According to behavioral finance, the effect of attention in the stock market has a significant impact on investor decision-making. Individual stocks of high investor attention increase investor irrational bias, such as overconfidence, and this psychological bias causes an overreaction to the asset. Overconfidence investors make aggressive transactions, and investor attention causes high trading volume. This study investigates the impact of investor overconfidence on stock returns in the Korean stock market based on the fact that investor confidence due to the effect of investor attention is closely related to trading volume. We present variables that can measure the degree of investor overconfidence in individual assets and analyze the effect of investor overconfidence on stock returns in the Korean securities market. In this study, we present the investor's overconfidence measure (IOC) using the highest trading volume over the past 12 months and the current trading volume. At the end of each month, we form a portfolio of deciles based on IOC to confirm the relationship between stock returns and investors' overconfidence. We focus on extreme portfolios to determine the impact of IOC on future returns. If the investor's overconfidence has a significant negative effect on the stock return, the investor's overconfidence has a relatively low stock return on an extremely high portfolio. As a result, the higher the investor's confidence, the lower the future return. It argued that the relationship between investor overconfidence and stock returns through a zero-cost portfolio strategy in which longs the lowest IOC portfolio and shorts the highest IOC portfolio, the IOC strategy has a significant positive return. This phenomenon is maintained even after considering firm characteristics factors, investor overreaction, volatility, and gambling tendency. The IOC's significant negative predictive power for stock returns is maintained through Fama-MacBeth cross-sectional regression analysis. Furthermore, We reaffirm the results of this study by the proportion of individual investors' trading, the separation of sub-periods, and the past period constituting the IOC. As a result of dividing the portfolio according to the proportion of individual investors, the higher the proportion of individual investors, the more pronounced the significant negative relationship between stock returns and investors' overconfidence. Moreover, the results of the KOSDAQ market where individual investors have a high proportion of transactions and high volatility has a higher return on IOC strategy. The sample period is divided into four sub-periods and analyzed. We confirm that the relationship between investor overconfidence and stock returns is relatively weakened after the financial crisis. In addition, the return on the IOC strategy increases as individual investors' market participation increases after the outbreak of coronavirus in the Korean stock market. These results reaffirm that the IOC fully reflects the psychological changes of individual investors. Finally, as a result of changing the past period constituting the IOC to 6, 18, and 24 months, the IOC strategy has a significant positive rate of return in all past periods. Accordingly, investors' overconfidence in individual assets in the domestic stock market has a significant negative effect on the stock returns and a significant cross-sectional negative predictive power. This study is meaningful in that it studied the effect of investor overconfidence on the stock market due to the effect of interest in individual assets in the domestic stock market. Furthermore, it has implications for related fields in that it presents measures indicating the degree of investor overconfidence in individual assets and presents empirical results. And report the results of controlling several variables closely related to investor overconfidence. These results support the existing argument that investors' overconfidence has a significant effect on stock returns.

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This paper investigates the ability to predict corporate default rates using loan-sample data from the Korea Credit Information Service's financial big data open system (CreDB). The corporate loan from financial institution increases financial institution's credit exposure. Because measurement of the impact on the credit risk in the financial institution is used in determining the pricing model and structure of loan products, it is an essential factor for the financial institution that affects its profit structure. In terms of risk management, predicting delinquency using loan data is necessary for 5,000 Korean financial institutions. In several studies, bankruptcy forecasting was conducted on listed companies that disclosed financial and stock price information. However, this study increases the practical utility by extending the analysis target to individual entrepreneurs and small and medium-sized enterprises(SMEs). In addition, this study presents representative big data analysis results by utilizing loan, delinquency, and technology credit information of approximately 1.1 million corporations, which is 20% of almost 5.6 million domestic sole proprietors and non-listed corporations. For loan data, it includes ten monthly loan type codes and eleven overdue reason codes. Prediction targets are separated by individual and corporate entrepreneurs. Also, analyses are divided by use of the processed dataset. For efficient analysis, the data dimension was reduced by changing the table structure through nested iterative operations while expanding the variable composition from a table consisting of N rows to one column. To reflect the characteristics of the data as much as possible, exploratory data analysis and feature-engineering were performed to process the data. Also, classification models are classified by four groups using a parametric method that nine models train for classification. Group 1 consists of Logistic Regression and Linear discriminant analysis based on the parametric method, group 2 consists of several algorithms that calculate the distance for model learning. In addition, group 3 consists of tree-based algorithms, which are also non-parametric methods. Group 4 consists of the semi-parametric method, which is deep neural network. However, out of the total 438,697 corporations, 810 defaulted, accounting for only 0.2% of the forecast, so the target distribution is severely imbalanced. For this reason, before model fitting, under sampling of imbalanced data was performed. The bias of the sampled training and validation data is minimized by performing. K-fold cross validation as much as the level of K=5. Finally, the analysis result suggests a significant effect on classification performance when the processed data is used. However, this study suggests no significant effect on performance when loan owner's characteristics are included. Moreover, tech-credit rating (TCB) information gives any meaningful effect regarding the type of corporation. Also, classification with Deep Neural Network (DNN), which is based on the Semi-parametric method, makes the best performance of binary classification. Non-parametric and Non-tree based models are not appropriate methods for analyzing loan data. In the case of the DNN based on the semi-parametric methodology, the highest classification performance was confirmed for all analyses and entrepreneurs' classifications performed in this study. The neural network used in this study consists of 14 hidden layers. According to the neural network baseline design, the sigmoid function was applied to the activation function's initial value, the relu function was applied to the hidden layer, and optimization was performed through the Adam optimizer. In particular, the analysis of credit transaction information based on credit information of all financial institutions in Korea was conducted, and there is a possibility for alleviating information asymmetry of individual credit institutions regarding risk management targets. In addition, in the case of parametric methodologies used in classical studies and most used in practice, the average classification performance for major segments was inferior to that of semi-parametric methodologies. Furthermore, the difference between these performances is up to 16 percent. This paper suggests the direction of using loan-sample data. It is foundational research for financial institutions that are using loan data for credit risk management. It is necessary to expand research focusing on semi-parametric methodologies about corporate credit information analysis.

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This study investigates the role of powerful CEOs on future stock price crashes. Our results reveal an inverted U-shaped relationship between CEO power and stock price crash risk. Specifically, powerful CEOs tend to conceal more negative news, increasing stock price crash risk, which indicates the presence of incentives to take private benefits. However, extremely powerful CEOs decrease stock price crash risk, suggesting that sufficient entrenchment may mitigate further private benefits from concealing negative news. Additionally, the nonlinear relationship is observed only in competitive industries. This fact implies that strong external monitoring mitigates CEOs’ incentives to pursue private benefits, but raises extremely powerful CEOs’ career concerns, which encourages them to conceal more negative news.

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Previous literature posits that CEOs with inside debt holdings are more likely to engage in corporate social responsibility (CSR) since they respond to bondholders’ demands as their appetite for risk decreases. This study examines whether a CEO’s risk concerns moderate the effect of CEO inside debt holdings on the firm’s CSR performance. We find that the positive relationship between CEO inside debt and CSR is weakened when CEOs are close to retirement, or when firms face less product market competition within their respective industries. Our results also suggest that the effect of CEO inside debt, as well as the moderating effect of CEO retirement and low competition, differs between internal and external stakeholder CSR. Furthermore, we find that the moderating effect of CEO retirement is strongly supported in propensity score matching analysis and alternative model specification, whereas that of low competition is weakly supported. Overall, this study has important policy implications for board members, managers, investors, and regulators as it highlights that CEOs’ compensation structure and risk concerns can be determinants of corporate sustainability policies.

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In the current low-interest rates environment, Korean banks' profitability is expected to weaken significantly because of the large proportion of interest revenue in total revenue. For instance, Korean banks' interest revenue accounted for 84 percent of total revenues in 2019. As a results, Korean banks need to accelerate their strategy for revenue diversification, such as increasing non-interest revenue in total revenue. In general, revenue diversification, such as increasing a non-interest revenue, is expected to stabilize or improve banks' profitability. However, previous empirical studies show inconsistent results on the relationship between non-interest revenue and total profitability in banks. For instance, Smith et al. (2003) argue that banks' profitability is stabilized by diversifying revenue if the non-interest revenue increases. In contrast, De Young and Roland (2001), Stiroh and Rumble (2006) show that the high volatility of non-interest revenue offsets revenue diversification. Stiroh (2004) argues that the increase in non-interest income does not lead to risk diversification because of the the high correlation between interest revenue and non-interest revenue in analysis for U.S. banks. Thus, unlike previous studies, the paper analyzes the relationship between the proportion of non-interest revenue and profitability in Korean banks using the U-shaped test method of Lind and Mehlum (2010) to determine a nonlinear relationship between the proportion of non-interest revenue and profitability. Empirical results using the financial statements of 15 Korean banks from 2008 to 2019 show that Korean banks' profitability and the proportion of non-interest revenue have an inverted U-shaped relationship. Here, the maximum point of an inverted U-shape represents the optimal proportion level of non-interest revenue that generates the highest banks' profitability. It means that profitability improves as the proportion of non-interest revenue increases until the optimal proportion level of non-interest revenue. However, exceeded an optimal proportion level of non-interest revenue, the profitability decreases as the proportion of non-interest revenue increases. This inverted U-shape relationship is interpreted as follows. In a positive relationship between non-interest revenue and profitability, an increase in non-interest revenue obtains an additional profit channel and generates a revenue diversification effect. On the other hand, when non-interest revenue and profitability have a negative relationship, the increasing non-interest revenue causes a reduction in the opportunity profit of interest revenue and amplifies revenue uncertainty by the high volatility of non-interest revenue. The results indicate that Korean banks' excessive concentration of the management capabilities on non-interest operations may decrease the total profitability. In particular, the study also has found that Korean banks have a high correlation between commission revenue, which accounts for the largest proportion of non-interest revenue, and interest revenue. Thus, the result implies that Korean banks' increasing non-interest revenue strategy, although it increases non-interest revenue, has inefficient to achieve revenue diversification effects because of the high correlation between interest revenue and non-interest revenue. For instance, Korean banks often sell products based on non-interest to customers who buy products based on interest; this sales strategy weak the risk diversification effects by overlapping the customer groups between interest and non-interest products. This paper also conducts an empirical analysis by dividing banks into commercial and regional banks. The results show that commercial banks' profitability and the proportion of non-interest revenue have an inverted U-shape relationship. We also empirical test for commercial banks by classifying the observation based on the optimal proportion of non-interest revenue. The results show that the commercial bank's relationship between the proportion of non-interest revenue and profitability is significantly positive in the case of below the optimal proportion level. On the other hand, the commercial bank's relationship between non-interest revenue and profitability is insignificantly negative in the case of above the optimal proportion level, which is attributable to a small number of samples for banks with a proportion of non-interest revenue above the optimal proportion level. That is, the result implies the Korean banks' high reliance on interest revenue. Similarly, local banks have statistically only positive relationships between non-interest revenue and profitability due to the deficient proportion of non-interest revenue. In the current low-interest rate environment, it is inevitable for Korean banks to accelerate expanding non-interest revenue. However, as the results in this paper, excessive non-interest revenue expansion strategies may occur a negative impact on profitability according to an inverted U-shaped relationship between the proportion of non-interest revenue and profitability. Thus, Korean banks should first set up sophisticated and systematic strategies for expanding non-interest revenue to achieve an advantage of increasing non-interest revenue. To do so, banks need to differentiate their sale strategy by customer characteristics and develop their risk management capabilities to manage volatility in non-interest revenue. In addition, it is necessary to derive the optimal proportion of non-interest income for the individual bank by considering the characteristics of an individual bank in the future study.

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This study analyses the effect of corporate governance on corporate innovation. Specifically, I investigate firms that are given corporate governance scores from the Korea Corporate Governance Service (KCGS) in the Korean market from 2005 to 2016. These governance scores have four categories: shareholders’ rights, board of directors, market disclosure, and auditing body. For the purposes of this study, I primarily consider the total governance score, which is the comprehensive index of a firm’s governance status. In addition, the corporate innovation output is measured by R&D expenditures, the total number of granted patents, and the total number of citations received. R&D activity, in general, is a long-term investment that causes uncertainty and information asymmetry. It also generates an agency problem, which is a conflict of interest between shareholders and managers (Miozzo and Dewick, 2002; Finkelstein and Boyd, 1998; Coff, 2003). While shareholders prefer R&D investment to pursue the long-term growth and profit of their firm, managers are more likely to prefer short-term investments. As corporate governance aligns the interests of managers and shareholders, governance can positively affect to corporate innovation. Therefore, the hypothesis in this study is that a firm with good governance is likely to demonstrate high innovation (R&D, grated patent, forward citation). Previous studies mainly focus on the relationship between corporate governance and R&D investments, while demonstrating a positive relationship between governance score and R&D investment (Kim, 2003; Kim, 2015; Kim and Lee, 2012; Lee and Cho, 2001). However, there are a few studies that show the relationship between corporate governance and patents. Seok (2018) reports that firms with a high governance score hold more patents using KOSPI firms from 2011 to 2016. He, however, analyzes the total number of granted patents, which represents the quantity of innovative activities. Like Seok (2018), Choi, Chung, and Wang (2020) examine the effect of governance quality on firm innovation using the total number of granted patents. In this study, I analyze forward citations, which represent the quality of corporate innovation, in addition to granted patents. The crucial contribution of this study is the use of a novel innovation measurement. Unlike, in the US, Korean patent information has not been consolidated in a single database. Since researchers need to hand-collect patent data, previous studies have only analyzed data for short periods or specific industries. Moreover, most research on this topic in Korea uses the total number of granted patents each year to measure firm innovation. To overcome this limitation, I retrieve patent data using a Python program from KIPRISplus (Korea Intellectual Property Rights Information Service), which is a patent information service providing real-time access to KIPO’s database with Open API. This allows for the use of forward citation information in order to investigate the quality of the patent. Thus, I extend the prior literature by examining both the quality and quantity of innovative activities using various measurements. The main findings are as follows. I find a positive association between a firm’s governance score and the level of corporate innovation. Firms that have a higher governance score spend more on R&D, which is consistent with the previous literature. Additionally, firms with a strong governance score are likely to grant more patents than firms with weak governance. Moreover, I introduce forward citations as a measure of the quality of innovation, which is calculated by the total number of citations received in subsequent years. The result indicates a positive association between governance score and forward citations. Firms with a strong governance index tend to achieve highly-cited patents. There also exists a significant difference in the coefficient estimates between granted patents and forward citations. These results are robust when compared to alternative approaches. Governance and innovation activities are likely endogenously determined. To alleviate this endogeneity problem, I use the t-1 value for the governance score as well as the two-year sum from t+1 to t+2 for innovation variables, which allow me to find qualitatively similar results. Next, I employ 2SLS analysis with instrument variables. The listed firms, with over two trillion won of total assets, have an obligation regarding the appointment of an outside director, auditor, and audit committee. Thus, this method can be an appropriate instrument to eliminate endogeneity between governance and innovation (Ko, Baik, and Ahn, 2012; Kim and Eum, 2008; Sohn, 2010). In summary, all the results imply that corporate governance is an important factor for explaining corporate innovation activities, especially forward citations.

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In order to ensure stable retirement life for employees, their rights to receive retirement pension benefits must be guaranteed. The claim that guaranteeing the entitlement to pension benefit is important and that ways to protect entitlement are necessary have been continued, there has been little improvement in this regard since the introduction of the “Retirement Benefit Guarantee Act”. Although this act implements the “Minimum External Funding Ratio Regulation”, the “Wage Bonds Priority Repayment System”, and the “Wage Bonds Guarantee System”, it is insufficient to protect the entitlement to pension benefits. First of all, the “Minimum External Funding Ratio Regulation” has a limitation in that a significant number of companies do not meet the minimum funding ratio, however there is no compulsory punishment for this. Next, the “Wage Bonds Priority Repayment System” and the “Wage Bonds Guarantee System” serves to guarantee workers’ retirement benefit ex-post when employers fail to pay retirement benefit due to bankruptcy or financial difficulty. However, due to the limited coverage, it serves only as a function of guaranteeing the minimum cost of living for employees. In this study, we present a plan to guarantee retirement pension benefit of employees belonging to defined benefit entitlement according to the pension governance structure. In particular, we propose that the retirement benefits of employees under the current contract-based governance structure are guaranteed by the “Retirement Benefit Guarantee Fund,” which separates the retirement benefits from the current “Wage Bonds Guarantee Fund”. In addition, we propose to establish “Pension Benefit Guarantee Fund” operated by Pension Benefit Guarantee Institution to guarantee retirement benefits for members under the funded pension governance structure to be introduced in the near future. However, prior to the introduction of these benefit guarantee systems, it should be implemented on strengthening the regulation of the “Minimum External Funding Ratio Regulation” first. Meanwhile, in order to guarantee the payment of retirement benefit, workers' right to receive benefits must be protected at a reasonable level. In particular, it is necessary to legally establish eligibility criteria for payment guarantees and prohibit guarantees over a certain amount to prevent from moral hazard of employers and financial institutions. In addition, the “Retirement Benefit Guarantee Fund” and the Pension Benefit Guarantee Fund” should be operated under the government's agency along with compulsory subscription rather than voluntary subscription by the choice of the employer or trustee. This is because the government's initiative is needed to alleviate the problems of the payment guarantee mechanism that the aforementioned adverse selection and systematic risk cannot be controlled to some extent. Recently, there has been continuous argument that asset management behavior of retirement pensions should be improved as a way to increase the return on retirement pension assets. The most worrying part about the introduction of default options and fund-type retirement pensions under discussion for this purpose is the fact that the current retirement pension system does not have a practical mechanism to guarantee workers' entitlements. Therefore, in order to increase the subscription rate of the retirement pension and to eliminate blind spots, it is necessary to present a more practical plan to strengthen the right to receive retirement benefits prior to the mandatory introduction of the retirement pension. Although compulsory retirement pension system has the effect of expanding the introduction of retirement pensions in small and medium-sized businesses with relatively weak financial conditions, considering that survival is a priority for companies with poor financial conditions, it may be practically impossible to accumulate retirement benefits outside the company. Therefore, in order to guarantee workers' right to receive retirement pensions, in particular, guarantee and protection of the payment of retirement benefits is a pre-emptive task.

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Using short-window regressions, prior studies have shown that the conditional CAPM performs as poorly as the unconditional CAPM and that unconditional alphas are too large to be explained by the covariance between conditional betas and market risk premium. I examine the extent to which these results are driven by estimation biases in short-window regressions. Even when the true time-varying beta has highly transient components, beta estimates from these short-window regressions can be estimated to highly persistent because of yearly portfolio reformulations that are commonly employed in empirical studies. I show that, under these circumstances, large non-zero alpha estimates from short-window regressions are consistent with the conditional CAPM and the covariance estimates between conditional betas and market risk premium are biased downward and can have large estimation errors.

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In this paper, we develop a new way of measuring the herding behavior of market participants and test herding behavior among investors in Chinese IPO firms, compared with prior methods of herding measure developed by Christie and Huang (1995), Chang, Chen, and Khorana (2000), and Hwang and Salmon (2009). Our proposed new non-parametric herding measure, cross sectional time dispersion (CSTD), is defined differently as dispersion in IPO issuance timing, compared with traditional definitions of herding as dispersion in IPO returns or risk measure. Traditional CSSD, CSAD and beta herding measures do not provide statistically significant or consistent relationship between the herding measures and the IPO firms’ initial or long-term returns. In contrast, the new measure of time herding, CSTD clearly and consistently indicates that investors are affected more by the herding behaviors of IPO firms than by those of investors in the IPO markets in China.

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This study examines how ESG (Environmental, Social, Governance) factors are incorporated in credit ratings in Korea. The empirical results show that ESG scores have, in general, a positive effect on credit ratings, suggesting that corporate ESG is reflected to some extent in credit ratings. Among the factors of ESG, the governance factor has a significant relationship with credit ratings. The result is obvious in that some important governance elements such as internal control devices, disclosure and transparency, and ethical management are included in the aspect of business management risk during credit evaluation. On the other hand, social and environmental factors have a partial or insignificant relationship with credit rating. As social interest in ESG increases, it is highly likely that ESG itself becomes one of the most important determinants on credit ratings in the near future. In such a case, the results of this study can be used as a reference for the decision logic of credit rating reflecting ESG.

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