Share repurchase is the buyback process that firms use to repurchase their own stocks. It is a major financial policy of many firms, and its use has recently increased. Share repurchases can signal firm value to investors, not only because most firms mention undervaluation as a key motivation for share repurchases but also because investors look favorably on repurchasing decisions. However, it is unclear whether repurchasing firms truly are undervalued. Ikenberry, Lakonishok, and Vermaelen (1995) divided US stocks into two groups based on their book-to-market ratio (B/M), and analyzed each group’s long-term stock returns. They found that value stocks with a higher B/M had earned a cumulative abnormal return (CAR) of 45.3% four years after the repurchase announcement, whereas glamor stocks with a lower B/M had earned almost 0% CAR. They concluded that share repurchases are a major signal for value stocks but not for glamor stocks. Byun (2004) divided a sample of firms into two groups based on abnormal earnings before interest and tax (EBIT), and compared low EBIT firms with high EBIT firms. Compared with the high EBIT firms, the low EBIT firms had a negative long-term stock performance, suggesting that undervaluation is not the motivation for share repurchase. How, then, can we identify which of there purchasing firms are truly undervalued? One way to identify undervalued repurchasing firms is to consider insider trading before share repurchase announcements. While share repurchasing is the buyback of a firm’s own stocks at the firm level, insider trading is personal trading by individuals with inside knowledge, such as the largest shareholders and directors. The decision-makers for these two types of trading are the same, so insiders have an incentive to increase their personal stakes if the firm is truly undervalued (Lee, Mikkelson, and Partch, 1992; Chan, Ikenberry, Lee, and Wang, 2012). Therefore, we examined whether insider trading prior to share repurchase was an additional signal of firm value. Share repurchasing firms in the KOSPI and KOSAQ markets in Korea were divided into a net-buy group and a non-buy group, based on insider trading for the six months before the repurchases. We then looked for differences between the short-term and long-term abnormal returns of the two groups. We further divided the sample into a value stock group and a glamor stock group, and investigated the relationship between insider trading and long-term abnormal returns. The main results were as follows. First, there were no differences in the short-term abnormal returns of the KOSPI and KOSDAQ markets. There were also no significant differences in the short-term CARs of the net-buy group and the non-buy group, even though the short-term CARs were significantly positive around the time of the repurchase announcements. Firms are required to complete repurchases of their own stocks within three months. It is thus possible that investors do not consider insider trading prior to share repurchase and simply react to the share repurchasing announcement. Second, unlike the short-term reaction, there were significant differences in the long-term abnormal returns of the KOSPI and KOSDAQ markets. There were no significant differences between the net-buy and the non-buy groups in the KOSPI market but there were significant differences between the two groups in the KOSDAQ market. We tested for robustness using buy and hold abnormal returns (BHARs) and CARs based on the Fama and French (1993) three-factor model. We conclude that insider trading can convey additional information regarding firm value only in the KOSDAQ market, which has higher information asymmetry. Third, there were no significant differences in the long-term abnormal returns of value stocks for the insider net-buy and non-buy groups in both the KOSPI and the KOSDAQ markets. However, for glamor stocks, share repurchases by the insider net-buy group showed a larger long-run CAR than those of the non-buy group in both markets. Therefore, we conclude that insider trading prior to share repurchase can convey information, especially for glamor stocks. Overall, insider trading prior to share repurchase is associated with private information about firm value, and can convey a signal in addition to the information signaled by share repurchases.

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Investment in private markets, formerly known as alternative investment, is increasing in Korea and elsewhere. The value of the assets managed by the National Pension Service (NPS) will reach USD 500 billion by the end of 2015 and is forecast to grow to USD 2.5 trillion over the next 30 years. The NPS is currently allocating around 10% of total assets to private markets, and will increase this to 14% within the next 5 years according to its mid-term asset allocation plan. As the Korean economy matures, financial assets held by institutional investors will grow exponentially, from USD 2 trillion in 2014 to USD 5 trillion over the next 30 years. As the local economy becomes saturated, huge growth in financial assets will flow to overseas markets, especially to private markets, which is the theme of this study. Global pension and endowment schemes are also increasing their investments in private markets as returns on fixed incomes have become very low following the financial crisis and the risk-return profile of equity is not attractive. Private markets provide diversification benefits and better returns for investors. Nevertheless, studies on private markets are limited in Korea. Previous international studies have focused on private equity dedicated to buyout and venture or on private equity real estate (PERE) funds. This comprehensive study included both private equity funds and various real asset funds such as real estate. Using Preqin’s database, a comprehensive global sample of the IRRs of 2,280 private equity funds and 380 PERE funds from 1985 to 2004 was analyzed. The IRR and standard deviation of various types of private equity fund that have not previously been studied (including not only buyout and venture but also growth, mezzanine, distressed and fund of funds) were analyzed. Various real assets such as real estate, infrastructure, resource and timber were also analyzed. Various types of real estate fund, such as debt, core, value-added, opportunistic and fund of funds, were included in the analysis. This is the first study to analyze the risk-return profiles of various assets, types of private equity and real estate funds. The Sharpe ratio concept of dividing IRR by standard deviation was used to determine the relative attractiveness of different assets in different regions. At the asset level, infrastructure was the most attractive, followed by real estate and private equity. However, type-level analysis gave a different result, and indicated that choice among different types of equity, assets and regions, is an important factor in explaining the risks and returns of private funds. Investors can use the risk-return profiles and information about relative attractiveness provided by this study to make decisions about asset allocation among different asset types in private markets in different regions. Humphery-Jenner studied how the diversification level of buyout and venture funds affected the performance of funds and concluded that diversification positively influenced the performance of funds due to knowledge sharing between different funds. There have been disagreements about whether diversification in industry or region has a positive or a negative effect on the performance of funds. This study extended Humphery-Jenner’s previous study to various types of private equity fund and real estate fund. Although Humphery-Jenner used Preqin’s industry classification, this study used the Global Industry Classification Standard (GICS) to improve objectivity. For geographic diversification, this study measured the number of continents rather than the number of countries, as used by Humphery-Jenner. For real estate, the number of property types, such as office, retail and residential, was measured. The same method was used to measure geographic diversification. The overall analysis of private equity funds agreed with Humphery-Jenner’s findings, confirming that industry and geographic diversification positively influenced fund performance. The number of industries and regions divided by the number of relevant staff negatively influenced fund performance, suggesting that staff numbers should increase as diversification increases. However, the results varied for each type of fund, and firms at different stages were affected differently by diversification. Early-stage venture funds showed benefits from industry diversification. However, the performance of growth funds was negatively associated with diversification, implying that growth funds benefit from concentration rather than diversification. Buyout and mezzanine funds investing in mature-stage firms were positively influenced by geographic diversification. Depending on the stage of the firm, fund managers may thus require either diversification or concentration in region and industry. In real estate, diversification had no effect on the performance of funds in both the overall market and at the individual type level. In conclusion, some types of private equity fund receive benefits from industrial or geographic diversification due to knowledge sharing. Growth funds benefit from concentration by focusing on the strengths of managers. Managers of other private equity funds and real estate funds may choose either diversification or concentration strategies.

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In recent years, concern about the economic polarization of large firms and small and medium-sized firms has drawn attention to the supply chain. Despite the economic and social importance of win-win cooperation between large firms and small and medium enterprises (SMEs), due to a lack of data there have been few analyses of the relationship between suppliers and large firms. This study investigates the accounting performance of the suppliers of large firms, and compares it with the accounting performance of the suppliers of other firms. Large firm buyers are defined as industry leading companies (the top two companies in an industry), and suppliers are the companies that sell to those firms. For a company to be defined as a supplier of a large buyer, that company’s sales to a large buyer should be more than 10 percent of its total sales. Sales data for the suppliers are taken from KED (Korea Enterprise Data), which provides transaction data from individual firms. Non-suppliers, those who do not sell to the large firms, are matched with the suppliers by asset size and 3-digit industry code. A total of 6,238 firm-year records for suppliers that sold to 104 industry leading companies between 2005 and 2012 are used, and 6,635 firm-year records for non-suppliers are matched with those of the suppliers. Conventionally, the relationship between large companies and their suppliers is explained in terms of relative bargaining power. If a large firm shifts costs to suppliers to make profits or to cover losses, the relationship between the suppliers’ margins and those of the large buyers is expected to be negative. However, we find that suppliers’ margins have a positive relationship with those of large buyers. Next, we compare the gross margins of suppliers with those of non-suppliers, and find that the gross margins of suppliers are significantly lower than those of non-suppliers. This result is consistent with findings previously reported in the Korean literature, which suggest that large buyers’ requests for suppliers to lower their product prices reduces the suppliers’ gross margins. Suppliers’ and non-suppliers’ operating margins, which reflect operating expenses, are not significantly different, but the profit margins of suppliers are significantly higher than those of non-suppliers. Analysis of the margins shows that suppliers’ operating and other expenses are lower than those of non- suppliers. A buyer’s reputation might reduce its supplier’s marketing expenses, which could offset the loss in selling price. Also efficient asset utilization induces cost reductions and can be measured by turnover ratios, we compare turnover ratios for suppliers and non-suppliers. Fewer days in inventory and receivables shortens the cash conversion cycle and improves the management of working capital, which is especially important to SMEs. We find that the asset turnover ratios, inventory turnover ratios and accounts receivables turnover of suppliers are significantly higher than those of non-suppliers. More specifically, the number of days in inventory and in receivables are lower for suppliers than for non-suppliers. Fewer days in inventory lowers the cost of inventory and fewer days in receivables lowers the cost of capital. There is no significant difference in payables turnover between suppliers and non-suppliers. Turnover ratio analysis shows that suppliers make more efficient use of assets than non-suppliers. According to the DuPont Identity, asset turnover increases return on assets (ROA) and return on equity (ROE) even though profit margins are not higher. In our analysis, we find that suppliers’ profit margins are higher than those of non-suppliers. Therefore, the better use of assets by suppliers enhances ROA and ROE compared with non-suppliers. Lower gross profit margins and enhanced asset utilization are more common among suppliers that are affiliated with the top four business groups (Samsung, LG, SK and Hyundai Motors). Samples are divided into two groups: suppliers of the top four business groups and their matched non- suppliers, and suppliers of other large firms and their matched non-suppliers. A small profit and quick returns strategy is apparent for the suppliers of the top business groups. This strategy means that the top business groups have more bargaining power than other large buyer firms, but can also help their suppliers to achieve higher sales with the associated benefit of a higher ROA and ROE. In this study, the performance and supplier dummies may lead to an endogeneity problem. However, after controlling for endogeneity using two-stage least squares (2SLS) regression, the results are consistent. To test robustness, the non-supplier sample is restructured according to a propensity scoring match. The main results are also consistent with the analysis of the restructured sample. This study shows that public perceptions of the relationship between large firms and small to medium-sized firms are partially correct. The low gross margins of suppliers can be interpreted as evidence of the bargaining power of large firms. However, suppliers obtain a higher ROA and ROE than non-suppliers due to efficient asset utilization. Given these results, we hope that both the suppliers and the large firms will appreciate each other’s role and strengthen their win–win relationships.

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This study used intraday high-frequency data over a 10-year period to empirically investigate the distributional and dynamic properties of returns and measurements of realized volatility in a situation of high market liquidity in the KOSPI 200 stock market index and the Japanese yen foreign exchange rate. The purpose and scope of the research were as follows. First, we examined the statistical characteristics of the empirical distribution of each return using high-frequency price data with eight time scales ranging from 1 min to 1 day, and determined the degree of difference from a normal distribution and the effect of increasing the measurement time interval from 1 min to 1 day. Second, we investigated the distributional and dynamic properties of the empirical distribution of each measurement of realized volatility calculated from the high-frequency returns, and the distribution of adjusted returns divided by the realized volatility. The empirical distribution of the returns from the KOSPI 200 market index and the Japanese yen exchange rate clearly differed from a normal distribution, with a more peaked central part and a much fatter tail. The time scale used to calculate the returns had a significant influence on the results; the shorter the measurement time scale, the larger the deviation from a normal distribution. Additionally, we found that the higher central part and much fatter tail of the empirical distribution of the returns, compared with a normal distribution, was supported at the 90% confidence interval in the central part and a significance level of 0.5% of the confidence interval in the tail. [The description of the confidence intervals and significance levels with respect to the center and tail of the distribution needs to be clarified.] The dynamic properties of the returns did not persist over time, decaying slowly according to changes in the autocorrelation from lag 1 to lag 100; that is, the distribution displayed unpredictability. The realized variance and realized standard deviation of volatility calculated from the highfrequency KOSPI 200 market index data and the Japanese yen exchange rate had the characteristics of a log-normal distribution, with a higher central part and a tail that was highly skewed to the right, whereas the distribution of the logarithmic realized standard deviation was similar to a normal distribution. The predictability of the measurements of the realized volatility was confirmed by time series persistence, in which the autocorrelation of the realized volatility decreased slowly according to the change from lag 1 to lag 100. Interestingly, the adjusted return divided by the realized standard deviation showed very similar characteristics to a normal distribution, unlike the distributional properties of the original return. Based on the observed distributional and dynamic properties of the returns and the realized volatility, commonality may exist regardless of the type of market. These findings suggest that there is a need to carefully consider the distribution and dynamic properties of returns when establishing an empirical design using intraday high-frequency data. An increasing number of studies have reported results based on empirical designs using intraday high-frequency data, and researchers have tried to control for the negative effects of market liquidity, measurement errors, and market microstructure. Unfortunately, however, they have not seriously considered the possibility that the time scale used to calculate the returns might influence the results. The main findings of this study suggest that time scales may be crucial influencing factors when establishing the design of an empirical test.

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This study examines how product market competition affects stock market returns by treating the advent of the Free Trade Agreement (FTA) between the United States and South Korea as an external shock. The relationship between product market competition and stock returns is unclear. For firms subject to strong product market competition, investors may demand higher rates of return to compensate for greater business risk or bankruptcy risk. For firms that face less market competition, investors may require lower returns because the business risk and risk of bankruptcy are correspondingly lower. However, the actual realized returns may not be as expected. Firms subject to strong market competition may earn low returns because of the stiff competition in the product market, and firms that face lower product market competition may earn higher returns because the lower market competition allows them to generate a steady cash flow. We are motivated by the limitations of previous studies that measure the degree of product market competition by market share to construct a CR (concentration ratio) or HHI (Hirschman-Herfindahl Index). These studies ignore the possibility that firms in the same industry may have vertical relationships; some firms in the industry may not be competitors, but rather cooperators. We take a new approach by considering how the Korea-US FTA increases market competition for products supplied by individual companies. We hypothesize that the decreased tariff resulting from the FTA induces a more competitive market environment and that the degree of tariff reduction is related to the degree of competition. We use the effective date of the FTA, March 15, 2012. By matching the degree of tariff reduction resulting from the FTA with product market sales, we construct a dataset for measuring product market competition. Specifically, we choose firms in the manufacturing industry that were listed on the Korea Stock Exchange between 2011 and 2013. We then match the firms’ two highest-selling products with the tariff change resulting from the FTA. The final sample comprises 714 firms. This unique data design reduces the biases that have often produced confounding effects and inconsistent empirical results in previous studies. We classify firms into a high-tariff-change group (the treatment group) and a low-tariff-change group (the control group). We use two different cutoff points for the change in tariff . The first is a tariff reduction of 1.6%, which places a similar number of firms in each group. Our results are robust when cutoff points for the change in tariff of 2%, 3%, and 4% are used. As an alternative way of dividing our sample, we group the firms based on whether they are subject to a tariff change (the positive-tariff-change group) or not (the no-tariff-change group). We then use controlled difference-in-difference (DiD) analysis to mitigate the possible endogeneity problem. First, we use the annual returns of firms as the dependent variable and run a DiD regression. Second, we examine the periods surrounding the effective date of the FTA and test whether there are significant differences in the monthly stock returns of firms that are subject to different tariff changes. The DiD estimation results indicate that both the monthly and yearly stock returns of the high-tariff-change group (and positive-tariff-change group) are significantly lower than those of the low-tariff-change group (and no-tariff-change group). This is clear empirical evidence that tougher product market competition lowers stock returns. Our results differ from those of previous studies, such as Hou and Robinson (2006) who examine the US market, Gallagher, Ignatieva, and McCulloch (2014) who examine the Australian market, and Ryu, Ryu, and Baek (2014) who examine the Korean market. Our results do support the argument of Bustamante and Donangelo (2014), who find that tougher product market competition reduces exposure to systematic risk and thus lowers stock market returns, rather than reducing profit margins and thus increasing exposure to systematic risk. When we examine a subgroup of firms that experienced the elimination of tariffs, we find that a greater increase in US imports is associated with a lower stock return. Our study makes the following contributions to the literature. First, we use an external shock to mitigate the methodological problems that have plagued previous studies. Second, for a country which relies heavily on foreign trade and is in the process of negotiating FTAs, we show how such agreements affect market competition and the financial performance of local firms. Third, whereas previous studies on this topic have inconsistent or mixed results, our results are strong and robust to different model specifications and empirical methodologies.

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