Quantum computing is an emerging field that offers the potential to overcome the limitations of classical computers and is gaining attention as the next-generation computing platform. With the growth of interest in quantum computers, the competition to develop more powerful systems has intensified, with leading companies such as IBM, Google, Intel, Microsoft, and Samsung investing in the technology. They are working towards creating more advanced and practical quantum computers that can lead to new applications in various fields. Consequently, quantum computing has become a game-changer in recent years, with applications in cryptography, simulation, machine learning, and data retrieval. Quantum computing is also beingapplied to finance, giving rise to a new field known as quantum finance. This offers a unique way of processing data and information that is different from classical computing technologies. With its ability to perform complex optimization problems faster and more accurately than classical computers, quantum computing has significant potential in finance. Quantum finance has numerous advantages and limitless potential applications. For instance, it can help financial institutions better manage complex financial products like derivatives and structured products. By providing more accurate risk assessments, portfolio optimization, and trading strategies, quantum finance can enhance the efficiency and accuracy of financial markets. This enables financial institutions to make informed decisions, reduces the likelihood of financial loss, and ultimately benefits both the institutions and their customers. Quantum computing can also reduce the time and cost of complex financial calculations, such as Monte Carlo simulations. This is crucial for financial institutions, as the savings can be reinvested in other areas of the business. Additionally, quantum computing has the potential to increase the stability of financial markets by reducing market volatility and increasing investor confidence. The implementation of quantum finance requires cooperation between the financial sector and the government. Financial institutions should invest in quantum financial technologies and create the necessary infrastructure and regulations. Governments should also provide funding and support through regulation to encourage the development of quantum finance. Financial institutions, governments, and academia must work together to advance the field and maximize the potential of quantum computing in finance. However, implementing quantum finance requires expertise in both quantum computing and finance. Financial institutions need to secure human resources, such as quantum computing experts, to successfully implement quantum finance. This requires close collaboration between the financial sector and academia to develop the necessary skills. In conclusion, the potential benefits of quantum finance are vast, and its impact on the financial industry could be significant. By enhancing the efficiency, accuracy, and stability of financial markets, quantum finance has the potential to revolutionize the industry and benefit both financial institutions and their customers. It is crucial that financial institutions, governments, and academia work together to invest in and support the development of this emerging field. By exploring the potential and implications of quantum finance, this paper highlights the importance of supporting its growth, which has the potential to shape the future of finance and quantum computing.

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The retirement pension system in the Korean market was introduced in 2005. The goal of the retirement pension system is to serve as a stable retirement income safety device under the multi-pillar pension system. As of the end of 2022, the accumulated pension assets is reached about 300 trillion won, but it is shallow compared to those of advanced pension countries and the OECD average. The shortcut to accumulating pension assets is improving investment performance through asset allocation and long-term investment. However, the current Korean retirement pension system is criticized for not achieving the effect of asset allocation due to excessive concentration on safe assets, which is an important cause of poor investment performance. This study analyzes the asset allocation of the pension funds of Korean firms adopting the defined benefit (DB) pension plan. For this study, data was constructed by manually collecting asset allocation data of pension funds for 526 firms listed on the KOSPI market during the sample period from 2013 to 2019. This study is the first to analyze the asset allocation behavior of retirement pensions for the Korean listed companies adopting the DB plan. The main empirical results are as follows. First, the average share of safe assets on total pension assets is about 82%. This result means that the Korean listed companies are investing most of their retirement pension assets in safe assets. In addition, this asset allocation behavior centered on safe assets continues despite the rapid increase in the size and the pension funded ratio (PFR) of pension funds during the sample period. Second, rebalancing between safe and risky assets during the sample period is hardly performed. Strategic asset allocation based on long-term target return and risk or tactical asset allocation reflecting short-term changes in market conditions is not being performed appropriately. Third, the relationship between the PFR and the share of safe assets appears in an inverted U-shape. In the group of under-funded firms with a low PFR, the higher the PFR, the higher the proportion of investment in safe assets. On the other hand, in the group with a high PFR, the higher the PFR, the higher the investment ratio of risky assets. These results mean that the asset allocation behavior of retirement pensions in the Korean listed companies adopting the DB plan supports the risk management hypothesis rather than the risk transfer hypothesis. However, as shown in the analysis of the characteristics of under-funded companies, because the change of risky asset allocation ratio is insignificant and the size of retirement pension assets is small, it has limitations in judging that it is generally supported. Additionally, this study shows that establishing and providing a national database containing information on asset allocation for retirement pensions is academically and practically urgent.

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The relationship between idiosyncratic volatility and investors’ trading weight is studied from February 2000 to June 2022, targeting stocks listed in the KOSPI and the KOSDAQ. The idiosyncratic volatility puzzle is examined according to the individual investors’ total trading weight(TW), net buying TW, intra-individual TW, and buying (selling) TW. The individual total TW has a positive (+) effect on total volatility(TV), systematic volatility, idiosyncratic volatility(IV), and especially IV²/TV². The IV puzzles appear differently in the KOSPI and the KOSDAQ. In the KOSPI, we find that statistically significant high risk-high return results, which coincide with conventional financial theory rather than the IV puzzle, in some portfolios with a low individual investors’ total TW and some portfolios with a low intra-individual TW, respectively. We newly find that the intra-individual TW can cause the IV puzzle through these results.

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This paper presents a comprehensive review of the behavioral finance literature on Korean financial markets, published recently in Korean academic journals. Our survey of behavioral finance in Korea is the follow-up work of Kim and Byun (2011). As part of the 2010 knowledge database project by the Korean Finance Association, we have previously reviewed behavioral studies in Korea. Compared to the environment at the time of the previous survey, most academic journals eagerly accept research articles from behavioral finance perspectives. Behavioral corporate finance has produced several studies on investor sentiment and managerial overconfidence. However, finding research on experimental tests or survey analyses from Korean finance journals remains challenging. This area requires interdisciplinary work with psychology researchers. Moreover, research methodologies using AI or machine learning could be more frequently used in future studies.

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This study surveys prior studies on corporate social responsibility (CSR) in Korean firms that have been conducted between 2000 and the present. It introduces how Korean researchers define CSR conceptually and develop CSR-related theories. We then discuss how CSR affects Korean firms and stakeholders by comprehensively reviewing prior studies. To this end, we collect and categorize CSR-related papers by subtopics, such as CSR concept, firm value, cost of capital, risk, compensation and ownership structure, and review the research results by topic. We then also review studies on responsible investment (RI). Lastly, we suggest topics and directions for future research.

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This paper develops a theoretical model to derive optimal pension funding ratios of defined benefit(DB) pension plans, and discusses their characteristics and empirical implications. The main results are as follows. First, DB firms’ optimal pension funding ratios are positively associated with their operating performances and corporate tax rates, while negatively associated with bankruptcy costs. Second, pension funding and financial debt service are inversely related each other, and DB firms have a certain degree of discretion in choosing their optimal pension funding ratios. Third, DB firms’ pension funding ratios are expected to show negative relationship with the firms’ debt ratios in the empirical tests, but intensity of their relationship becomes weaker as the sample firms in the tests get more diverse. Fourth, pension funding ratios are expected to show positive relationship with both firm value and operating performance variables, but negative relationship with financial distress variables. Their intensity becomes stronger when the proportion of large firms increases. Finally, theoretical results and predictions of the paper are largely consistent with the findings of existing empirical studies.

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This study aims to examine the influence of investor sentiment in the cryptocurrency market on the mean-variance relationship of Bitcoin. We find that Bitcoin expected excess return is positively related to conditional variance of Bitcoin return daily during the period of Extreme Fear but unrelated to conditional variance during the periods of Fear, Neutral, Greed, and Extreme Greed. Our findings are consistent with a distortion of a positive mean-variance tradeoff by investor sentiment. We also find that a negative relation between returns and contemporaneous innovations of conditional variance is only significant in the period of Extreme Fear. Moreover, the findings are robust, even after controlling for the impact of global factors determining Bitcoin price, and in Ethereum market, beyond Bitcoin market.

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This paper reviews the academic research on derivative products and derivatives markets in Korea published since 2010. We classify the literature into three main research areas: derivative securities markets, option pricing models, and risk management. Topics in the derivative securities markets section include the effects of an increase in the option contract multiplier, the price discovery function of derivatives markets, expiration-day effects, and the trading behavior and strategies of market participants. Next, in the section on option pricing models, we introduce theoretical modeling papers, empirical research on pricing models, implied moments, and the variance risk premium, which is derived from option prices. Thereafter, in reviewing the literature on risk management, we focus on the foreign exchange risk management of firms and the relation between risk management and firm value. Finally, we add three unique topics—equity-linked warrants, equity-linked securities, and credit default swaps—to consider the developments in derivatives markets over the past decade.

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This paper reviews the empirical evidence on payout policy in Korea over the last three decades. This study aims at providing the researcher with a comprehensive understanding of dividend policy by reviewing the theories and empirical evidence of dividend policy including tax-preference, information asymmetry and signaling hypothesis, agency costs and the free cash flow hypothesis, and catering theory of dividends. The theoretical and empirical research on dividends and stock repurchases has produced an extensive volume of literature. Despite decades of study, we have yet to understand completely the factors that influence dividend policy and how these factors interact. One of the reasons for the difficulty in resolving the dividend puzzle is that some researchers have strived to develop a universal, one-size-fits-all explanation, despite knowing that dividend policy is sensitive to factors like firm characteristics, market friction, corporate governance, and legal environments. Although not all of the pieces of the dividend puzzle may be in place, this paper features information that provides useful guidance for identifying the determinants of payout policy in the real world.

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