Korea Capital Market Institute

The Korean Target Date Fund (TDF) market has expanded substantially over the past decade, growing from KRW 67.2 billion in 2016 to KRW 16.6 trillion in 2024. The majority of TDF assets are held within retirement pension accounts, with Defined Contribution (DC) plans and Individual Retirement Pensions (IRP) serving as the primary channels of utilization. This development suggests that TDFs have played a meaningful role in retirement asset management in Korea, particularly as a structured investment option for long-term savers.   Despite this expansion, the introduction of the Default Investment Option (DIO) system in July 2023 has had a limited impact on increasing TDF utilization to date. Structural features of the current system—such as the inclusion of a large share of principal-protected products and the requirement that participants actively select default options—have constrained the automatic allocation function that default arrangements are intended to provide. At the same time, the competitive landscape of retirement asset management has evolved rapidly, with exchange-traded funds (ETFs), robo-advisors, and industry-wide retirement pension funds emerging as alternative investment vehicles.   An empirical analysis of TDF performance reveals several notable characteristics. First, risk exposure and return profiles vary systematically across target dates, reflecting differences in asset allocation paths over the investment horizon. Second, even among TDFs with the same target date, performance dispersion and persistence are observed, indicating meaningful variation in investment strategies across asset managers. These findings suggest that competition and differentiation among TDF providers are actively shaping market outcomes, rather than TDFs operating as a homogeneous product category.   In terms of costs, TDF expense ratios are generally lower than those of traditional mutual funds but remain higher than those of ETFs and other low-cost alternatives. Moreover, expense ratios tend to increase with longer target horizons, reflecting structural features of TDF design. Importantly, the relationship between costs and performance is not uniform: higher-cost TDFs do not necessarily underperform lower-cost funds, underscoring the need to evaluate fees in conjunction with investment strategy and outcomes rather than in isolation.   Overall, the findings indicate that the key policy issue is not whether TDFs should continue to grow, but under what institutional and market conditions they can function effectively as an automatic asset allocation tool within the retirement pension system. Improvements in the design and objectives of the default investment framework, greater transparency in cost structures, enhanced comparative disclosure, and clearer evaluation of performance relative to risk are essential to strengthening the role TDFs can play. Within a competitive retirement investment environment, TDFs represent one of several viable options for supporting long-term, life-cycle–based asset allocation, provided that the surrounding regulatory and institutional conditions are appropriately aligned.

Cross-border transactions in blockchain-based cryptoassets are rapidly expanding in ways that complement or potentially substitute traditional financial infrastructure. According to IMF estimates, the volume of cross-border cryptoasset transactions reached approximately USD 2.5 trillion as of 2024. After a period of rapid expansion in 2021 followed by a subsequent correction, cross-border activity has entered a renewed growth phase led primarily by stablecoins. In particular, recent cross-border transactions have moved beyond investment-driven flows centered on store-of-value cryptoassets, with an increasing share of activity reflecting actual use cases such as payments and remittances conducted via stablecoins. Empirical evidence and the existing literature suggest that store-of-value cryptoassets are highly sensitive to the global financial cycle and tend to behave as typical risk assets, whereas stablecoins and small-value cryptoasset transactions are more closely linked to real-economy factors such as remittance costs, exchange rate volatility, and the intensity of capital controls. Moreover, in some jurisdictions, stablecoins have been observed to function as de facto substitutes for foreign currency or as channels for regulatory circumvention in cross-border capital movements. At the same time, discussions surrounding wholesale CBDC–tokenised deposit–based settlement architectures, such as the BIS’s Project Agora, indicate that international coordination efforts to integrate private-sector innovation into the formal payment system are gaining momentum. These developments point to a gradual shift toward a more layered and networked structure in the international monetary and foreign exchange system. For Korea, the growing use of stablecoins and on-chain cross-border transactions raises important policy challenges, including ensuring consistency within the existing foreign exchange and capital account regulatory framework, enhancing real-time monitoring capabilities, modernising domestic payment infrastructure through tokenised deposits and CBDC-based systems, and engaging strategically in international discussions on payment and settlement standards. Accordingly, Korea needs to move beyond a narrow focus on whether to regulate digital assets and instead formulate policy from a broader perspective that redefines the role of the won and domestic financial institutions within an evolving international payment environment shaped by digital liquidity.

This study empirically analyzes the investment value of stock recommendations and target prices issued by Korean stock analysts. Using portfolios constructed from analysts’ recommendations and target prices announced between 2000 and 2024, the study examines their abnormal returns and obtains the following results. First, stocks with favorable recommendations or high implied expected returns embedded in target prices exhibit positive abnormal returns, confirming the investment value of analysts’ recommendations and target prices. Second, stock recommendations and target prices possess independent investment value, and combining the two pieces of information yields higher abnormal returns. Third, the investment value of recommendations and target prices is relatively greater for small- and mid-cap stocks. Fourth, the investment value of recommendations and target prices is no longer observed after 2013. The disappearance of the investment value of analysts’ recommendations and target prices is attributed to a decline in analysts’ information advantage and a weakening of the discriminatory power of the information they provide. Following the CJ E&M incident in 2013 and the subsequent tightening of regulations on market abuse, analysts’ channels for acquiring private information were constrained. As a result, stock recommendations became increasingly concentrated on ‘buy’, while both the cross-sectional dispersion and the time-series variability of implied expected returns declined. These findings suggest that a reduction in the information content of analysts’ recommendations and target prices contributed to the erosion of their investment value. As producers and intermediaries of information and as monitors of the market, analysts’ economic role fundamentally rests on their information advantage, analytical capability, objectivity, and accuracy. Therefore, the disappearance of the investment value of recommendations and target prices due to diminished information advantage and weakened discriminatory power raises concerns regarding the essential function of analysts. Going forward, analysts should enhance the value added of their information by utilizing diverse alternative data, adopting new analytical techniques, and differentiating their areas of analysis, while also reducing optimistic bias through stronger independence and improved performance evaluation criteria. Policymakers, in turn, should improve the quality of disclosure, strengthen formal communication channels between listed firms and analysts, and promote the disclosure of non-financial information to enhance the information environment of the stock market.

Since the outbreak of COVID-19, Korea’s capital market has seen a rapid expansion of its retail investor base, with a growing number of individuals actively investing in overseas assets and structurally shifting from a domestic-equity-centered focus to broader global portfolios. Yet, there has been little account-level empirical evidence on how individuals conduct overseas direct investment, how foreign asset allocation reshapes their realized returns and risk, and through what channels characteristics such as age, gender, and asset size affect performance. To address this gap, this report reconstructs individual portfolios that include both domestic and foreign listed stocks and ETPs, using detailed account-level holdings and transactions for roughly 100,000 investors at a major securities firm between 2020 and 2022, and analyzes their investment behavior and outcomes in an integrated way.  The results show that, although domestic equities remain dominant overall, younger investors in their 20s and 30s and high-wealth investors hold significantly higher shares of foreign assets and are especially active in overseas ETPs. Male investors tend to hold fewer positions but concentrate more heavily in higher-risk assets compared with women, while high-wealth investors more often build systematic global portfolios centered on foreign ETFs. By contrast, small-scale investors frequently trade high-leverage, derivative-type foreign ETPs with limited capital. Even when the number of holdings is large, effective diversification is often weak, with assets clustered in a few names and specific U.S. stocks and ETPs, resulting in structures that superficially resemble international diversification but in practice are highly dependent on the U.S. market and leverage/inverse products, exposing investors to elevated volatility and uncertainty. In terms of performance, overall returns across domestic and foreign assets were generally weak relative to the broader equity market over the same period. After accounting for trading costs, more investors incurred losses than realized gains, and only a small minority meaningfully outperformed benchmark indices. While many participants in overseas markets did see improvements in portfolio returns and risk-adjusted performance, roughly half of them still failed to achieve satisfactory outcomes. A quantile analysis of performance drivers reveals strong heterogeneity: for low-performing investors, excessive trading without sufficient experience, concentration in a small number of stocks, and aggressive risk-taking further depress returns, whereas for top performers these same traits are not necessarily harmful and can sometimes be linked to outperformance. These findings indicate that overseas investment can expand diversification opportunities and improve results for some investors, but also embeds structural risks through excessive concentration and frequent trading of high-risk listed products.  Policy-wise, it is notable that relatively stable and favorable outcomes are observed when investors use savings-type accounts to invest long term and consistently in broadly diversified instruments such as plain-vanilla ETPs and overseas equity ETFs. This suggests the need to promote wider use of long-term, diversification-oriented accounts such as IRPs and ISAs, strengthen tax incentives for long-horizon investing, and tighten oversight of product design, disclosure, and sales practices for high-risk products including leverage/inverse ETPs. For young and small-scale investors in particular, expanding tailored financial education and digital, intuitive risk-warning systems is essential. Ultimately, enabling individuals to rely more on pooled investment vehicles and advisory or wealth-management services—rather than bearing complex investment decisions entirely on their own—will support both the financial soundness of households and the sustainable development of Korea’s capital market.  

Artificial intelligence (AI) is driving transformative change across the financial investment industry. The global AI market is projected to grow from USD 189 billion in 2023 to USD 4.8 trillion by 2033, and the financial sector has emerged as one of the most active adopters of AI technologies. In Korea as well, AI-related patent filings in the financial sector have surged rapidly, increasing from 20 cases in 2015 to approximately 380 in 2023—a nineteenfold rise—reflecting accelerating efforts to integrate AI into financial services. As expectations grow that AI will spur innovation across industries, it is essential to understand how AI can actually be applied in the financial investment industry based on objective data. In this regard, patent data serve as a highly valuable analytical resource. Patent data cover a broad range of industries, and each patent document provides detailed information on the data used, AI models employed, and technical specifications. Accordingly, patent analysis can go beyond identifying AI technology trends to forecasting the future development path of the financial industry and deriving meaningful policy implications. This study systematically analyzes the potential applications of AI in the financial investment industry using patent data. The results show that AI functions applicable to financial investment activities have expanded across diverse areas, including data analysis, anomaly and fraud detection, customer service, and report generation, with expected gains in operational efficiency and cost reduction. In particular, B2B startups are actively developing AI-based solutions tailored to financial services, suggesting that financial institutions’ reliance on external technology providers is likely to increase. The applicability of AI varies significantly across business segments within the financial investment industry and across different stages of each segment’s value chain. In repetitive and highly structured tasks, where data are well-organized and procedures are clearly defined, AI adoption is relatively straightforward. In contrast, in tasks that are unstructured and require contextual interpretation and judgment, AI applicability is lower and the expected benefits of adoption are more uncertain. Data accessibility is also a critical determinant of AI adoption: areas where data acquisition, processing, and sharing are smooth tend to exhibit higher concentrations of related patents. Moreover, AI adoption remains limited in high-risk areas, as AI errors in such domains can lead to large-scale financial losses or legal disputes. To overcome these limitations, three key policy directions can be proposed. First, regulatory sandboxes and pilot programs should be expanded to enable experimental AI adoption not only in routine tasks but also in unstructured and high-complexity activities. Such initiatives can support risk management while also generating empirical evidence for future policymaking. Second, data infrastructure should be upgraded at the national level to embed security and regulatory compliance capabilities and to establish support systems that facilitate data collaboration among financial institutions. Third, comprehensive financial AI guidelines should be developed, encompassing AI governance, principles of explainability, and third-party risk management, thereby reducing the psychological and institutional barriers that hinder active AI adoption by financial institutions. While patent analysis provides a forward-looking perspective on the potential integration of AI into the financial investment industry, case studies of overseas financial institutions offer practical insights into the processes of AI internalization and commercialization. These international cases demonstrate that real-world AI adoption is shaped not only by task structure, data accessibility, and risk levels, but also by three additional dimensions: the maturity of technologies and services within the industry, return on investment (ROI), and infrastructure constraints. Accordingly, effective AI adoption in the financial investment industry requires a phased approach that clearly recognizes both the potential and the limitations of AI while carefully weighing expected returns on investment. First, adoption strategies should be formulated based on the maturity of technologies and services within the industry, enabling rapid commercialization in mature areas while managing risk through pilot implementations in more uncertain domains. Second, investment priorities should be set with a strong focus on ROI—concentrating in the short term on areas that offer cost reductions and efficiency gains, while strategically fostering competitive technologies such as risk analysis and personalized advisory services over the long term. Third, continuous investment in data quality and computing infrastructure is essential to enhance AI performance and reliability, ultimately reducing operating costs and enabling stable service delivery. In conclusion, AI has already become a core strategic asset in the financial investment industry. Effective utilization of AI will require coordinated efforts to support AI experimentation by financial institutions, upgrade data infrastructure, establish robust ethical and accountability frameworks, and pursue gradual, practice-oriented diffusion strategies. With such a systematic foundation in place, Korea’s financial investment industry can leverage AI to achieve both innovation and stability, while further strengthening its global competitiveness.

The Korean public fund industry has undergone significant structural changes amid the rapid growth of Exchange-Traded Funds (ETFs). Traditional mutual funds—once the main driver of market expansion—have seen stagnating growth and declining market presence, while ETFs, with their low fees and trading convenience, have surged to surpass public mutual funds in both net assets and market share around 2022. Since then, the overall growth of the collective investment market has been led by ETFs, widening the gap between the two sectors. This transition highlights ETFs’ position as an attractive investment vehicle but also signals the weakening competitiveness of traditional public funds. However, ETFs’ index-linked structure inherently limits portfolio diversity and active management. Even “active ETFs” are typically designed to maintain high correlations with benchmark indices, which constrains their ability to provide meaningful diversification or differentiated performance. In contrast, traditional public funds can actively deviate from benchmarks, engage in stock selection based on unique strategies, and expose investors to distinct sources of risk and return. Such flexibility allows them to pursue portfolio differentiation strategies that align with diverse investor preferences. This study focuses on portfolio differentiation as a sustainable growth strategy for public mutual funds amid intensified competition with ETFs. Its objective is to empirically assess how differentiated portfolio strategies—reflecting each fund’s unique management philosophy and style—affect (1) fund flows (investor subscriptions and redemptions) and (2) the market share of asset management firms. The analysis seeks to objectively evaluate how managerial originality and investment capability translate into performance and competitive outcomes in the industry, providing policy insights for enhancing the competitiveness of Korea’s mutual fund market. Using data from 2014 to 2024, the study quantifies the degree of portfolio differentiation for each fund, based on the overlap between its holdings and comparable ETFs. Differentiation indices are constructed by fund type (equity, bond, and fund-of-funds), and panel regression models are estimated to analyze the impact of differentiation on subsequent fund inflows and changes in asset manager market share. Control variables include fund returns, fees, commissions, and fund and firm size, while dynamic panel models (GMM estimators) are employed to address endogeneity concerns and ensure robustness. The main findings are as follows. First, greater portfolio differentiation significantly enhances fund inflows: funds with lower overlap with ETF holdings attract higher levels of new investment. Second, differentiation also contributes positively to asset managers’ market share growth. Firms that maintain distinctive portfolios—rather than replicating ETF-style compositions—show statistically significant increases in market share over time. The policy implications are clear. Promoting portfolio differentiation can strengthen the competitiveness of public mutual funds and yield positive spillover effects across the financial ecosystem. For investors, differentiation expands investment options and improves utility through better risk-return matching. For the industry, it mitigates excessive price competition and concentration in a few large firms, fostering a healthier, more diverse market structure.