This paper evaluates the (out-of-sample) prediction performance of bankruptcy prediction models using Korean firms. Based on the source of information, we classify these models into accounting-based, market-based, and hazard categories. Note that hazard models are based on both accounting and market information. We consider five bankruptcy prediction models in this study; two accounting-based models, one market-based model, and two versions of a hazard model. One of the accounting-based models employs multivariate discriminant analysis (MDA), and the other employs logit analysis. The example of the first accounting-based model is the Altman (1968) Z-score model, and that of the second is the Ohlson (1980) O-score model. Most studies in the Korean literature use the accounting variables and coefficient estimates that Altman (1968) and Ohlson (1980) use for U.S. firms to predict bankruptcy, which may result in bias and inaccuracy because accounting variables may have different economic implications in different countries. Accordingly, in this study, we select new accounting variables that better fit Korean firms with respect to discriminant power and goodness-of-fit, and re-estimate the coefficients. For the market-based model, we use the KMV default-to-distance (DD) model. DD indicates the distance from the mean of the firm’s current asset value to its default point. The greater the DD, the smaller the probability of default. For the hazard model, we use the bankruptcy prediction model developed by Campbell, Hilscher, and Szilagyi (2008) (CHS), which uses both market and accounting information and has become popular in the finance literature. It has also been shown empirically that the CHS model is effective in predicting bankruptcy for firms in a variety of countries. We consider two versions of this hazard model. The first is one that adopts the same variables as those selected for U.S. firms in the CHS model and re-estimates them using Korean data. The second is a modified version of the CHS model. The variables are newly selected for Korean firms, and the coefficients are then re-estimated using data on these firms. The modification involves the addition of effective variables and exclusion of irrelevant variables based on empirical analyses. We estimate the five foregoing bankruptcy prediction models using data on all Korean firms in the seven years (in-sample period say, 2001~2007) prior to the one-year forecasting period (out-of-sample period say, 2008). By rolling over year by year, we repeat the in-sample estimation using the seven-year data prior to the one-year out-of-sample period. The sample period is 2001 to 2013. Thus, we obtain forecasting results from the five models for six years (i.e., 2008, 2009, 2010, 2011, 2012, and 2013). We then evaluate their bankruptcy prediction performance. Three methods are used to evaluate the models’ prediction accuracy for Korean firms: the hit ratio, receiver operating characteristic (ROC) curve, and information content test. The hit ratio is calculated as the ratio of the number of bankrupt firms in the portfolio to the number of all bankrupt firms in each forecasting year. Portfolios are formed by assigning all firms into one of ten decile portfolios based on the seven-year in-sample estimation results of each model. The hit ratio and ROC curve are traditional comparison methods that classify firms dichotomously (bankrupt or not). The information content test, in contrast, assesses whether different models convey information on actual bankruptcy. Of the five models evaluated, the hazard model modified for Korean firms performs best in predicting actual bankruptcies in the out-of-sample period with respect to all three bankruptcy prediction performance measures. The unmodified hazard model performs second best, and the DD model worst. There is little difference in prediction performance between the two accounting-based models, i.e., that using logit analysis and that using multivariate discriminant analysis, although their performance varies depending on the performance evaluation method used. This paper contributes to the literature in the following ways. First, by modifying the accounting and market variables used in the CHS model for Korean firms and re-estimating the model, we present a new hazard model that better fits Korean firms and outperforms other models in bankruptcy prediction accuracy. To the best of our knowledge, this is the first study to evaluate the performance of bankruptcy prediction models using Korean data. Second, this study is also the first in the Korean literature to include data over a period encompassing the 2008 global financial crisis. As there were many bankruptcies during that period, its inclusion enhances the reliability of our results. We suggest that our modified hazard model be used in future studies in both academia and industry.

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Institutional investors are obligated to actively exercise their shareholder rights to perform fiduciary duties as trustees. Korean institutional investors, however, do not perform these duties diligently because they indirectly invest in entrusted assets and are reluctant to exercise shareholder rights out of concerns over investing companies, political affairs, and institutional constraints. Foreign investors, in contrast, are more likely to exercise their shareholder rights because they are free from these concerns. This paper investigates the role of domestic and foreign institutional investors as corporate monitors using a daily mechanism rather than voting rights, which are exercised only on specific proposals at general shareholder meetings. We analyze how the agency costs and value of target firms are affected by the sale of a portion of their stocks by domestic and foreign institutional investors. Our sample comprises all institutional investors’ disclosures of an equity ownership change to abide by the “5% rule” in the period from April 2005 to December 2012. Under the 5% rule governing large share acquisitions of publicly held companies, a person or institution who holds 5% or more of the equity securities in a target company or thereafter changes its holdings by 1% or more must file a report with the Financial Supervisory Commission and Korea Exchange (KRX) within five days of the transaction or change date. We exclude from the sample announcements made by a target company between the trading date and announcement date of stock sales because the firm announcement effect and institutional investor disposal effect are likely to be intertwined. We also exclude disclosures that generate a positive market response because only unfavorable announcements are followed by monitoring-motivated stock sales. If a target firm makes an announcement before an institutional investor’s announcement of share disposal, we include that announcement only if it shows a statistically significant negative market response at the 10% level, as measured by the cumulative abnormal returns (CAR) around the stock sale disclosure date. CAR is calculated by summing all market-adjusted abnormal returns around the target firm’s announcement. If a target firm makes no announcement within five days of institutional investors’ announcement of a stock sale, the announcement is included in the final sample to ensure that we do not rule out the disposal of a portion of shares that is too small to attract an announcement obligation by institutional investors to punish management seen to be destroying shareholder value. A sale is regarded as a monitoring-motivated sale when the CAR around the announcement date of an institutional investor stock sale is positive at the 10% significance level. We expect that institutional investors’ sale of a portion of their stake reduces a target firm’s agency costs and increases corporate value if it has a “kick-in-the-pants” motivation and that strategic investors are more likely to reprimand and exert influence on management than financial investors. However, the opposite outcome is also possible if management subordinates shareholders’ passive stock sales to the more active exercise of shareholder rights. In multiple regression analysis, the dependent variables are agency costs measured by the ratio of operating expenses to sales, which tend to decrease when managers’ perks are restrained, and the asset turnover ratio, which tends to increase when assets are used more efficiently. Another dependent variable is firm value measured by (industry-adjusted) Tobin’s Q. The explanatory variables are a monitoring dummy indicating a positive market response, an institutional investor intention-to-hold stock dummy indicating a strategic investment, an unfavorable announcement-by-the-target-firm dummy, a foreign investor dummy, and a foreign investor intention-to-hold stock dummy. Two-stage least-squares regression analysis is performed with one year lagged data to consider the possible endogeneity of the monitoring dummy representing monitoring motivation. We find that an institutional investor’s sale of a portion of its stock is more likely to reduce operating expenses relative to sales when an unfavorable disclosure by the target company generates a positive market response to the institutional investor’s announcement of that sale and when foreign investors are labeled as strategic investors. Our results also show that stock sales by institutional investors improve firm value. For foreign investors, firm value is improved only when they report the purpose of their stock holdings to be management participation. Strategic institutional investors tend to have a negative effect on firm value except in the case of kick-in-the-pants-motivated sales, which suggests that we should encourage strategic foreign investors to improve the long-term performance of firms. In sum, institutional and foreign investors monitor firms through the sale of a portion of their shares, in addition to registering a “no” vote on firms’ proposals in shareholder meetings and engaging in face-to-face talks with management.

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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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The analysis of long-term bond excess returns is an important issue in portfolio management and risk dynamics. Under the classical expectation hypothesis, which assumes that long-term yield represents future short-term rate expectations, the excess return on a long-term maturity bond is constant over time. However, it is well known that this assumption does not hold empirically. In the U.S. and other international markets, the forward rate factor suggested by Cochrane and Piazzesi (2005) strongly predicts bond excess returns. Thus, the bond excess return is time-varying and the current yield curve contains information on bond risk premia. Given that the bond price reflects the market participants’ expectations regarding future economic states, it should be closely related to macroeconomic variables, such as inflation and real growth. There is a growing area of research called “macro-finance” that tries to explain the term structure of interest rates and bond risk premia with macroeconomic variables. In this paper, we empirically investigate the predictability of bond excess returns in the Korean market. We use information from the current yield curve, inflation shock, and real production shock. Specifically, we use the forward rate factor from Cochrane and Piazzesi (2005), the inflation cycle factor from Cieslak and Povala (2014) and the output gap factor from Cooper and Priestley (2009) as candidate variables to predict bond excess returns. First, we construct the three candidate factors: forward rate, inflation cycle and output gap. The forward rate factor is defined as the fitted value from the regression of the mean excess return on the forward rates. Under the Fisher hypothesis, a long-term yield can be decomposed into an expectation hypothesis term, a long-term inflation expectation term, and a cycle term. The inflation cycle factor summarizes information in the residuals from the regressions of the yields on the long-term inflation expectation. The output gap factor is generated by removing the time trend from the industrial production index. The empirical result shows that the forward rate factor strongly predicts the excess returns of all maturities, with an adjusted   higher than 50%. Consistent with the other markets’ results, the information in the yield curve is important in predicting bond excess returns. Compared to the forward rate factor, the inflation cycle and output gap factors, which are individual macroeconomic variables, have weak or no predictive ability. Although the cycle factor has comparable forecasting ability in relation to the forward rate factor, it does not have any additional predictive power when the forward rate factor is taken into account. Even worse, the output gap factor does not have any explanatory power alone. Overall, the results indicate that the macroeconomic variables in our analysis do not have information above the yield curve. We also conduct further analyses of the forward rate factor, which exhibits strong predictive power. The explanatory power of the forward rate factor is beyond the conventional yield curve factors (level, slope and curvature). It does not come from the multicollinearity of forward rates. In addition, the forward rate factor survives after controlling for the effect of international variables; specifically, the U.S. forward rate factor and the currency swap rate. As with the results from the international market data in Sekkel (2011), the explanatory power of the forward rate factor decreased after the financial crisis. Finally, the forward rate factor effectively explains the longer maturity bonds with maturities longer than five years. Focusing on the failure of the inflation cycle factor, which theoretically contains refined information about bond risk premia, we find that the long-term inflation expectation does not have explanatory power in addition to bond yields. Cieslak and Povala (2014) argue that the forward rate factor is a restricted version of the cycle factor, and they remove the long-term inflation term from the bond yields. In contrast, the inflation cycle factor becomes a noisier measure of bond risk premia in the Korean market and the predictive power of the forward rate factor is very strong in our sample period in the global market. The empirical results in this study imply the possibility that bond prices in the Korean market can be expressed as an affine model of yield curve factors, as in Cochrane and Piazzesi (2005). Although the macroeconomic factors do not seem to contain information about bond risk premia above the yield curve, we do not strongly reject the macro-finance models from our empirical results, as the macroeconomic factors in this paper are from a small subset of macroeconomic variables. We remain open to the possibility of more explanatory macroeconomic variables of bond risk premia.

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The Organisation for Economic Co-operation and Development (OECD) (1998) defines a tax haven as having the following characteristics: (a) no or only nominal taxes, (b) a lack of effective exchange of information, (c) a lack of transparency, and (d) no requirement that the activity be substantial. As these guarantee anonymity and little regulation in financial transactions, capital flows from tax havens are suspected to derive from dishonest motives and to have a negative impact on the local financial market. In Korea, there also has been a debate about local investors’ round-tripping through accounts in tax havens. Specifically, local investors set up paper companies in tax havens and camouflage themselves as foreign investors by trading local securities through these companies. The Korean media often refer to these investors as ‘blackhaired foreigners’. There is, however, little empirical evidence of the effect of capital flows from tax havens because relevant data are not available. This paper empirically investigates the impact of capital flows from tax havens on the Korean stock market using the 246 country codes provided by the Korea Exchange (KRX). The primary data source is the TAQ (trade and quote) dataset, which includes the full history of all trades made in the Korea Composite Stock Price Index (KOSPI) market between January 2006 and June 2008. Each trade record contains the price, quantity, time-stamp, investor class, and, most importantly, the country of origin of both buyers and sellers. First, I compute the dollar trading volume of both purchases and sales across nations and list all the foreign countries investing in the KOSPI market. The summary statistics indicate that investors from the U.K. constitute a quarter of the total trading activity of all foreign investors in Korea. U.S. investors account for roughly 14% of all trades from foreign countries. The Cayman Islands, which is a tax haven, is the third largest foreign country investing in Korean stocks, accounting for 9% of all foreign trading. I consider a country a tax haven if it was listed in the 1998 OECD report on tax havens. Finally, I define the following 5 jurisdictions as tax havens: the Cayman Islands, the Bermuda, the Bahamas, the British Virgin Islands, and the U.S. Virgin Islands. Trades from these tax havens amount to about 10% of the total trading volume of foreign investors in the KOSPI market. This suggests that trades from tax havens make up a substantial proportion of all foreign trading and that their impact on the KOSPI is likely to be significant. Next, I investigate whether foreign investors from tax havens pursue positive feedback trading strategies. These strategies are considered to have a destabilizing effect because their sales lead to falls in the stock prices and their purchases increasing in price. This may contribute to an increase in the volatility of stock returns. Such trading can also destabilize capital flows as investors rush into booming stocks and flee from falling ones. Empirical results show that tax haven investors buy more Korean stocks on days after a market rises and sell more on days after it falls. They also buy more of the stocks that outperformed the market the previous day. These results mean that foreign investors from tax havens are positive feedback traders. Finally, I examine whether foreign trades from tax havens have a significant impact on stock prices and increase the volatility of stock returns. In the first study, I select event days with large net purchases (sales) from tax haven investors, and compute abnormal returns for 11 days surrounding these events. The null hypothesis that tax haven investors do not have an effect on the Korean stock market can be rejected if significant abnormal returns follow large trades from tax havens in the same direction. The results show that both large purchases and sales from tax havens have a significant price movement within the event days and that the impacts are larger for purchases. In particular, the price impact of large purchase trades from tax havens persists one day after the event, and their cumulative abnormal returns are significantly positive for five days. These results mean that large trades by tax haven investors have a significant price impact on Korean stocks. In the second study, I use panel regression to examine the relation between stock volatility and trades from tax havens. The results show that stock volatility increases significantly as both net purchases and net sales from tax havens increase. Overall, the results in this paper allow the conclusion that capital flows from tax havens have significant effects on the Korean stock market. It is thus necessary for us to know who the tax haven investors are and what they do. However, tax havens remain domains of secrecy. This paper supports the recent efforts of the OECD and G20 to increase the transparency of capital flows from tax havens.

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The assets under management (AUM) of the Korean National Pension Fund (NPF), which started from 530 billion won in 1988, reached 426.9 trillion won by the end of 2013. This is the fourth largest pension fund in the world. Over 99% of the Korean NPF portfolio is comprised of finance sector holdings and the NPF’s performance thus depends on the management of financial sector investments. For many years, major investment vehicles in the NPF portfolio have been domestic bonds, domestic stocks, foreign bonds, and foreign stocks. Recently, alternative investments have become important parts of pension portfolio management. It is common to find alternative investment products such as real estate, infrastructure, private equity, commodities, and hedge funds in various sovereign pension portfolios. As alternative asset classes have little correlation with traditional investments, they help to diversify portfolio risk and also extend portfolios’ efficient frontier. In consequence, the proportion of alternative investments among global pension funds increased from approximately 7% in 2003 to 17% in 2012. The Korean NPF has followed this trend. The amount and proportion of alternative investments in the NPF portfolio steadily increased to reach 40 trillion won and to account for 9.4% of the total portfolio as of the end of 2013. However, few studies have been conducted on the management and performance of alternative investments in Korea. This study explores a way to construct the optimal alternative investment portfolio for the Korean NPF using both the Markowitz mean-variance and Black-Litterman models. With six asset classes, we use a proxy for the fund’s alternative investment portfolio to test which of the two optimization models is more appropriate for improving portfolio performance. We also construct an alternative investment portfolio with eight asset classes, adding commodity and hedge funds, which are currently excluded from the Korean NPF portfolio, to examine whether including these can enhance the portfolio’s efficiency. The main results of this study are as follows. First, we construct the optimal alternative investment portfolio with the Markowitz mean-variance model using the historical average returns of various alternative investment assets as proxy for the equilibrium expected returns. However, the model is extremely sensitive to changes in the input variables and often converges to the corner solution, which allocates unreasonably high weights to one or two assets. This reduces the advantages of portfolio diversification. Second, the Black-Litterman model has been devised to improve these limitations of the mean-variance model. It combines the equilibrium expected returns embedded in a market portfolio with managers’ views on its future asset performance. The model alleviates the extreme asset allocation problem. Thus, we suggest that the Black-Litterman model can be more appropriate so long as managers have marketforecasting capabilities. Finally, we confirm that including commodity and hedge funds in the Korean NPF alternative investment portfolio can improve its efficiency, as long as the fund has appropriate market-forecasting capabilities and imposes reasonable portfolio weights restrictions in asset classes. We consider the Black-Litterman model, which reflects managers’ views on future performance, in preference to the mean-variance model. We provide new insights into asset allocation methodology for the Korean NPF, which has mainly conducted asset allocation using a Markowitz-type mean-variance model. Some of the current alternative investment segment benchmarks used in the Korean NPF do not explain the variance and covariance of their asset classes, and we propose new benchmarks to replace them. Considering the growing prominence of the alternative investment portfolio in the Korean NPF, we suggest that continuous research effort should be made in this area to further improve the performance of the fund.

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