Levi and Welch (2020) argue that market beta and asymmetric downside beta are highly correlated and that most of downside beta's explanatory power stems from market beta. This study re-examines the relationship between stock returns and downside beta in the Korean stock market. We test beta spreads including beta asymmetry (i.e., down beta - up beta spread) and relative downside beta (i.e., down beta - market beta spread) to control for the market beta. We find negative correlations between downside betas and stock returns even after controlling for market beta and firm characteristics. We also find that regardless of market conditions (i.e., bear, neutral, and bull markets) high beta spreads are associated with low returns. Accordingly, zero-cost portfolios that purchase the stocks in the low quintile of beta spreads and sells the stocks in the top quintile generate significantly positive alphas. These findings underline that downside beta contains the unique information beyond market beta in the Korean stock market.

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This study investigates whether pre-meeting vote disclosures by large asset owners can amplify the influence of their votes at shareholders' meetings. We utilize the newly adopted 2019 rule that mandates Korea’s National Pension Service (NPS) to disclose voting decisions before the shareholders’ meeting. Firms subject to this pre-meeting disclosure must meet either of two conditions: the NPS holds at least 10% of the firm’s voting shares or the firm’s weight in the NPS domestic equity portfolio is at least 1%. Employing a regression discontinuity design and difference-in-differences analyses, we find that the NPS pre-meeting disclosure causes other institutional investors to increase their conformity to the NPS votes. We further find that this effect mainly originates from the resolutions that the NPS votes against management; this result is pronounced among the institutional investors who are more likely to face problems related to conflicts of interest.

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Educational background in Korea can represent personal traits, since academic tracks in the Korean educational system are determined earlier in the individual’s lifetime than in other countries. This study investigates whether CEO educational background affects the firm’s external financing choices. We find that firms with CEOs who majored in science or engineering are less likely to issue equity, and the investment of firms with such CEOs is more responsive to cash flow. We also find that equity issue announcements by firms with such CEOs exhibit more negative market reaction, suggesting that those have bad signals, for instance, poor conditions to issue debt even though they prefer debt to equity. Overall, our study suggests that Korean CEOs’ educational background, particularly science or engineering, is related to managerial confidence, which is the belief that the market undervalues their firms. However, we cannot completely rule out the endogeneity concern arising from CEO-firm matching.

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This paper examines the effect of issuance of ELS(Equity Linked Security) with the Hong Kong HSCEI index as an underlying asset, on the volatility skew in the Hong Kong options market. The most common structure of ELS includes an autocallable option every 6 month and 3-year time-to-maturity, which pursues medium-return along with medium-risk. When trading ELS as an issuer, traders are exposed to various risks in the process of hedging - typically the vega risk caused by changes in volatility. In the case of ELS with knock-in put option, the issuer’s position is generally similar to taking a long position in a put option at the moment of issuance, so vega hedge is normally executed through selling vanilla options. As the ELS with global stock indices as underlying assets has become popular since 2014, local securities companies have begun to adopt volatility surfaces to evaluate the fair price of ELS for the purpose of increasing the book sizes and enhancing trading performance. Accordingly, the demand for selling options with specific strike prices is matched with the autocall barriers. We analyze the effect of ELS issuance on market volatility including the VHSCEI index. The volatility skew is defined as the difference between the volatility indexes of the OTM(Out-of-The-Money) put option and those of the ATM(At-The-Money) option. Since the first autocall barriers of ELS are located on 80% to 95% of the strike price, the volatility index of the 90% strike put option is used. So far, most studies related to ELS examined the effect of issuance on the trading volume and volatility of underlying assets. Even in the previous studies on the effects of delta and gamma (or vega) risk hedging on the volatilities, the effect on only short-term volatility such as realized volatility or VKOSPI index was analyzed. Also there are various studies on the way of calculating the volatility surface depending on maturity and strike price. But there was no studies on the effect of the issuance of structured products in one country on the option market in another country. This study is the first study on the effect of issuance of structured products in Korea on the volatility skew in the Hong Kong options market. The detailed results are as follows. First, as the issuing volume of ELS increases, market volatility such as VHSCEI index decreases, and in particular, VHSCEI index decreases more relative to the realized volatility. This is consistent with the results of previous studies. Also, issuance of ELS lowers the volatility index of the 90% put option compared with the VHSCEI index. Second, with respect to the volatility skew of the same maturity, a strong negative correlation between the ELS issuance volume and the volatility skew since 2014 is observed. It can be interpreted that the volatility of OTM put options decreases compared with the ATM ones as the selling pressure for the OTM increases compared to the ATM. These results are the same for all OTM put options. As a result, if the volume of financial products with the same structure increases significantly, and in particular, if the underlying assets, maturities, and strike prices of the financial products are concentrated, the impact of volatility on the options market can be expected to be larger. It is necessary to sophisticate the issuing and book-managing strategies to diversify the risk of the ELS issuer and to enhance the product’s yield in the future.

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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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