’s (1998) system Generalized Method of Moments (system-GMM) estimator to measure the speed of cash holdings adjustments and test the second hypothesis. To address potential statistical issues, the standard errors of the coefficients in the static models were corrected using cluster-robust standard errors at the firm level. For the dynamic models, the standard errors were corrected using Windmeijer’s approach (2005). Additionally, the study conducted robustness tests by considering the years 2020-2021 (318 firm-years) as the COVID-19 pandemic period and employing the two-stage approach suggested by Orlova and Rao (2018). These additional analyses aimed to ensure the reliability and consistency of the main findings. The data analysis was performed using Stata software and tabular data presentations. Findings The empirical analysis yielded several key findings. First, the positive and statistically significant coefficient of the COVID-19 dummy variable in the static models indicated that, after controlling for the determinants of cash holdings, as well as year and industry fixed effects, firms held a higher ratio of cash to non-cash assets (4.52-percentage point) during the COVID-19 pandemic period compared to the pre-pandemic years. This supported the first hypothesis that firms increased their cash holdings during the COVID-19 crisis. The dynamic model results provided further insights. Prior to the COVID-19 outbreak, the estimated speed of cash holdings adjustment was around 50%, suggesting that firms removed half of the deviation from their target cash ratio over a 12-month period. However, during the COVID-19 pandemic, the speed of adjustment increased to approximately 68.5%, implying that firms removed half of the deviation from their target cash ratio in about 7 months. These findings suggested that the speed of cash holdings adjustments increased by around 40% during the COVID-19 period compared to the pre-pandemic years and this was in line with the second research hypothesis. Overall, the results demonstrated that firms in Iran increased their cash holdings and exhibited faster cash holdings adjustments in response to the heightened uncertainty and financing constraints imposed by the COVID-19 crisis. These findings are consistent with the predictions of the pecking order and trade-off theories, highlighting the importance of precautionary cash management during periods of global economic turmoil. Discussion & Conclusion: The existing literature on the determinants and adjustment dynamics of corporate cash holdings has expanded considerably in recent years. Among the various motivations for holding cash, the precautionary motive has emerged as a key focus of scholarly attention. Theoretical frameworks, such as the trade-off theory, have been instrumental in explaining firms' cash management behaviors. Prior studies have investigated the impacts of firm-level, industry-level, and macroeconomic factors on cash holdings and their adjustment speeds. More recently, researchers have examined the effects of global systemic shocks, such as the COVID-19 pandemic, on corporate cash policies. However, evidence from the context of firms listed on the Tehran Stock Exchange (TSE) has been lacking. The current research helped to fill this gap by investigating the impacts of the COVID-19 crisis on the cash holdings and adjustment speeds of Iranian firms. The findings indicated that during the pandemic period, firms' cash-to-non-cash asset ratios increased by 4.52-percentage points compared to the pre-pandemic years. Moreover, the speed of cash holdings adjustments accelerated by around 40% during the COVID-19 crisis, with firms removing half of the deviation from their target cash ratios in about 7 months compared to 12 months in the pre-pandemic period. These results are consistent with the precautionary motive for holding cash and align with the predictions of the pecking order and trade-off theories. The observed increases in cash holdings and adjustment speeds suggested that Iranian firms adopted more aggressive cash management strategies to navigate the heightened uncertainty and financing constraints imposed by the COVID-19 pandemic. The findings of this study contribute to the growing body of literature on corporate cash policies in the context of global systemic shocks. The insights generated may also have practical implications for financial managers in developing economies, highlighting the importance of dynamic and proactive cash management practices during periods of economic turmoil.

https://amf.ui.ac.ir/article_28619_77f399465a9c61c9d07c87c1a910552b.pdf

University of Isfahan Journal of Asset Management and Financing 2383-1189 12 4 2024 12 21 Effect of Information Genotype on Investors' Inertia Effect of Information Genotype on Investors' Inertia 61 86 28657 10.22108/amf.2024.140801.1864 FA Fatemeh Jahandari Ph.D. Candidate, Department of Accounting, Ke.C., Islamic Azad University, Kerman, Iran. Amirhossein Taebi Noghondari Assistant Professor, Department of Accounting, Ke.C., Islamic Azad University, Kerman, Iran. Kerman, Iran. Hadis Zeinali Assistant Professor, Department of Accounting, Ke.C., Islamic Azad University, Kerman, Iran. Kerman, Iran. Journal Article 2024 03 02 Investors' belief that current market conditions will persist often leads them to delay reacting to earnings information. Conversely, companies may disclose information in different patterns to significantly impact stock prices and influence investor decisions. They may reveal positive and negative news sequentially or all at once. This study investigated the effects of the order and pattern of information presentation (information genotype) on investor inertia. The sample included data from 5 industries and 58 companies listed on the Tehran Stock Exchange (TSE) from 2010 to 2014. Linear regression analysis based on panel data methods was conducted using EViews and Excel software to test the hypotheses. The findings indicated that information genotype had a positive and significant effect on investor inertia. However, while the sequence of negative to positive information had a direct and significant impact on investor inertia, the sequence of positive-to-negative information did not significantly affect investor inertia. Keywords: Information Genotype, Investors' Inertia, Market Sentiment Index, Standard Unexpected Earnings. Classification JEL: G11-G41-G4-G14 Introduction Disclosure of information is considered in terms of its content, timing, and presentation method (Haqiqat & Iranshani, 2010). Previous studies have focused on the impact of information content and its timing on investors' decisions, but have paid less attention to the form of information presentation (Sheari Anaqiz et al., 2023). Today, companies often disclose information sequentially rather than simultaneously, while the pattern of information presentation can affect information overload, cognitive effort, and decision-making (Rafay & Farid, 2018). Understanding the effect of information presentation models is important for investors facing a wide range of information to make optimal decisions. This study investigated the effects of information genotype on investor inertia, which are emerging areas of study globally. The innovation of this study was that it examined 3 different scenarios dealing with the effects of - a sequence of positive-to-negative information, a sequence of negative-to-positive information, and simultaneous disclosure of good and bad news - on investor inertia. According to classical finance theory, people should react to information in a similar way regardless of how it is presented as the underlying content is the same (Aprayuda, 2021). However, in financial decision-making, the way information is processed, in addition to how it is presented, can affect investor behavior. The belief adjustment theory suggests that when the information genotype is such that positive news is published first followed by negative news, or vice versa, investors will revise their prior beliefs. The information published first will receive less attention than the more recent information due to the "recency effect" (Samal & Mohapatra, 2020). The "primacy effect" also indicates that investors are more sensitive to the first news published (Samal & Mohapatra, 2020). Furthermore, prospect theory suggests that investors may remain in their current position and hold their stocks when bad news is published due to loss aversion (Cui & Zhang, 2022). The information processing theory posits that when investors are bombarded with large amounts of information, their cognitive limitations may prevent them from adequately analyzing the information, leading to suboptimal decision-making. Based on these theoretical perspectives, the central hypothesis of this study was that information genotype has a significant effect on investor inertia. Materials & Methods To examine the effect of information genotype, i.e., the order and sequence of information presentation, the study analyzed Average Abnormal Returns (AAR) and Cumulative Average Abnormal Returns (CAAR) under two scenarios: a) Before the news announcement when the order of news is either good news followed by bad news or bad news followed by good news, b) After the news announcement when the order of news is either good news followed by bad news or bad news followed by good news. The independent variable "information genotype" was calculated as the actual deviation from the expected number of executions: The dependent variable "inertia" was calculated using two measures - the Unexpected Profit Index (UPI) and the market Sentiment Index (SENTI): The following regression models were used to evaluate the hypotheses: The independent variable "information genotype" was proxied by 3 scenarios: 1) Positive-to-negative consecutive information, 2) Negative-to-positive consecutive information, and 3) Simultaneous information (good and bad news). The dependent variable "investors' inertia" was proxied by 2 measures: 1) Market sentiment index and 2) Unexpected profit. To select the control variables, the researchers reviewed prior studies related to information genotype and investor inertia. The control variables include company size, financial leverage, and return on assets. Findings The regression coefficient associated with the sequence index of negative to positive information is 0.752, with a significance level of p = 0.0107 (p < 0.1). Consequently, at the 10% significance level, the second hypothesis is supported, indicating that the transition from negative to positive information significantly influences the market sentiment index. In contrast, the regression coefficient for the sequence index of positive to negative information is -0.605, with a significance level of p = 0.036 (p < 0.1). Thus, at the 10% significance level, the fourth hypothesis is confirmed, revealing a significant negative relationship between positive to negative information and the market sentiment index. The regression coefficient that reflects the simultaneous effect of negative and positive information is -0.012, with a significance level of p = 0.924 (p > 0.1). Therefore, the sixth hypothesis is not supported, indicating that there is no significant relationship between the simultaneous variables of positive and negative information on the market sentiment index. Furthermore, the regression coefficient for the sequence index of negative to positive information is 0.576, with a significance level of p = 0.0502 (p < 0.1). This implies that the influence of negative to positive information on unexpected profit is significant, thereby confirming the third hypothesis. Conversely, the regression coefficient for the sequence index of positive to negative information is -0.660, with a significance level of p = 0.022 (p < 0.1). Hence, the fifth hypothesis is also confirmed, as there is a significant relationship between the sequence of positive to negative information and unexpected profit. Lastly, the regression coefficient for the combined effect of negative and positive information is 0.009, with a significance level of p = 0.952 (p > 0.1). Therefore, the relationship between the simultaneous variables of positive and negative information on unexpected profit is insignificant, leading to the conclusion that the seventh hypothesis is not supported. Discussion & Conclusion The findings from the three different scenarios investigated in this study provided insights into the underlying behavioral theories that explained investor inertia. Perspective theory suggested that investors tended to sell losing stocks faster than profitable ones driven by excessive reaction and loss aversion. This behavioral bias led to increased investor inertia, causing them to sell stocks and exit the market. This hasty decision-making hurt market sentiment and prevented investors from earning unexpected profits. In contrast, belief adjustment theory explained that when negative news was followed by positive news, investors revised their previous beliefs and became optimistic about the stock's future growth potential. This positively influenced investor inertia, leading them to hold onto the stocks in anticipation of higher future returns. As a result, investors were able to earn unexpected profits and market sentiment improved. However, the information processing theory indicated that when good and bad news were released simultaneously, investors' inherent limitations in processing large amounts of information impaired their ability to analyze the news effectively. This affected investor inertia, causing them to remain indifferent and not react. Consequently, market sentiment declined and investors failed to earn unexpected profits. Based on the resutls, one of the key conclusions was that the genotype of information, i.e., the order and sequence of news presentation, had a significant impact on the inertia of investors. This underscored the importance of understanding the behavioral biases and decision-making processes that drove investor behavior in response to different information environments. Investors' belief that current market conditions will persist often leads them to delay reacting to earnings information. Conversely, companies may disclose information in different patterns to significantly impact stock prices and influence investor decisions. They may reveal positive and negative news sequentially or all at once. This study investigated the effects of the order and pattern of information presentation (information genotype) on investor inertia. The sample included data from 5 industries and 58 companies listed on the Tehran Stock Exchange (TSE) from 2010 to 2014. Linear regression analysis based on panel data methods was conducted using EViews and Excel software to test the hypotheses. The findings indicated that information genotype had a positive and significant effect on investor inertia. However, while the sequence of negative to positive information had a direct and significant impact on investor inertia, the sequence of positive-to-negative information did not significantly affect investor inertia. Keywords: Information Genotype, Investors' Inertia, Market Sentiment Index, Standard Unexpected Earnings. Classification JEL: G11-G41-G4-G14 Introduction Disclosure of information is considered in terms of its content, timing, and presentation method (Haqiqat & Iranshani, 2010). Previous studies have focused on the impact of information content and its timing on investors' decisions, but have paid less attention to the form of information presentation (Sheari Anaqiz et al., 2023). Today, companies often disclose information sequentially rather than simultaneously, while the pattern of information presentation can affect information overload, cognitive effort, and decision-making (Rafay & Farid, 2018). Understanding the effect of information presentation models is important for investors facing a wide range of information to make optimal decisions. This study investigated the effects of information genotype on investor inertia, which are emerging areas of study globally. The innovation of this study was that it examined 3 different scenarios dealing with the effects of - a sequence of positive-to-negative information, a sequence of negative-to-positive information, and simultaneous disclosure of good and bad news - on investor inertia. According to classical finance theory, people should react to information in a similar way regardless of how it is presented as the underlying content is the same (Aprayuda, 2021). However, in financial decision-making, the way information is processed, in addition to how it is presented, can affect investor behavior. The belief adjustment theory suggests that when the information genotype is such that positive news is published first followed by negative news, or vice versa, investors will revise their prior beliefs. The information published first will receive less attention than the more recent information due to the "recency effect" (Samal & Mohapatra, 2020). The "primacy effect" also indicates that investors are more sensitive to the first news published (Samal & Mohapatra, 2020). Furthermore, prospect theory suggests that investors may remain in their current position and hold their stocks when bad news is published due to loss aversion (Cui & Zhang, 2022). The information processing theory posits that when investors are bombarded with large amounts of information, their cognitive limitations may prevent them from adequately analyzing the information, leading to suboptimal decision-making. Based on these theoretical perspectives, the central hypothesis of this study was that information genotype has a significant effect on investor inertia. Materials & Methods To examine the effect of information genotype, i.e., the order and sequence of information presentation, the study analyzed Average Abnormal Returns (AAR) and Cumulative Average Abnormal Returns (CAAR) under two scenarios: a) Before the news announcement when the order of news is either good news followed by bad news or bad news followed by good news, b) After the news announcement when the order of news is either good news followed by bad news or bad news followed by good news. The independent variable "information genotype" was calculated as the actual deviation from the expected number of executions: The dependent variable "inertia" was calculated using two measures - the Unexpected Profit Index (UPI) and the market Sentiment Index (SENTI): The following regression models were used to evaluate the hypotheses: The independent variable "information genotype" was proxied by 3 scenarios: 1) Positive-to-negative consecutive information, 2) Negative-to-positive consecutive information, and 3) Simultaneous information (good and bad news). The dependent variable "investors' inertia" was proxied by 2 measures: 1) Market sentiment index and 2) Unexpected profit. To select the control variables, the researchers reviewed prior studies related to information genotype and investor inertia. The control variables include company size, financial leverage, and return on assets. Findings The regression coefficient associated with the sequence index of negative to positive information is 0.752, with a significance level of p = 0.0107 (p < 0.1). Consequently, at the 10% significance level, the second hypothesis is supported, indicating that the transition from negative to positive information significantly influences the market sentiment index. In contrast, the regression coefficient for the sequence index of positive to negative information is -0.605, with a significance level of p = 0.036 (p < 0.1). Thus, at the 10% significance level, the fourth hypothesis is confirmed, revealing a significant negative relationship between positive to negative information and the market sentiment index. The regression coefficient that reflects the simultaneous effect of negative and positive information is -0.012, with a significance level of p = 0.924 (p > 0.1). Therefore, the sixth hypothesis is not supported, indicating that there is no significant relationship between the simultaneous variables of positive and negative information on the market sentiment index. Furthermore, the regression coefficient for the sequence index of negative to positive information is 0.576, with a significance level of p = 0.0502 (p < 0.1). This implies that the influence of negative to positive information on unexpected profit is significant, thereby confirming the third hypothesis. Conversely, the regression coefficient for the sequence index of positive to negative information is -0.660, with a significance level of p = 0.022 (p < 0.1). Hence, the fifth hypothesis is also confirmed, as there is a significant relationship between the sequence of positive to negative information and unexpected profit. Lastly, the regression coefficient for the combined effect of negative and positive information is 0.009, with a significance level of p = 0.952 (p > 0.1). Therefore, the relationship between the simultaneous variables of positive and negative information on unexpected profit is insignificant, leading to the conclusion that the seventh hypothesis is not supported. Discussion & Conclusion The findings from the three different scenarios investigated in this study provided insights into the underlying behavioral theories that explained investor inertia. Perspective theory suggested that investors tended to sell losing stocks faster than profitable ones driven by excessive reaction and loss aversion. This behavioral bias led to increased investor inertia, causing them to sell stocks and exit the market. This hasty decision-making hurt market sentiment and prevented investors from earning unexpected profits. In contrast, belief adjustment theory explained that when negative news was followed by positive news, investors revised their previous beliefs and became optimistic about the stock's future growth potential. This positively influenced investor inertia, leading them to hold onto the stocks in anticipation of higher future returns. As a result, investors were able to earn unexpected profits and market sentiment improved. However, the information processing theory indicated that when good and bad news were released simultaneously, investors' inherent limitations in processing large amounts of information impaired their ability to analyze the news effectively. This affected investor inertia, causing them to remain indifferent and not react. Consequently, market sentiment declined and investors failed to earn unexpected profits. Based on the resutls, one of the key conclusions was that the genotype of information, i.e., the order and sequence of news presentation, had a significant impact on the inertia of investors. This underscored the importance of understanding the behavioral biases and decision-making processes that drove investor behavior in response to different information environments.

https://amf.ui.ac.ir/article_28657_11cc22aa44bf235616af881c445cae4c.pdf

University of Isfahan Journal of Asset Management and Financing 2383-1189 12 4 2024 12 21 Analyzing Company’s Internal and External Factors Influencing the Financing Model through Structural Equation Modeling (SEM) Analyzing Company’s Internal and External Factors Influencing the Financing Model through Structural Equation Modeling (SEM) 87 120 28697 10.22108/amf.2024.140584.1861 FA Sajad Veisi Ph.D. Candidate, Department of Accounting, Faculty of Economic and Social Sciences, Shahid Chamran University of Ahvaz, Ahvaz, Iran Seyed Ali Vaez Associate Professor, Department of Accounting, Faculty of Economic and Social Sciences, Shahid Chamran University of Ahvaz, Ahvaz, Iran Ebrahim Anvari Associate Professor, Department of Economics, Faculty of Economic and Social Sciences, Shahid Chamran University of Ahvaz, Ahvaz, Iran 0000-0002-6050-8465 Esmaeel Mazaheri Assistant Professor, Department of Accounting, Faculty of Economic and Social Sciences, Shahid Chamran University of Ahvaz, Ahvaz, Iran Journal Article 2024 02 03 This study aimed to identify the most effective financing model by analyzing the internal and external factors influencing companies. We compiled data from 159 companies spanning 2012 to 2021, encompassing 1,590 company-years, to test 14 hypotheses. These hypotheses were evaluated using Structural Equations Modeling (SEM) with SmartPLS4 software across 3 distinct models. The financing model was categorized into 3 components: internal financing, short-term external financing, and long-term external financing. The findings revealed that the following factors significantly impacted all three types of financing: 1) Board of Directors’ characteristics; 2) Audit characteristics; 3) Internal control characteristics; 4) Ownership structure; 5) Managerial characteristics; 6) Financial reporting quality; 7) Financial performance; 8) Market performance; 9) Investment efficiency; 10) Competitive strategies; 11) Corporate social responsibility; 12) Political communication; 13) Economic uncertainty; and 14) Firm characteristics. Notably, economic uncertainty was found to exert a negative and significant effect on financing across all three dimensions, while the other variables positively facilitated company financing. Furthermore, the analysis indicated that the selected structures had greater explanatory power for long-term financing compared to internal and short-term financing as evidenced by the determination coefficients of all three models. This study aimed to identify the most effective financing model by analyzing the internal and external factors influencing companies. We compiled data from 159 companies spanning 2012 to 2021, encompassing 1,590 company-years, to test 14 hypotheses. These hypotheses were evaluated using Structural Equations Modeling (SEM) with SmartPLS4 software across 3 distinct models. The financing model was categorized into 3 components: internal financing, short-term external financing, and long-term external financing. The findings revealed that the following factors significantly impacted all three types of financing: 1) Board of Directors’ characteristics; 2) Audit characteristics; 3) Internal control characteristics; 4) Ownership structure; 5) Managerial characteristics; 6) Financial reporting quality; 7) Financial performance; 8) Market performance; 9) Investment efficiency; 10) Competitive strategies; 11) Corporate social responsibility; 12) Political communication; 13) Economic uncertainty; and 14) Firm characteristics. Notably, economic uncertainty was found to exert a negative and significant effect on financing across all three dimensions, while the other variables positively facilitated company financing. Furthermore, the analysis indicated that the selected structures had greater explanatory power for long-term financing compared to internal and short-term financing as evidenced by the determination coefficients of all three models.

https://amf.ui.ac.ir/article_28697_ccff28bce6088d365183147862868a35.pdf

University of Isfahan Journal of Asset Management and Financing 2383-1189 12 4 2024 12 21 Examining the Effects of Investor Sentiment Shocks on Normal and Abnormal Returns in the Oil Products Sector of the Tehran Stock Exchange: A PVAR Analysis Examining the Effects of Investor Sentiment Shocks on Normal and Abnormal Returns in the Oil Products Sector of the Tehran Stock Exchange: A PVAR Analysis 121 140 28751 10.22108/amf.2024.141845.1892 FA Mohammad Javad Zare Bahnamiri Associate Professor, Department of Accounting, Faculty of Economic and Administrative Sciences, University of Qom, Qom, Iran Samira Balavar M.A., Department of Accounting, Faculty of Economic and Administrative Sciences, Qom University, Qom, Iran Vahid Omidi Assistant Professor, Department of Economics, Faculty of Economics Sciences and Administrative, University of Qom, Qom, Iran. Journal Article 2024 06 14 Abstract The behavioral finance perspective posits that fluctuations in security prices are significantly influenced by investors' emotional responses, which can, in turn, affect stock returns. Understanding the sources of stock price changes is critical within asset pricing theory, highlighting the necessity of exploring the effects of investor sentiment on stock returns. This study aimed to investigate how investor sentiment shocks impact both normal and abnormal returns in the oil products sector of the Tehran Stock Exchange. To measure abnormal returns, we employed the six-factor model developed by Fama and French (2018). Investor sentiment was evaluated using the Relative Strength Index (RSI), the Psychological Line Index (PLI), trading volume, and the Adjusted Turnover Rate (ATR). Data were collected from 12 companies in the oil products industry over a period of 1,584 months, spanning from 2010 to 2020. The findings revealed that the influence of sentiment shocks on normal returns was more pronounced than on abnormal returns. Conversely, the impact of normal return shocks on sentiment was initially positive but became negative over time. Additionally, positive shocks to abnormal returns adversely affected investor sentiment, with the peak effect observed after five periods. This research enhances the understanding of how investor sentiment shocks influence normal and abnormal returns in the oil products sector, offering valuable insights into behavioral differences among investors. Abstract The behavioral finance perspective posits that fluctuations in security prices are significantly influenced by investors' emotional responses, which can, in turn, affect stock returns. Understanding the sources of stock price changes is critical within asset pricing theory, highlighting the necessity of exploring the effects of investor sentiment on stock returns. This study aimed to investigate how investor sentiment shocks impact both normal and abnormal returns in the oil products sector of the Tehran Stock Exchange. To measure abnormal returns, we employed the six-factor model developed by Fama and French (2018). Investor sentiment was evaluated using the Relative Strength Index (RSI), the Psychological Line Index (PLI), trading volume, and the Adjusted Turnover Rate (ATR). Data were collected from 12 companies in the oil products industry over a period of 1,584 months, spanning from 2010 to 2020. The findings revealed that the influence of sentiment shocks on normal returns was more pronounced than on abnormal returns. Conversely, the impact of normal return shocks on sentiment was initially positive but became negative over time. Additionally, positive shocks to abnormal returns adversely affected investor sentiment, with the peak effect observed after five periods. This research enhances the understanding of how investor sentiment shocks influence normal and abnormal returns in the oil products sector, offering valuable insights into behavioral differences among investors.

https://amf.ui.ac.ir/article_28751_597212dc0887cb9d6f30dd851eb01053.pdf