Structured derivatives markets, including equity linked securities (ELS), derivatives linked securities, structured notes and credit linked notes have grown dramatically since the mid-2000s in Korea, but little attention has been paid to how much these securities contribute to the improvement of investors’ performance from a portfolio perspective. This study fills the gap by examining the optimal portfolio choice of investors who are allowed to invest not only in stocks and bonds, but also in ELS (especially auto-callable ELS). As ELS are generally regarded as alternative assets to enhance portfolio performance, their economic benefits should be considered from a portfolio perspective rather than on a stand-alone basis. In addition, even though the majority of ELS in Korea include an auto-callable feature, there is little study for this specific type of product. This study is the first step in understanding the investment benefits of ELS. In our analysis, we first estimate the return distributions of the KOSPI200 index, a risk-free asset, and a typical auto-callable security linked to the KOSPI200 index. Taking the complexity of the payoff structure into consideration, it is very difficult to theoretically determine the return distributions of the auto-callable ELS. Unlike stocks and bonds, even from an empirical point of view, any standard statistical method to derive the empirical distributions from the observed historical returns cannot be applied to the auto-callable ELS as we do not have a large enough sample (i.e., independent or non-overlapping return data) to obtain a reliable estimate. For example, even if we assume that all of the auto-callable ELS issued during the past 10 years were exercised early on the first possible exercise date, the maximum number of independent returns we can observe is only about 20, and thus we cannot estimate the return distributions in a valid manner. To reconcile this problem, we estimate the GJR-GARCH (1,1) model from the observed returns of the KOSPI200 index from 2003 through 2015, and then derive the empirical return distributions of the ELS via Monte Carlo simulations using the estimated GARCH model. Second, we use three portfolio selection models to derive investors’ optimal portfolio choice given access to the ELS market: (1) the conventional expected utility theory, (2) the prospect theory of Kahneman and Tversky (1979), and (3) the safety first theory of Telser (1956), which is the cornerstone of the behavioral portfolio theory with mental accounts proposed by Das, Markowitz, Scheid, and Statman (2010). Our main empirical findings are as follows. First, auto-callable ELS are shown to be unnecessary for the construction of the optimal portfolio for all investors trying to maximize their expected utility, regardless of their degree of risk aversion. Second, the auto-callable ELS do not improve performance for the majority of loss-averse investors. That is, the auto-callable ELS are regarded as a redundant asset according to both expected utility theory and prospect theory. Third, we find that auto-callable ELS are valuable assets that play a key role in improving the portfolio performance of the majority of investors who make investment decisions based on the safety first theory. This suggests that auto-callable ELS can be a very effective investment tool for investors who try to maximize the expected returns of a portfolio with a restricted probability of failing to reach a pre-specified threshold return. The difference in our empirical results depending on the portfolio selection models arises fundamentally from the structural characteristics of the auto-callable ELS. Their risk and return profile indicates that losses occur infrequently, but when they do, the expected losses can be considerably large. Similarly, although gains occur frequently, they tend to be very marginal. These characteristics of auto-callable ELS are very similar to those of selling deep out-of-the-money (OTM) put options. In this sense, for investors assumed by safety first theory, who measure risk by the frequency rather than the amount of expected losses, auto-callable ELS can be effective in enhancing the investment opportunity set. However, for investors with expected utility theory or prospect theory preferences, the relative advantages of auto-callable ELS over common stocks and bonds are weakened as the portfolio risk is generally recognized and measured by the expected losses rather than the frequency of losses. Finally, our robustness test results indicate that the findings remain valid when we consider other types of auto-callable ELS, issuing costs, and the effect of the global financial crisis.

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This paper analyzes the information value of a credit watchlist in the Korean credit rating market. Credit rating agencies issue credit watches to indicate the direction of ratings changes within a short time horizon of three months on average. Credit watches are marked as either up, down, or uncertain. A watch is usually triggered by discrete corporate events such as mergers, acquisitions, restructuring, and announcements of plans expected to affect credit quality, or by trends in the issuer’s operations or financial weaknesses such as financial performance, liquidity and leverage, and accounting fraud. The watchlist either improves the information-certification role of credit ratings (delivering information), or allows rating agencies to influence the risky choices of issuing firms by threatening them with imminent rating downgrades and subsequent investor reactions (implicit contract). This study tests these two different explanatory lines to determine the information value of the credit watchlist. This study also identifies the features of firms with rating changes that are preceded by credit watches, and the factors affecting the agreement between a credit watch and subsequent rating changes. In addition, it examines whether the market reaction to rating changes depends on whether it is preceded by a negative credit watch. It is observed that there is a greater proportion of credit watches marked as “down” in Korea than in the US, and that the credit watchlist has been operated quite conservatively. Using the Nice’s credit rating and watchlist data from 2000 to 2014, the results support the delivery of information argument more than the implicit contract argument. Most of the variables that represent delivery of information, such as size, fixed assets, and BBB rating, are statistically significant, whereas the only significant variable associated with an implicit contract is cash ratio. However, the watchlist by provisional evaluation and simultaneous announcement with rating change presents a role of the implicit contract as well as the delivering information A negative watchlist followed by a downgrade is more likely to occur with larger issuers, greater rating changes, and lower credit ratings. Moreover, the extent to which the direction of credit watches coincides with the direction of subsequent rating changes is greater when there is a shorter duration between the watchlist and the rating change, periodical evaluation, and lower credit ratings. In terms of market reactions to downgrades, the negative watch-proceeded downgrades rather than the direct downgrades exhibit greater negative cumulative abnormal returns, which deepen in investment grade, provisional evaluation, and simultaneous announcement of watchlist and rating change. Meanwhile, the issuing firm’s cumulative abnormal return is statistically significantly negative when a negative watchlist is issued, but insignificantly positive when a positive watchlist is issued. Therefore, the information value of the credit watchlist can be summarized as follows. First, the watchlist in the Korean credit rating market generally fulfills the delivery of information rather than the implicit contract role. Analysis of the characteristics of firms that are issued with a negative watchlist indicates that the proxies measuring the delivery of information, such as size, fixed assets, and BBB of credit rating, are statistically significant. The role of the implicit contract is also partly observed in that the downgrades are actually executed in less than seventy percent of the issued negative watchlist cases. Furthermore, the credit watches by provisional evaluation and simultaneous announcement with rating change are also observed to present the implicit contract role. Second, the watchlist provides more information about issuers with investment credit ratings than speculative credit ratings. There is a greater deterioration in negative cumulative abnormal returns for investment than for speculative grades when a negative credit watch is issued. This phenomenon also appears when the downgrade is subsequent to a negative credit watch. The watchlist is less likely to be issued to speculative or default credit ratings. Third, the watchlist together with rating changes magnifies a negative market reaction in Korea, which is inconsistent with the results for the US market due to the unique timing of announcements, as the watchlist tends to be issued simultaneously with rating changes. This study makes three contributions to the literature. First, it is the first study to document the watchlist in the Korean credit rating market. Most studies have examined market reactions with respect to rating changes. The findings will be useful for academics and practitioners. Second, the study comprehensively investigates the role of the watchlist in Korea and discloses the genuine economic function of the delivery of information. Finally, the paper suggests policy implications for encouraging more issuance of speculative grades, separation from grade changes, and periodic evaluations.

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Short selling is the practice of selling securities or other financial instruments that are not currently owned, and then subsequently repurchasing them in the near future to return borrowed securities to their owner. Short selling can play a positive role in the market. It increases market liquidity, contributing to efficient price discovery, and helps to expand the selection of investment strategies and risk management. However, short selling can also play a negative role, with naked short selling sometimes used to manipulate the market. During the global financial crisis triggered by the subprime mortgage crisis in 2007, the financial authorities in many developed countries implemented short-selling restrictions to stabilize financial markets, protect investors, and aid efficient price discovery. Most studies on short selling concern their relation with stock prices (returns), with less attention paid to the relation between short selling and volatility. In this study, we investigate the relationship between short-selling activities and stock return volatility in the Korean stock market using daily data on individual stock returns, stock trading volume by investors, and short-selling activities by investors. The sample period ranges from January 2007 to November 2012. Three types of traders are considered: individual investors, institutional investors, and foreign investors. We use several volatility measures: historical volatility, range-based volatility (Garman-Klass volatility or intraday volatility), implied volatility (VKOSPI or the volatility index), and conditional volatility, which is estimated from the GJR-GARCH model. Three kinds of short-selling activity measures are adopted as the major explanatory variable: logarithm of the money value of short-selling volume, the short-selling/stock trading volume ratio, and the share of short-selling volume by trader type. Miller (1977) and Diamond and Verrecchia (1987) suggest that policies that impose short- selling constraints increase volatility in the stock market. Such a policy was enacted during the sample period, allowing us to test the prediction that short-selling transactions as a whole increase volatility in the Korean stock market. However, the daily short-selling trading volume was found to exert a negative effect on the volatility of KOSPI index returns. In the case of short-selling restrictions, it turns out that such restrictions serve to reduce intraday volatility, conditional volatility, and the volatility index (VKOSPI), although the effect of a short-selling ban on volatility remains inconclusive. There are two short-selling ban periods in our sample period: the eight months from October 1, 2008 to May 31, 2009 (BN1) and the three months from August 10 to November 9, 2011 (BN2). The sample data show BN1 and BN2 to have a higher and lower volatility level, respectively. After empirical analysis, the short-selling ban was found to increase intraday volatility and the VKOSPI in BN1 and to decrease them BN2, which implies that such a policy measure does not have deterministic effects on volatility. When we classify short-selling trading volume by trader type, the short-selling volume of individual investors is observed to stabilize daily range-based volatility and the VKOSPI, whereas that of institutional investors destabilizes such volatility measures as historical volatility, range-based volatility, and the VKOSPI. Foreign investors’ short-selling volume increases none of the volatility measures. The finding that the short-selling trading activities of individual investors stabilize the stock market and those of institutional investors increase stock market volatility, whereas, in the stock market more generally, individual investors increase stock market volatility and institutional investors stabilize the market, is an interesting one. It implies that individual investors have an information advantage in short-selling trading, considering that their share of such trading volume hovers around 3%. This finding is consistent with that of Jung, Kim, and Lee (2013), who report that the short-selling trading activities of individual investors do not increase stock market volatility in Korea. Foreign investors stabilize the stock market through both short-selling transactions and stock trading activity. With regard to policy effects, we find that short-selling restrictions reduce intraday volatility, the VKOSPI, and conditional volatility. The short-selling ban initially prompted by the global financial crisis appears to have had limited effects, although the second prohibition clearly reduced volatility. Therefore, it can be concluded that short-selling regulations can stabilize the market if implemented in appropriate and timely fashion. A remaining puzzle is why individual investors’ short-selling activities reduce volatility, whereas those of their institutional counterparts increase it. The issue requires further analysis, and is left to future research.

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A random-end (RE) trading mechanism is an integral part of the call auction mechanism. The ending time of a call auction is not fixed, but can be extended in certain circumstances for a brief randomly-chosen span of time less than or equal to the “maximum duration.” RE mechanisms are intended, in part, to discourage the placement of spoofing orders. In this paper, we investigate the main characteristics of a specific RE trading mechanism, that which the Korea Exchange (KRX) employs at the opening and closing call auctions, and its effects on price discovery and stabilization. We are aware of four papers related to RE trading mechanisms. Medrano and Vives (2001) is a theory paper, whereas Hauser, Kamara, and Shurki (2012) is an event study analyzing market quality just before and after the adoption of the RE trading mechanism. Hence, neither paper illuminates the detailed functioning of RE mechanisms. The other two papers, Zimmermann (2013) and Eom and Park (2014), directly analyze the economic functions and effects of real-world RE mechanisms. The present paper is in line with Eom and Park (2014) in that it examines the KRX RE trading mechanism, but differs from it in that it performs cross-sectional analyses and analyzes spoofing orders, the discouragement of which was the main motivation for the mechanism’s adoption. Our sample comprises all 1,567 stocks listed on the KOSPI and KOSDAQ markets after filtering out a typical group of special-purpose stocks. We analyze all RE invocations occurring among the sample stocks during the daily opening and closing call auctions from January 2009 to December 2010. We use both daily and intraday data during our sample period. For real- time RE occurrence data, we first reconstruct the real-time order book from KRX Trade and Quote data, and then match our reconstructed order book against the complete set of RE occurrences provided by the KRX to validate the reconstruction process. We obtain the following results. First, at both the open and close, RE was invoked at least once for most stocks listed on the KOSPI and KOSDAQ markets. However, it was invoked most frequently for smaller, more volatile, lower-priced, financially distressed, or poorly managed stocks. The RE occurrence rate is consistent with market volatility. That of KOSDAQ is 2.1% on average, which is higher than that of KOSPI, at 0.8%. The disparity ratios between the projected price and potential price and between the potential price and opening (closing) price are 8.3% (8.2%) and -27.5% (-30.2%), respectively. The reversals in these ratios indicate that the RE trading mechanism makes a meaningful contribution to price stabilization for the opening and closing prices. The realized duration between the scheduled opening (closing) time and the real opening (closing) time is, on average, 1 minute 30 seconds, which indicates that the RE time is not drawn from a uniform distribution. Second, the opening process on the days on which RE occurred exhibits a different pattern from that on the days it did not occur, suggesting that sophisticated investors can identify the discrepancy and trade strategically, whereas other investors trade normally. Also, at the closing call auctions, the ratios of cancellation and correction orders to normal orders were overwhelmingly higher than those at the opening call auctions. Third, although the potential prices overshot to some extent, they were close to the average market equilibrium price formed during the five minutes after RE occurrence. Moreover, some of the overshooting was corrected during the RE period. These results imply that the RE trading mechanism contributes to opening price discovery and stabilization. Finally, many more spoofing orders were observed for the stocks for which RE occurred than for those for which it did not. Further, among the stocks for which RE occurred, spoofing orders were more than twice as numerous on the days of occurrence, with spoofing much more pronounced in the closing call auctions. In addition, at both the open and close, spoofing orders fell sharply after RE invocation, suggesting that the RE mechanism helps to discourage spoofing. In sum, our results suggest that the current KRX RE mechanism fulfills its purpose to some extent, that is, by improving price discovery and stabilization and reducing spoofing order submission, although more could be achieved. To increase the efficacy of its RE trading mechanism, the KRX should consider adjusting the current parameters. For example, it could set multiple RE invocations in succession, make the disparity rate more flexible to deal with situations as they develop, expand the RE period, and so on. The major European exchanges, which have been praised for providing some of the most sophisticated RE trading mechanisms in the world, would be a good benchmark.

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We construct the “betting against beta” (BAB) factor in Frazzini and Pedersen (2014) using Korean stock market data, and investigate the relationship between leverage constraints and stock returns. Frazzini and Pedersen (2014) extend Black’s (1972) capital asset pricing model (CAPM) with restricted borrowing by explicitly considering leverage and margin constraints that vary across investors and time. According to their model, investors who cannot use leverage overweight the high-beta assets in their portfolios, leading to the overpricing of those assets and subsequent lower returns. Unconstrained investors, in contrast, underweight (or short-sell) overpriced high-beta assets and buy low-beta assets with leverage. Frazzini and Pedersen (2014) show that their model with leverage constraints produces a security market line that is flatter than that predicted by the CAPM, with the slope depending on the tightness of the leverage constraints that investors face on average. Frazzini and Pedersen (2014) derive several testable predictions from their model, and they propose a BAB factor as a central portfolio whose pattern of returns captures the asset pricing effect of leverage constraints implied by their model. The BAB factor is a portfolio that holds low-beta assets, leveraged to a beta of one, and shorts high-beta assets, de-leveraged to a beta of one. The returns on the BAB factor correspond to a zero-cost (self-financing) investment strategy that longs low-beta assets and shorts high-beta assets, with the weights on the long and short positions adjusted in combination with leverage to ensure that the factor’s ex ante beta is zero. Frazzini and Pedersen’s (2014) model predicts the BAB factor to have a positive expected return and a realized return that decreases when leverage constraints become more binding. They test their model’s predictions by constructing BAB factors in a wide range of asset classes, including 20 international equity markets, Treasury markets, and corporate bonds and futures markets, and find evidence to support its predictions. We construct a BAB factor using the stocks listed on the Korea Stock Exchange, and investigate whether the relationship among leverage constraints, the beta, and risk-adjusted returns exhibits patterns consistent with the predictions of Frazzini and Pedersen’s (2014) model. The sample period is from April 1990 to Mach 2014. We find the average monthly return on the BAB factor to be significant both economically (1.32%) and statistically (t-statistic of 2.85). Its alphas (risk-adjusted abnormal returns) are also of sizable magnitude (CAPM alpha of 1.33% and Fama-French three-factor alpha of 1.25%) and statistically significant. These findings are consistent with the overpricing of high-beta stocks and underpricing of low-beta stocks arising from leverage constraints, as predicted by Frazzini and Pedersen’s (2014) model. The BAB factor is constructed using beta-ranked portfolio weights: lower-beta stocks have greater weight in the low-beta portfolio (a long position in the BAB factor), and higher-beta stocks have greater weightin the high-beta portfolio (short position in the BAB factor). This weighting scheme is designed to strengthen the beta’s effect on the alpha (i.e., the alpha is decreasing in the beta) in returns on the BAB factor. We examine the effect of different portfolio weighting schemes on the average returns on the BAB factor by constructing the factor using more conventional value-weighting and equal-weighting schemes. The results show the risk-adjusted return on the BAB factor to be substantially reduced in size and to loseits statistical significance when value-weighting is used, which indicates that the effect of leverage constraints on the underpricing of low-beta stocks is likely to be concentrated in small capitalization stocks in Korea. Accordingly, we classify stocks into three groups by market capitalization and construct a BAB factor within each group. We find that the BAB factor constructed within the small capitalization group shows a larger average (and risk-adjusted) return with stronger statistical significance. Moreover, when the proportion of trading by institutional and foreign investors is considered in addition to market capitalization when forming the BAB factor, we find the risk-adjusted return on the factor to be sizable and statistically significant when it is constructed using small capitalization stocks with a lower proportion of trading by institutional and foreign investors. These results suggest that the pricing effects of leverage constraints in Korea are concentrated primarily in small capitalization stocks heavily traded by individual investors. We also investigate the hypothesis of Frazzini and Pedersen’s (2014) model that the realized return on the BAB factor decreases when leverage constraints become more binding. We find that changes in the 91-day CP-CD spread and 3-year AA-rated corporate bond-government bond spread are negatively associated with contemporaneous returns on the BAB factor in Korea. These results are consistent with Frazzini and Pedersen’s (2014) finding that changes in the TED spread are negatively associated with contemporaneous returns on the BAB factor in the U.S. Taken together, our findings suggest that the pattern of returns on the BAB factor in Korea captures the asset pricing effect of leverage constraints faced by investors, as postulated by Frazzini and Pedersen (2014).

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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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