This study comprehensively analyzes the patterns of risk and return relationship in the Korean stock market and applies them to portfolio management strategies. Total eight number of risk measures - long and short term total volatility, systematic volatility, idiosyncratic volatility, and market beta - are employed to analyze the risk-return relationship in the KOSPI market from July 1990 to December 2021. Furthermore, based on the results of the analysis, we conduct various empirical experiment to improve the profitability of the low-risk related ETFs traded in the Korean stock market. The key findings are as follows: First, we observe that the low-risk anomalies are significant over the entire period only for the short-term volatility measures. Small-growth groups show greater low-risk premiums for long-short portfolios, whereas small-value groups exhibit higher low-risk premiums for long-only portfolios. Second, the low-risk anomalies are not robust across the risk measures and measurement periods. Third, as a result of the causality analysis between the risk premiums from the different risk measures, we find that the low-risk anomalies in the Korean stock market are primarily driven by idiosyncratic volatility anomaly. Lastly, we find that the definition of underlying indices of the low-risk related ETFs currently traded in the Korean stock market does not adequately reflect the empirical patterns of the risk-return relationship. If we modify them in accordance with our empirical findings, the profitability of the low-risk indices significantly improve with robustness. This study has contributions in that it deepen the understanding of the low-risk anomalies in the Korean stock market and proposes practically useful applications of them to enhance portfolio management strategies.

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Motivated by the mixed findings of the existing literature, we investigate the performance of the volatility targeting strategy in four Asian equity markets based on a block-bootstrap simulation. We found no clear evidence of outperformance of the strategy against a 50/50 constant-mix portfolio, except in the Chinese market where volatility and tail risk are highest. The lack in performance has been attributed to an inability to detect the negative relationship between volatility and returns by all of the volatility forecasting models we consider. This may affect the capacity to reduce downside risk and tail risk but consistently causes a substantial drag on performance. Owing to forecasting errors, the strategy appears to perform considerably better and easier to implement in practice when using a model with low sensitivity to volatility changes along with a rebalancing buffer.

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Virtual assets have experienced dramatic ups and downs over the past few years, since an anonymous developer named Satoshi Nakamoto introduced Bitcoin in 2008. Bitcoin is a peer-to-peer electronic cash system based on blockchain technology, enabling payments and transactions verification without a centralized custodian. Despite controversies surrounding Bitcoin's currency status (IMF, 2016; Yermack, 2015; Hendrickson et al., 2015), there is a consensus that virtual assets function as alternative investment assets providing portfolio diversification, inflation hedging, and exposure to new technology effects. (Glaser et al., 2014; Briere et al., 2015; Bouri et al., 2017; Choi, 2022) Consequently, the market for virtual assets has evolved significantly, with over 26,346 types of virtual assets issued by the end of June 2023, and their total market capitalization estimated to exceed $11.7billion (coinmarketcap). Despite recognition of the legitimacy of virtual assets by major countries such as the US, EU, Japan, and Korea, attempts to bring them under policy consideration have led to differing regulatory systems and relative scales of supply and demand across countries, resulting in price deviations. Notably, the daily average price ratio between the USD and KRW Bitcoin market exceeded 15% from December 2017 to February 2018, a phnomenon referred to as the 'Kimchi premium' in both popular press and academic research (Makarov ans Schoar, 2020; Yang, 2019). These deviations from the law of one prices is even more pronounced due to the untraceable cross-border trading of virtual assets via peer-to-peer (P2P) transaction facilitated by advanced blockchain technology (Nakanoto, 2008). It seems that constraints and frictions in the arbitrage capital flow have led to market segmentation and significant, persistent price deviations between countries. However, there has not been a systematic analysis of the arbitrage trading across borders and the price deviation between countries due to the lack of transaction data in the virtual asset market. This paper attempts to fill this gap in the previous studies. In this study, daily trading data from September 2017 to December 2022 for virtual assets such as Bitcoin(BTC), Ethereum(ETH), Ripple(XRP), Cardano(ADA), and Dogecoin(DOGE) were used. For each coin, the price deviations between the KRW domestic and the USD international market were calculated by subtracting the KRW/USD spot exchange rate from each coin's exchange rate, which is the ratio of its KRW closing price to its USD closing price on the same trading day. Subsequently, a price disparity index was constructed by extracting a common factor from the price deviations of each coin using principal componant analysis(PCA) methodology. This study examined the time-series characteristics of the disparity index and the economic factors related to the index. Our analysis showed that the disparity index co-moved with the KRW price index, indicating that price deviations occur during periods of a rapid appreciation in the KRW coin market. The disparity index increased significantly after the implementation of a new regulation such as the Travel Rule, implying that frictions in the arbitrage activities lead to a market segmentation and price deviations across countries. In the multi-variate regression analysis, where the price disparity index was regressed on cryptocurrency market sentiment variables, financial market variables, commodity and stock market variables, the disparity index was closely related to investor sentiment in both the KRW and USD coin market, as well as to the movement of international financial markets, while showing no significant relationship with commodity and stock markets. Next, for each coin, the idiosyncratic price deviation was extracted by subtracting the disparity index from each coin's price deviations. The unique price deviations between the KRW and the USD market observed in individual coins were influenced by demand factors specific to each coin, unlike the disparity index. Specifically, the idiosyncratic price deviations on the previous day, daily returns, and KRW trading volume exhibited positive relationships with idiosyncratic price deviations in the four coins, and these results were maintained even after controlling for other variable. Meanwhile, using the daily change in price deviation as a proxy variable, this study divided the entire sample into two groups: one estimated to have arbitrage trading and one without, and examined whether arbitrage trading contributes to resolving the price disparity. The sample estimated to have no arbitrage trading showed a higher Kimchi premium than the sample estimated to have arbitrage trading, indicating that arbitrage transactions contribute to resolving price deviations between the KRW and the USD market. The sample without arbitrage trading showed larger KRW trading volume and lower Amihud measure compared to the sample with arbitrage trading, exhibiting a stronger tendency towards momentum trading that follows price deviations, rather than engaging in contrarian trading for arbitrage purposes.

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We investigate the impact of price limit expansion on stocks’ realized volatility, uniquely integrating both magnet effect and correction effect into our model. Our findings reveal that price limit expansion may increase or decrease stock volatility, with the magnet effect and stocks’ inherent volatility levels as primary driving forces, and the correction effect playing a minor role. Typically, a decrease in volatility occurs when a stock’s inherent volatility is moderate (i.e., neither too high nor too low), while an increase takes place when it is relatively high. We offer an insightful explanation of these contrasting behaviors in relation to the magnet effect and stocks’ inherent volatility.

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This study examines the chronology of regulations and policy implications for two features embedded in convertible bond (‘CB’) contracts: the option to adjust the conversion price downwards when the stock price falls (i.e., the ‘refixing option’) and the call option designatable to a third party (i.e., the ‘call option’). We provide the summary of this study as follows. First, we investigate the change in legal regulations regarding refixing options. CBs with the refixing option emerged in the late 1990s. In the early 2000s, the Financial Services Commission (‘FSC’) recognized a problem that the refixing option dilutes the interest of existing shareholders as the stock price falls and thus enacted a rule for setting the lower limit of the conversion price. However, the problem persisted. In 2021, the FSC revised the rule, requiring an upward adjustment, following a prior downward adjustment, to the conversion price, prompted by an increase in the stock price. The revised rule is applicable to applicable to privately-placed CB. Under the revised rule, the cap for the upward-adjusted conversion price is allowed to be set lower than the initial conversion price. Thus, the rule does not effectively eliminate the refixing option. We believe that strengthening the regulation of refixing options is necessary. We also examine the accounting issues for refixing options. After the adoption of the Korean International Financial Reporting Standard (‘K-IFRS’) in 2011, conversion rights (‘CR’) are recognized as a derivative liability and should be measured at fair value in every reporting period. This accounting treatment may lead to significant valuation losses for CR and an increase in liability when stock prices rise. In extreme cases, certain firms face the risk of delisting from the exchange. To address this issue, in 2022, the Korea Exchange (‘KRX’) revised a listing maintenance rule for screening criteria for delisting. The revised rule excludes valuation losses on CR due to refixing options from pre-tax income. In accordance with the KRX rule, the Korean Accounting Standards Board amended the accounting standard, which mandates firms to disclose valuation gains and losses on financial liabilities with refixing options separately from pre-tax income. Another issue with the accounting treatment for refixing options is that some treat CR as debt based on K-IFRS, while others treat CR as equity based on the Financial Supervisory Services(‘FSS’)’s interpretation on the accounting for refixing options. We believe the regulators should address the issue on this interpretation. Next, we examine the change in legal regulation of call options. In 2013, CBs featuring call options emerged to circumvent the legal prohibition of detachable BWs, which are allegedly utilized to strengthen the controlling power of the largest shareholder. The issue with CBs featuring call options is that the issuer designates call option recipients (mainly, the largest shareholders) only when the stock is convertible, thereby enabling them to purchase stock at a strike price lower than the prevailing market price. In 2016, when the market became aware of issues of CBs featuring call options, the FSS modified the disclosure format of CB issuance. But this approach proved ineffective. In 2021, the FSC implemented rules to impose a limit on the exercise of call options by the issuer's largest shareholder up to the ownership rate prior to the issuance of CB and to require issuers to provide detailed disclosure on the exercise of call options in both publicly and privately-placed CB. However, the rules do not effectively address the problem that exclusive benefits from call options are given only to those designated by CB issuers, and not to other shareholders. Another issue with CBs featuring call options pertains to issuers’ own CBs, which is not retired after redemption but remains resalable. The resale of issuers' own CBs is economically similar to CB featuring call options. However, considering that the resale of issuers' own CBs is subject to more misuse than call options, additional regulation on it is necessary. We investigate the accounting treatment for call options. Most firms had not accounted for call options in CB since their emergence in the market. In 2022, upon recognizing this fact, the FSC issued a supervisory guideline requiring issuers to recognize call options as financial assets separately from CBs in their financial statements. However, the guideline is limited to call options only. Under the current accounting standard, issuers' own CBs are not recognized in financial statements. We believe regulators need to mandate issuers to disclose more information about their own CBs. Lastly, this study discusses the applicability of the 2021 regulation to the following convertible instruments: bond with warrants (‘BW’), exchangeable bond (‘EB’), convertible preferred stock (‘CPS’), and redeemable convertible preferred stock (‘RCPS’). BWs are subject to the regulation for CB as well. However, EBs are not subject to the regulation. Particularly, a set of EBs exchangeable to the issuer's treasury stock needs to be regulated at a level comparable to that of CBs due to their economic equivalence. In 2023, the FSC revised the rule to extend the 2021 regulations to include CPS and RCPS. Nevertheless, the regulations for CPS and RCPS remain less sophisticated than those for CB and BW. Overall, our study suggests that further regulatory measures for the two options are warranted to secure the fairness of the market.

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Prior studies show that momentum is induced because investors underreact to information when anchored by the 52-week high (52WH). We propose the possibility that investors’ anchoring bias could vary over time. Accordingly, we develop an alternative momentum strategy, namely thedynamic 52WH (denoted as D52WH) momentum,that buys (short sells) stocks with the nearness to the 52WH ranked in the top (bottom) 10% of the historical distribution. We show that the D52WH momentum not only generates significant profitability but also outperforms the 52WH momentum. In addition, amajor advantage of the D52WH momentum is that it experiences considerably weaker momentum crashes. Further evidence shows that the D52WH momentum is more pronounced under limited investor attention and lower shorting activities, thus confirming the underreaction-driven return predictability implied by the anchoring bias.

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Banks’ credit management impacts the terms of lending, and diversification of loan portfolios and thus affects the total loan delinquency ratios. We find that the rising shares of recurring payment mortgages, one of the policy measures of restructuring mortgage loans since the second half of 2015, made positive contributions to banks’ asset management by improving credit management in the process of evaluating borrowers’ credits. Banks differentiated lending interests for mortgage borrowers even when their bank-issued credit ratings were the same in consideration of the differences in credit ratings that the credit bureaus (CB) issue. Using individual bank-level monthly data from September 2015 to May 2018, to explain the total loan delinquency ratios, we consider the banks' lending behavior on small and medium-sized enterprise (SME) loans, recurring payment mortgages, one-time payment mortgages, personal loans, and personal lines of credit. During the period, the Bank of Korea maintained its base interest rate between 1.25 percent and 1.75 percent and we focus on the share of high-interest loans (over five percent) for relatively low-credit borrowers. We also include the business cycle, return on financial asset (KOSPI), changes in the foreign exchange rate (KRW/USD), and real interest rate that could affect borrowers’ payment ability. We adopt the system-GMM estimation to correct bias caused by the problem of endogeneity as financial ratios can be affected simultaneously by the bank management. The system-GMM has some advantages over the fixed effect model since it deals with the omitted bias for some time-varying variables such as the CEO’s trait. Among fifteen commercial banks, nine banks experienced CEO turnovers during the period. Macroeconomic variables are significant determinants of the banks’ total loan delinquency ratios. A rise in economic activity, an increase in stock prices, and domestic currency depreciation against USD can positively impact bank asset quality. However, a rise in real interest rates can worsen bank asset quality. Banks’ total loan delinquency ratios could be varied by varying both the composition of the loan types and the credit structures of the banks’ loans. While the increase of high-interest loans for non-prime borrowers in new SME lending raised the total loan delinquency ratios, the increase of high-interest loans for non-prime borrowers in new recurring payment mortgages lowered the total loan delinquency ratios. This is due to the differences in the credit structures of non-prime borrowers of high-interest loans between SME loans and mortgage loans. Moreover, we analyze how the banks determine the lending interest rates for household loans and SME loans as it matters to asset quality. The Korea Federation of Banks provides the bank-issued credit ratings of household loan borrowers into five categories, from 1~2 grades at the top to 9~10 grades at the bottom as well as the CB credit ratings. The stages of bank-issued credit ratings of SME loans are 1~3 grades at the top, grade 4, grade 5, grade 6, and 7~10 grades at the bottom. For household loans, even when the bank-issued credit ratings are the same, we find a fair amount of heterogeneity in the lending interest rates depending on the differences in borrowers’ CB-issued credit ratings. This implies that banks’ credit management has improved since the second half of 2015. We especially focus on low-credit borrowers of mortgage loans whose bank-issued credit ratings are 7~10 grades. There exist noticeable differences in the borrowers’ CB credit ratings depending on the types of mortgage loans. For low-credit borrowers of high-interest mortgage loans, the average CB credit quality of the recurring payment mortgages is superior to that of the one-time payment mortgages. This explains the reason why the rising shares of high-interest recurring payment mortgage loans lowered the total loan delinquency ratios of commercial banks. Local banks are more active players in the process of this diversification than nationwide banks. For SME loans, the bank-issued credit ratings significantly affect the lending interest rates. When it comes to the credit qualities of borrowers, the default probabilities of the non-prime borrowers of SME loans are more widely distributed with higher upper and lower bounds than those of household loan non-prime borrowers. The average default rate is much higher in SME loans compared to household loans, which reinforces the importance of credit structures in bank-loan diversification and explains the reason why rising shares of high-interest loans in new SME loans worsened the bank asset quality. Improving the bank’s management efficiency in SME loans could benefit the banks as it provides some opportunities to improve banks’ asset quality in the process of bank-loan diversification in efforts to lower the risk level associated with their bank-loan portfolios. Banks adjust their lending interest rates in consideration of return on asset (ROA), costs, and other factors as well as borrowers’ credits. Our findings suggest that bank-loan portfolio diversification and efficient bank credit management together can reduce the bank’s total delinquency ratios.

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The level of pension assets that can cover pension liabilities in firms that operate defined benefit (DB) pensions and the management of pension assets is important information that affects the valuation of the companies in the capital market. This study analyzed the effect of the underfunded risk of DB pension plan on stock returns for firms listed on the Korea Exchange. We examined the relationship between the pension funding ratio and the stock return through multivariate analysis including firm characteristic variables for companies that adopted the DB pension system from 2013 to 2022, when the minimum funding ratio of plan assets for DB was gradually raised in the Employee Retirement Benefit Security Act(ERBSA). The main results of this study are summarized as follows. First, during the sample period, pension funding ratios increasd in accordance with the minimum funding ratio provisions specified in the ERBSA. In addition, the level of the funding ratio and the behavior of asset allocation focused on safe assets showed strong persistence throughout the sample years. Second, for portfolios sorterd by the pension funding ratio, the alpha (risk-adjusted excess return) from the factor model was estimated to be a statistically significant negative sign in the portfolio with high funding ratio, while no statistical significance was found in the portfolio that did not meet the minimum funding ratio. These results imply that the stock prices of firms that meet the minimum funding ratio exhibited the tendency of overvaluation in the market. Furthermore, it was confirmed that such pricing errors are a dominant results in companies that met the minimally required funding ratio but did not meet the overfunding ratio. Third, the robustness of the portfolio analysis results estimated by the factor model was confirmed through panel regression analysis. As a result of the analysis, firms that do not meet the minimum funding ratio show higher stock returns as the funding ratio is lower (the higher the underfunding risk), but firms that achieve the minimum funding ratio do not explain changes in returns. However, even if the minimum accumulation ratio is achieved, companies that do not fully overfunding ratio show an increase in stock returns as the funding ratio increases. These results support the analysis of the factor model earlier, and imply that investors neglected the underfunded risk for firms that have met the minimum funding ratio but do not fully cover the pension liabilities, so the underfunded risk is not reflected in stock price.

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