A stop-loss strategy is an investment strategy that automatically sells a stock that is suffering a loss when its price reaches a stop price. It is well known that investors actively use these strategies to protect against downward risk in the face of (ultra-) short-term volatility and drastically dropping stock prices. Since a stop-loss strategy uses algorithms to determine when the stock should be sold, investors do not have to follow the market constantly. Therefore, investors can control their behavioral biases and prevent losses in advance, and in practice this strategy is generally known to be useful in improving returns on investment. However, according to Kaminski and Lo (2014), the stop-loss strategy has different effects depending on the return-generating process the stocks follow. If stock returns follow a momentum or a regime-switching process, then a stop-loss strategy can increase portfolio profits and/or reduce volatility. However, if they follow a random-walk or a mean-reverting process, then a stop-loss strategy can lower portfolio profits. This paper analyzes the performance and effectiveness of stop-loss strategies in the Korean stock market by analyzing a general stop-loss strategy and a specific stop-loss strategy. For the general stop-loss strategy, we use the one studied by Lei and Li (2009). For the specific stop-loss strategy, we use the Active Risk-Management Phase 3 of the Korea National Pension Service (NPS). We analyze the effects of the general stop-loss strategy on the stocks listed on the KOSPI and KOSDAQ markets from July 1996 to June 2016. We use block bootstrapping to compare the performances of the stop-loss strategy to the buy-hold strategy, and calculate the efficiency of the stop-loss strategy by calculating the stop-loss premium. To analyze the specific stop-loss strategy embedded in the NPS’s Active Risk-Management Phase 3, we analyze the NPS’s investment universe from January 2011 to December 2017. We compute the cumulative rate of returns after the entry of the Active Risk-Management Phase 3 under an algorithm simulation. Ever since the 2008 global financial crisis, the Korean stock market, like other leading global markets, has experienced ultra-short-term volatility and sudden liquidity droughts in the absence of any material news. Stop-loss orders are a basic risk-management tool under these circumstances. Despite these structural market conditions, the Korea Exchange (KRX) does not offer stop orders or stop-loss orders to investors. Therefore, it is important to determine whether stop-loss strategies can help control the downside risk to investors. This study also addresses how the interaction between the structural conditions of the Korean stock market and the implementation of mandatory stock trading under the risk-management rules affect the investment strategy of the NPS, which is a timely and important topic. The results of our analyses are as follows. First, in terms of performance, we cannot confirm that a general stop-loss strategy is statistically superior to a buy-hold strategy, or vice versa. However, in terms of risk management, a general stop-loss strategy is more effective at reducing volatility than a buy-hold strategy. Second, 75% of the stocks that enter Phase 1 exit and return to a normal status within fourteen trading days. Phase 1 only involves enhanced monitoring of the stock, and stop-loss orders are not applied to these. When a stock enters Phase 2, a report is generated, but no specific action is mandated. Once a stock enters Phase 3, NPS is mandated to consider placing a stop-loss order. We find that in Phase 2 it is beneficial to observe whether the stock return becomes positive or remains stable over the ensuing 2~3 months (60 trading days) or 4~5 months (120 trading days). If the return continues to be positive or stable, NPS should continue to hold the stock and not place a stop-loss order. However, if the return remains negative in Phase 2, it is desirable to sell the stock without waiting for it to enter Phase 3. If a stock enters Phase 3 and NPS still holds it, it is desirable to sell the stock and to invest the sales proceeds in safe assets, and then repurchase the stock if and when it meets the re-entry threshold. Third, as the cumulative return after entering Phase 3 is often negative for up to 240 trading days, the stop-loss strategy does not seem to hurt returns by realizing transitory losses. Any possible increase in volatility, which results from the introduction of static VI or the increase of the price limit, does not appear to adversely affect the stop-loss strategy. Fourth, we find that the general stop-loss strategy in the Korean stock market does not improve performance. However, in the case of active risk management of NPS, it is desirable to sell the stocks prior to or on entering Phase 3. The difference between the two results appears to be largely due to the differences of the specific parameters of the stop-loss strategies. In the end, the effectiveness of stop-loss strategies critically depends on matching the parameters of the strategy to the conditions in the Korean stock market.

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Since the Korean currency crisis of 1997, Korean firms have followed the compensation system used in the U.S. With this shift, pay for executives has risen sharply and the pay multiple has increased. We investigate the effect of this increased pay multiple on the overall operating and stock performance of Korean firms. Our data comprise 15,438 firm-year observations in 1,745 non-financial firms listed on two Korean stock markets from 2004 to 2016. Researchers in the field of human resource management find that relative pay has greater relevance than absolute pay in shaping the behaviors or attitudes of lower-level employees. Accordingly, we conjecture that enlarged pay multiples have a negative effect on Korean firms, as Korea has a relatively more egalitarian culture and a less elaborate evaluation system. In addition, relative deprivation theory posits that employees feel deprived when they perceive that their executives are overpaid. Employees may accept that high pay for an executive is deserved if that executive has high managerial ability. However, the employees may feel that executives with low managerial ability are paid too much. We therefore estimate the managerial ability of executives by adopting the method suggested by Demerjian, Lev, and McVay (2012), and we divide our sample firms into high and low managerial ability groups. We hypothesize that the effects of pay multiple on firm performance differ according to whether the firms have high or low managerial ability. Our empirical results are as follows. First, pay multiple negatively affects the overall operating and stock performance of most Korean firms. This finding implies that most employees think their executives’ pay is unjustifiably high, and it should be reduced. This sentiment seems to support relative deprivation theory. Second, the negative impact of pay multiple occurs only in the low managerial ability group. In the high managerial ability group, increased pay multiples have a positive effect. This finding indicates that employees in firms with low-ability managers feel deprived because of their executives’ excessive pay, whereas employees in firms with high-ability managers accept that their executives’ increased levels of pay are deserved. Third, the squared terms of pay multiple have negative coefficients. In other words, the negative effect of pay multiple becomes greater as pay multiple increases in the low managerial ability group. Meanwhile, this result indicates that the positive effect of pay multiple changes negatively as pay multiple increases in the high managerial ability group. In quintile analyses, we confirm that this non-linearity applies for both high and low managerial ability groups. In general, the negative effect becomes greater for each higher quintile of pay multiple in the low managerial ability group. We find that there is an inverted U-shaped relationship between pay multiple and firm performance in the high managerial ability group, which implies the existence of the optimal pay multiple. Fourth, we use an instrumental variable to check for potential endogeneity due to reverse causality between pay multiples and firm performances. Our empirical results are robustly confirmed. Finally, we further analyze various sub-samples of manufacturing and non-manufacturing firms, chaebol and non-chaebol firms, and Korea Stock Exchange (KSE) as compared to KOSDAQ firms. We obtain consistent results for all of the subsamples. In summary, we show that pay multiple has a negative effect on firm performance. However, this negative effect only occurs in low managerial ability firms, where the negative impact becomes more significant as the pay multiple grows larger. These findings are consistent with relative deprivation theory. This paper examines executive-employee pay multiples, rather than pay gaps among executives or employees. By linking the pay multiple to firm performance, we show that it is important to adopt a pay structure that includes both executives and employees. Furthermore, we contribute meaningful evidence concerning relative deprivation theory by analyzing how managerial ability is related to the relationship between pay multiple and firm performance. Our findings indicate that to enhance firm performance, executive pay structures need to reflect managerial ability.

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In this paper, I analyze household portfolios with and without household debts, each of which is supposedly subject to distinct financial target according to household characteristics and financial status, respectively. Four issues were identified through the 2011~2013 Household Financial Survey. First, households with debts have more financial assets in addition to real assets than those without debts, which include stocks, bonds, insurance, and mutual funds. Households with debts also own more real estate and durables such as automobiles and real assets, which is statistically significant. This result implies that households with debts invest aggressively in asset allocation and in specific assets, unlike those without debts. Second, disposable income is a main interest variable and reduces the share of financial assets at a low level but increases the share at a high level, irrespective of household debts. In contrast, At a low level, the net worth increases real assets, whereas it decreases at a high level. Thus, we conclude that households tend to diversify the portfolio risk of real assets through financial markets. Third, as previously found, household debts reduce household financial assets but reinforce the holdings of real assets, which is also prevalent in the sample of households with excessive debts. Finally, in terms of generations, middle-aged and older households with debts are more likely to prefer stocks, and significantly more likely than younger households.

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This study examines how the business relationship between IPO underwriters and institutional investors affects the holding periods of IPO stocks allocated to institutional investors by underwriters. Studies such as Reuter (2006), Binay, Gatchev, and Prinsky (2007), and Chung and Kim (2015) have shown that the business relationship between underwriters and institutional investors affects underwriters’ initial allocation of IPO stocks. Chemmanur, Hu, and Huang (2010) argue that underwriters allocate more IPO stocks to institutional investors because institutional investors tend to hold stocks longer, especially for weaker post-issue demand IPOs, helping underwriters’ efforts to stabilize prices in the after-IPO market period. However, it is well known that on average, institutional investors sell initially allocated IPO stocks quite soon after they have been listed in the market. For example, Aggarwal (2003) and Boehmer, Boehmer, and Fishe (2006) report that in the U.S. market, flipping—that is, selling initially allocated IPO stocks within a couple of days after their listings —is common and it is mostly conducted by institutional investors. An analysis by the Financial Supervisory Service in Korea of 142 Korean IPOs listed in the Jan. 2008 to Sept. 2010 period found that on average, 64.7% of IPO shares were allocated to institutional investors, who sold 34.2% of them during the first trading day and 48% of them during the first 4 weeks after the listing. In addition, Dongyang Securities, examining 119 Korean IPOs from the Jan. 2010 to Jun. 2011 period, report that the return on IPO stocks falls rapidly after their listing, and the average closing price of the IPO stocks in one year falls to only 77% of their closing prices on the first trading day. They blame the institutional investors’ flipping of IPO stocks for the rapid price drop. It is thus evident that the length of time that institutional investors hold initially allocated IPOs in the after-market is an important issue for IPO firms and underwriters who wish to stabilize prices and protect their reputation capital. We therefore argue, based on the findings from prior studies, that the holding period can be affected by the business relationship between underwriters and institutional investors. To examine the effect of the business relationship between underwriters and institutional investors on institutional investors’ holding period of initially allocated IPOs, we use monthly mutual fund holding information and IPOs listed in the KOSDAQ market for the 2002 to 2012 period. To the best of our knowledge, this is the first study to examine the holding period of IPO stocks by institutional investors in Korea. Following Chung and Kim (2015), we measure the strength of a business relationship in three ways: (1) the total investment amount by each mutual fund in IPOs underwritten by each underwriter, (2) the number of participation by each mutual fund in IPOs underwritten by each underwriter, and (3) the average investment of each mutual fund in each IPO underwritten by an underwriter for the two years prior to the target IPO. We find that mutual funds sell, on average, about 48% of the IPO stocks within 30 calendar days of the listing. However, funds that have 1 (2)-year business relationships with the underwriter hold the IPO stocks, on average, 22.67 (17.12) calendar days longer than those without a relationship. We also show that the strength of the relationship matters: the stronger the relationship is, the longer the holding period. Tobit analyses confirm Aggarwal’s (2003) finding that institutional investors tend to sell more underpriced IPOs (hot IPOs) more quickly. We, however, show that when institutional investors have a strong business relationship with underwriters, they seem to hold hot IPOs longer than when they have a relatively weaker relationship. Combined with the results from Chung and Kim (2015), these results imply that underwriters allocate more favorable IPO stocks to institutional investors with whom they have business relationships, and institutional investors hold the IPO stocks longer, helping the underwriters stabilize prices in the after-IPO market. In addition, we find that funds that are affiliated with underwriters hold IPO stocks for shorter periods than unaffiliated funds. We also find that the business relationship has a negative effect on the holding periods of affiliated funds.

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The cost of capital is one of the key determinants of corporate investment, and according to the q theory framework, it has a negative effect on investment. However, there has been relatively little research on the relation between the cost of capital and corporate investment. Frank and Shen (2016) report the following findings: (1) the cost of capital estimated by asset pricing models such as the CAPM have a positive effect on investment; and (2) the implied cost of capital is negatively related to investment. They provide considerable insight into methods for estimating the cost of equity, but do not give a convincing explanation for their unexpected results. Building on their insight, we use a dataset of listed Korean firms to estimate a firm’s expected return using different measurement methods, and investigate whether the empirical result depends on how the cost of equity capital is measured. The most common approach to estimating a firm’s cost of equity is to calculate the expected return based on the CAPM. The implied cost of equity derived from stock prices and analyst forecasts could be an alternative measure of the expected return for a firm’s stock. In this study, we estimate the implied cost of equity by applying two different valuation models: the Gordon growth model and the abnormal earnings growth model developed by Ohlson and Juettner-Nauroth (2005). The sample dataset covers the 2002 to 2016 period. Following Frank and Shen (2016), we use a g-decomposed model in which investment is formulated as a function of marginal profitability and discount rate for a firm’s capital budgeting decision. According to the model based on the q theory, investment should be negatively related to the weighted average cost of capital, which represents the discount rate. Our findings, however, show that the CAPM-based estimate does not confirm the validity of the theoretical prediction. We consider the effect of macroeconomic factor such as the business cycle on the association between the CAPM-based estimates and corporate investment, as it is possible that firms make different investment decisions at different stages of the business cycle. We divide our sample period into an expansion period and a contraction period, and conduct the same analysis on the subsamples. We find that the positive impact of the CAPM estimate is only significant in the expansion period. We also find that the positive effect is large for the subset of relatively small firms that are listed on the Kosdaq market. The implied cost of capital-based analysis produces different results. We find that the implied cost of capital is negatively linked to investment, perhaps because the implied cost of equity capital (i.e., the return required by shareholders) better reflects investors’ expectations about the riskiness of firm-specific investments, and the information imbedded in the estimate can be useful for managers’ capital budgeting decisions. Next, we focus on the internal capital market effect, which occurs in the Korean business group. Following previous studies, we assume that firms that belong to business groups have easier access to internal capital markets. To examine whether the internal capital market plays a significant role in firms’ investment decisions, we categorize our sample firms into two subsamples: independent firms and group-affiliated firms. Our analyses of the subsamples suggest that the cost of capital can have different effects on firms’ investment expenditures depending on their business group affiliation. More specifically, we find that the negative relation between the weighted average cost of capital and investment is statistically insignificant for group-affiliated firms, whereas for independent firms, we find that investment is negatively affected by the weighted average cost of capital. This evidence is consistent with the notion that the investments of group-affiliated firms with easier access to internal capital markets are less affected by external financing cost than independent firms. In a further analysis, we also find that the investment of group-affiliated firms is negatively correlated with the debt component of the WACC, but not with its equity component. This implies that the internal capital market relieves the financing constraints of firms belonging to business groups, but it does not completely substitute for the external capital market. Finally, we use the expected return estimated by the Fama–French three-factor model as a proxy for the cost of equity. We find that the FF3-based estimate has a negative effect on investment, but the effect is not statistically significant for the whole sample, suggesting that the factor loadings of the Fama-French model can measure firm-specific risk more accurately than the CAPM beta, but they are insufficient to represent the unsystematic risk that individual firms are likely to face with respect to their investment decisions.

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Almost all prior studies on the Korean accrual anomaly focus on the stock market. In contrast to prior studies, our study examines whether or not the accrual anomaly exists in the Korean corporate bond market. Using the corporate bond data traded in the Korean market from 2000 to 2011, we find supporting evidence of the accrual anomaly in the Korean corporate bond market using three approaches: (1) hedge portfolio return test, (2) the Fama-French five factor (three equity market factors plus two bond market factors) time series regression test, and (3) the Fama-MacBeth cross sectional test. Next, we examine whether the unique Korean corporate governance system, chaebol, affects the magnitude of the accrual mispricing in the corporate bond market and find evidence that the accrual anomaly exists only for bonds issued by non-chaebol firms. This finding indicates that bond investors’ expectation about explicit or implicit subsidy from chaebol-affiliated subsidiaries dampens accrual mispricing of a chaebol firm. Taken together, our results suggest that investors in the Korean corporate bond market fixate on earnings, in particular, for non-chaebol firms.

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The essence of strategic asset allocation (SAA) is to derive the optimal asset allocation taking into account the diversification effect of each asset class under the same risk and return profile structure. The mean variance optimization method is useful when the structure of the risk and return of assets is homogeneous. However, due to the emergence of various alternative investments, methods for determining optimal asset allocation are the subject of controversy. We review the problems of the traditional SAA method that is used by pension funds and propose a new SAA method that considers multiple factors. We examine how to apply the new model to domestic pension funds. We provide a new asset allocation paradigm that provides a reasonable weighting for alternative investments and a basis for determining foreign currency hedge ratios for foreign investments. A review of domestic pension funds’ portfolios, assuming a similar target rate of returns and risk tolerance limits, identifies big differences in the weights given to alternative investments. The variation occurs because most pension funds predetermine the portion of the portfolio that will be alternative investments and then perform an SAA only for the remaining asset classes. As decisions on the weights of alternative investment consider the entire portfolio, it is necessary to improve the current asset-based SAA method that performs the allocation after excluding the alternative investment. Factor-based SAA can be a useful method for incorporating alternative investments into the asset allocation framework and can identify methodologies for integrating risk with existing assets such as stocks and bonds. There are four steps in factor-based SAA: selecting an asset mapping the asset class to each corresponding factor determining the target factor weight and re-mapping it to the asset class. In the first step, an appropriate factor must be selected to explain the payoff of each asset class. We use a principal component analysis to extract the common elements in all of the asset classes and then conduct a correlation analysis with the factor candidates to determine growth, inflation, real interest rates, credit, and FX. It is interesting to note that the inflation factor has a higher negative correlation with the other factors during an economic crisis, confirming that investing in the inflation factor during a crisis can effectively hedge a portfolio’s returns. Second, to estimate the factor coefficients for each asset using a multifactor model it is necessary to map the asset class to each corresponding factor. The estimated coefficients are then used as a link in determining the target factor exposure and to determine the optimal asset allocation. The current six asset classes are re-defined and divided into 17 asset classes based on the cash flow and risk characteristics of each asset class. In particular, we classify the alternative investments into equity and debt types. In this way, we can make the risk and profit structure of each asset class as homogeneous as possible. Third, the target factor weight is determined by selecting an appropriate factor exposure for the risk profile of the pension fund. The target factor weight should be consistent with the pension fund’s investment objectives and risk tolerance limits and is also a key element in determining the optimal allocation of investment assets. To determine the target factor exposure, we first derive a factor-based efficient frontier. Once the factor-based efficient frontier has been acquired, the optimal factor exposure with the highest Sharpe ratio is selected from the alternatives that meet the target returns and risk tolerances of the pension fund. In this case, the target factor exposure is based on the implied factor exposure obtained from the current portfolio’s starting point. Fourth, to remap to the asset class, we determine the asset class that meets the target factor weight. This process usually uses an optimization method. We set up a hypothetical portfolio of pension funds and analyze these portfolios. The implications of the case analysis are summarized as follows. First, to increase the Sharpe ratio, it is desirable to reduce the domestic equity investments and increase the portion of overseas investments. Second, the foreign exchange hedge policy of the pension fund is too conservative and should be expanded. Third, the impact of alternative investments on the portfolio’s risk-return profile varies by its composition, such that the weights should be distributed based on the correlation of factors and factor exposures. In addition, factor-based SAA allows monitoring of the exposure of investment assets to each of the corresponding risk factors at all of the times when effective risk monitoring for alternative investments is expected.

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A substantial body of research has examined the customer-supplier relationship in Korea from both the economic and social perspectives. The majority of the Korean studies on the customer-supplier relationship have focused on the performance of the suppliers of large companies (Chung, 2007; Shim, 2011; Kim and Shin, 2015). In this study, we extend this line of research by investigating the effect of the customer-supplier relationship on the cash holdings of the supplier firms. The customer-supplier relationship can directly affect a firm’s cash flow, which in turn can significantly affect the supplier firm’s working capital management, sales expenditures (Kalwani and Narayandas, 1995), leverage (Titman and Wessels, 1988; Kale and Shahrur, 2007; Banerjee, Dasgupta, and Kim, 2008), cost of debt (Campello and Gao, 2014; Cen, Dasgupta, Elkamhi, and Pungaliya, 2015), and cost of equity (Dhaliwal, Judd, Serfling, and Shaikh, 2016). Firms hold cash as a buffer to protect themselves from adverse cash flow shocks. If a customer accounts for a large proportion of a supplier’s sales, then the loss of that customer will result in a large adverse cash flow shock. As a precaution against the additional operating risk associated with having an important relationship with a customer, suppliers tend to hold cash in proportion to the importance of the customer-supplier relationship (Itzkowitz, 2013). Bae and Wang (2015) find that the relationship-specific investments of firms in customersupplier relationships are associated with the high cash holdings of the supplier firms. Firms that rely on relationship-specific investments tend to maintain high cash reserves as a cushion to sustain their relationship-specific investments when negative shocks occur (Titman, 1984). Using R&D based measures and durable-goods industries as proxies for the extent of relationship-specific investment, Bae and Wang show that the positive relationship is more pronounced for firms with positive R&D expenses and firms in the durable-goods sector. Kim, Jinn, and Han (2012) find that the leverage of Korean firms is negatively related to the R&D intensity of their suppliers and customers on the industry level but not the firm level. The primary goal of this study is to determine how the customer-supplier relationship affects the suppliers’ cash holdings. We use the percentage of sales to major customers and the major customer concentration to measure the customer-supplier relationship. Firms’ sales data from 2006 to 2012, including the proportion of sales and the customer names obtained at the firm level from Korea Enterprise Data (KED), are used to calculate the customer-supplier relationship variables. As a supplier’s dependence on major customers increases, the suppliers can potentially lose a significant proportion of sales, which could cripple their financial health. Therefore, the suppliers are likely to hold additional cash to protect themselves against the operating risk induced by their buyers. Our results indicate that suppliers are motivated to increase their cash holdings as a precautionary measure. This positive relationship between a supplier’s cash holdings and the supplier’s reliance on customers is also found in Korean supplier firms. The suppliers of customers that have considerable bargaining power may face higher uncertainty of keeping their contracts. In the case of big customers, such as leading companies, the suppliers face a higher risk of losing sales. Therefore, the suppliers of leading companies have an incentive to hold more cash as a precaution. Accordingly, the results of this study indicate that the positive relation between customer–supplier relationships and cash holdings is more pronounced for firms with big customers. Following Bae and Wang (2015), the sample is divided into subsamples based on a measure of relationship-specific investments that uses firm level R&D intensity as a proxy for relationship-specific investment. The results indicate that firms with more relationship-specific investments hold more cash than other firms. Research suggests that the precautionary motive is stronger during recession periods when firms have less access to credit and their customers are more likely to cancel purchases (Ikowitz, 2013). In line with this, the findings of this study show that during the 2008 and 2009 financial crisis, suppliers held more cash relative to the strength of their relationships than during other periods.Although the results of this study show that a supplier’s reliance on major customers induces the supplier to hold more cash, the customers may prefer to deal with financially stable suppliers and thus purchase more from such suppliers. To handle this endogeneity problem, a two-stage least squares (2SLS) regression is conducted in which the instrumental variable is a dummy variable that is set to one if a supplier is located in the same area with one or more customers, and zero otherwise. The results show that although the instrumental variable is associated with the proportion of a supplier’s sales, the relationship does not affect the firm’s cash holdings. Thus, the 2SLS analysis supports the main results of this study.

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Equity funds that invest primarily in equities are exposed to both market risk and cross-sectional systematic risks. However, Barber, Huang, and Odean (2016) and Berk and van Binsbergen (2016) show that investors in the U.S. mutual fund industry mostly consider the market risk (beta) when evaluating funds and treat the returns attributable to other systematic risks as alpha. Thus, the capital asset pricing model (CAPM) alphas are the best predictors of fund flows among the competing performance evaluation models. Indeed, Barber, Huang, and Odean (2016) and Berk and van Binsbergen (2016) show that investors take into account the realizations of aggregate risk factors when assessing the performance of mutual funds. Similarly, Berk and Green (2004) use a rational model to demonstrate that investors learn about a manager’s ability from past returns. Based on the work of Berk and Green (2004), Barber, Huang, and Odean (2016), and Berk and van Binsbergen (2016), Franzoni and Schmalz (2017) investigate the flow-performance sensitivity of mutual funds across market states and show that the sensitivity changes across market states. They assume that the fund investors are Bayesian investors who are uncertain about the degree to which the fund returns are exposed to systematic risk. In extreme periods, defined as periods of very high or low market excess returns, they find that the flow-performance sensitivity is weaker because fund investors have difficulty estimating the skill of fund managers. In line with Franzoni and Schmalz (2017), Starks and Sun (2016) find that the fund flow-performance sensitivity decreases during periods of economic uncertainty. In this study, we investigate the equity fund flow-performance sensitivity across market states in the Korean fund market. Sirri and Tufano (1998) and Huang, Wei, and Yan (2007) show that search costs or participation costs are an important determinant of fund flows, emphasizing the convex relationship between flow and performance. Because a fund investor cannot evaluate all of the funds in the fund market, the fund flows are concentrated in high-performing funds. However, Ferreira, Keswani, Miguel, and Ramos (2012) show that the participation costs have declined over time as the U.S. mutual fund industry has matured, thereby weakening the convex flow-performance relationship. However, in the emerging fund market of Korea, the flow- performance relationship is strongly convex because the investors are less sophisticated. In fact, during the 2008 global financial crisis, there was a massive redemption of equity funds because the less sophisticated investors were not aware that the fund returns could move in line with the market returns. In contrast to the U.S. mutual fund market, in which investors acknowledge the fund market risk, there may be a lack of awareness of the fund market risk in the Korean fund market. Thus, we also examine the effect of market risk on equity funds in the flow-performance relationship. The aims of this study are as follows. First, drawing on Franzoni and Schmalz (2017), we analyze the flow-performance sensitivity across different stock market conditions. Using Fama and Macbeth’s (1973) monthly cross-sectional regression, we divide the entire period into three periods of down-, moderate-, and up-market depending on the market risk premium and divide the periods into negative and positive periods. Second, to examine the effects of an equity fund’s market risk, we investigate the fund flow response to the fund’s raw returns (i.e., the absolute returns without adjusting the benchmark returns) and market-adjusted returns (i.e., the raw returns minus the market returns). We then use the pooled regression model to estimate how the fund flows respond to the raw returns and the market-adjusted returns divided by the negative and positive returns, respectively. Our results are as follows. First, in contrast to Franzoni and Schmalz (2017), we find that the flow-performance sensitivity in the Korean fund market increases significantly during the up-market periods and the positive periods in which the market risk premium is high. This suggests that Korean equity fund investors expect high absolute positive returns and respond more sensitively to the performance of the funds in such market conditions. Second, we find that the fund risk does not affect the flow-performance relationship, thus indicating that the fund investors do not respond to the fund risk. Third, the flow-performance relationship is significant only when the raw returns are positive for the entire period. Finally, the flow-performance relationship is only observed when the raw returns are positive regardless of the fund size, age, and performance evaluation period. The results of this study suggest that unlike in the developed U.S. mutual fund market, the fund investors in the Korean equity fund market do not regard market risk as a risk and expect high absolute raw fund returns. This suggests that fund investors in Korea need to recognize the inevitably of market risk and invest in funds as a means of long-term investment.

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This study investigates the impact of the trading of the national pension fund (NPF, hereafter) on the stock markets in Korea. In 2017, the Korean national pension system, which was introduced in 1988, was ranked as the third largest public pension fund after Japan and Norway, with assets of 6.8 trillion Korean won. Moreover, the NPF accounts for 6.75 percent of the Korean equity market, which is higher than the 5.06 percent of equity held by the Japanese pension fund. As the NPF has increased its investment in the Korean stock market, its trading strategies and possible influence on the stock market have attracted increasing attention from market participants and regulators. However, despite the growing interest in the subject, few studies have examined the strategies and influence of the NPF and there is little research data on the trading in the past decade. In addition, the NPF recently announced that it plans to increase the proportion of investment in stocks in its portfolio over the next five years. Thus, the NPF is expected to have an increasing influence on the Korean stock market. Given the significant size of the NPF, the increased proportion of stocks held by the fund could lead to price pressures unrelated to the intrinsic value of firms and result in price movements induced by follow-up investors. For these reasons, there has been considerable debate over the effect of the NPF’s trading on the stock market. Some have argued that the NPF’s investment decisions are based on political judgement rather than information whereas other institutional and foreign investors conduct information-driven transactions. In line with this, the NPF recently provided an official explanation of why its stock portfolio only achieved average returns of 5%, which is significantly lower than the 22.15% average returns on the Korea Stock Exchange (KSE) and 24.75% returns on the Korea Securities Dealers Automated Quotation (KODAQ) market. Taken together, these concerns suggest that there is a pressing need to comprehensively examine whether the NPF’s transactions on the stock markets distort the markets and worsen the market quality in terms of liquidity and volatility. In this study, we attempt to address these questions by examining the influence of the NPF’s transactions on the Korean stock markets. Our dataset comprises the combined data from the ownership change and trading records of the KSE and KODAQ over the 12-year period from August 2005 to July 2017. Specifically, we combine the insider equity ownership disclosures, disclosures of large equity ownership, and information on the trading record files and infer detailed information on the dates, quantity, and prices of the stocks traded by the NPF. Based on the inferred accounts of the NPF, we analyze the trades of the NPF from 2005 to 2017 at both the aggregate market and individual stock levels. Some of our major findings are as follows. First, consistent with the literature, we find that the NPF uses a contrarian trading strategy such that the fund tends to buy stocks when the market return goes down and sell them when the return goes up. This phenomenon is also observed at the individual stock level even after controlling for various stock characteristics, and the results are consistent across the yearly analyses. Second, the market volatility decreases when the NPF’s net buying increases. Therefore, the NPF’s stock transactions do not appear to destabilize the stock market. Furthermore, in contrast to the general concerns, our empirical results suggest that the NPF’s stock transactions contribute to market stabilization. Third, we do not find evidence showing that the trading of the NPF influences the trading of other investors, including the other sub-groups of institutional investors and individual investors. However, we find that among the various sub-institutional investor groups, the increased net buying of the NPF is associated with increased net buying by investment companies and miscellaneous financial investors. These sub-groups are influenced by the net buying of the NPF after two to three days, indicating follow-up transactions. Together, these findings suggest that some financial investors may consider the NPF to possess a strong capacity to analyze information.

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