In line with Basel Ⅱ capital guidelines financial institutions have developed internal credit rating systems to mainly assess credit risk. Meanwhile, ever since introduced in Ohlson(1980)’s seminal paper, conditional default probability models, such as logit and probit, have been universally adopted as a standard credit risk model while neglecting significant theoretical progresses that have been made in this field in the recent years. Further, for nearly half a century since Altman(1968) the older model has been also actively utilized in evaluating firms’ financial information as a way to gauge the default risk. Meanwhile, credit theories claim that credit risk is likely to be influenced by macroeconomic environments. In fact, a large body of literature has provided evidence that credit risk is closely related to the state of an economy. If it is really so, then we should take into account salient macroeconomic characteristics as the determinants of credit risk in order to accurately evaluate systematic risk. However, it is difficult for a static default probability model based merely on cross-sectional accounting information to fully account for credit risk dynamics affected by volatile business cycles. Moreover, there has been no consensus established on what financial ratios should be benchmarked in making default prediction in spite of empirical evidences. For these reasons, this paper empirically examines how macroeconomic characteristics as well as firm-specific factors are being used to evaluate credit risk through random effect probit model. To do this, we looked into an unbalanced panel data set of small and medium-sized enterprises(henceforth, SMEs) for a 10 year period of 1997 to 2006. In addition, it is important to note that previous research has not fully delved into the effect of firm age on credit risk while credit risk is known to be largely dependent on firm duration. In this regard, the default probability model can be useful in identifying default and non-default firms as well as the factors contributing to firm failures; however, such framework does not reveal much information about the timing of a default. To improve on these potential short comings, the Cox proportional hazard model and the Kaplan-Meier survival analysis were performed to demonstrate whether credit risk would actually depend on firm duration. However, the Cox model is still vulnerable to the censored data problem. Thus, Cox regression was applied to start- up firms’ sub-samples from 2000 to 2006. The accounting dataset is obtained by Korea Credit Guarantee Fund and Korea Enterprise Data Co., Ltd. The main results of empirical analysis can be summarized as follows: First, utilizing quarterly data for the period between 1990Q1 and 2008Q4 we estimated cross-correlation coefficients, which is to shed light on the relation between macroeconomic variables and loan default. Loan default is proxied by the default amount of loans guaranteed by Korea Credit Guarantee Fund. We found out that loan interest rates, government bond yields, and term structures rather than inflation and unemployment rates are closely related to loan default. Second, most financial data pertaining to idiosyncratic risk factors appear to be statistically significant in both probit and Cox regressions, including: sales growth; cash ratio calculated as cash and cash equivalents divided by total assets less cash and cash equivalents; profitability ratio defined as EBIT divided by total assets; and solvency ratio proxied by equity capital as a percentage of total assets. They are, in fact negatively related to default probability even after controlling for firm size and industry as well as time effects. This result suggests that companies with healthier financial status are less likely to go default on their debts. Third, some of macroeconomic factors which are often blamed for being drivers of systematic risk fail to properly function in the assessment of default probability for SMEs. Nevertheless, empirical results revealed that models with variables representing financial market conditions, such as government bond yields, loan interest rates, KOSPI, and foreign exchange rates, are more significant factors for estimating default probability than other macroeconomic factors such as real GDP and inflation proxied by growth rate of consumer price index. The results using lagged macroeconomic variables are fairly similar to the former. In short, macroeconomic characteristics appear to be salient in assessing macroeconomic condition but probit models with macroeconomic variables are inferior to those with time dummy variables as compared with pseudo R-squared. Fourth, we find that there exists a negative relationship between credit risk for SMEs and their firm ages in Korea. The Kaplan-Meier analysis shows that a hazard rate steeply increases over time during the first 4 years of a firm life. Afterwards, hazard rate decreases, resulting in a hump‐shaped curve with time. Through the survival analysis we could also find out that a non-linear relationship exists between hazard rate and firm age. This evidence supports the empirical results of Bonfim(2009). Finally, the larger firm size is or/and the more collateral increases, the less credit risk increases. Firm size is defined as the logarithm of total assets and collateral as the share of tangible assets on firms’ total assets. Empirical results from the Cox model show that profitability ratios and collaterals are more useful than macroeconomic factors on default probability measurement of start-up firms. Of other factors, government bond yield is positively correlated with credit risk in start-up SMEs. From these findings, it may be safer for us to conclude that both macroeconomic characteristics and firm- specific factors play important roles in estimating default probabilities for SMEs. It is worthwhile to note that our study resulting from an extensive accounting data set of more than 21,000 SMEs minimizes the likelihood of sample selection bias which is one of the drawbacks of prior default prediction models.

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Based on Harrison and Pliska(1981)’s no arbitrage equilibrium theory, Markose and Alentorn(2005) introduced an original analytical closed form solution for generalized extreme value distribution (GEV) in the European options. They showed that the three parameter GEV based risk-neutral density function for asset returns has great flexibility in defining the tail shape implied by traded option price data. They also found that the GEV option pricing model not only accurately captures the negative skewness and higher kurtosis of the implied risk neutral density but also delivers the market implied tail index that governs the tail shape. Hence, the model allows accurate estimation of the risk neutral density function by including extreme values and fat tails. Meanwhile, Aït-sahalia and Lo(2000) and Panigirtzoglou and Skiadopoulos(2004) have argued that Economic VaR, calculated under the option market risk neutral density, is a more relevant measure of risk than historically based VaR. Economic VaR can be seen as a forward looking measure to quantify market sentiment about the future course of financial asset prices whereas historical or statistically based VaR is backward looking based on the historical data. Thus, in this paper adjusting Markose and Alentorn (2005)’s closed form solution to improve the model stability for in-sample-fit and out-of-sampling pricing, we empirically investigate the usefulness of the adjusted GEV model implied in the KOSPI 200 index options prices in terms of effectiveness for value at risk(VaR). As benchmark models, we use two-lognormal mixture model(TLM) and variance-gamma model(VG) as well as Black-Scholes model(BS). Because TLM is the weighted sum of two Black-Scholes solutions, the model can relax the assumption of the lognormal distribution. And variance gamma process is obtained by evaluating the Brownian motion at a random time change given by a gamma process. So variance-gamma model can relax the assumption of the geometric Browian motion. As time-series model for comparative analysis, we use not only normal model but also GJR-GARCH model which can reflect the presence of excessively fatter tails and pronounced skewness, reflecting strong volatility clustering. To estimate parameters for each option pricing model, the non-linear least squares approach is applied to minimize the sum of squared errors between the model and the market prices. As for the back-testing of value at risk, we examine the number of violations, mean violation, and maximum violation. For the statistical testing of the performance, the frequency tests of Christoffersen’s conditional back-testing procedures are examined. The Christoffersen approach enables us to test both coverage and independence hypotheses at the same time. Moreover, if the model fails a test of both hypotheses combined, this approach enables us to test each hypothesis separately so as to establish where the model failure arises. The hypothesis of unconditional coverage means that the expected frequency of observed violations is precisely equal to observed violation. The hypothesis of independence means that if the model of VaR calculation is valid, then violations must be distributed independently. We also wonder whether it is helpful to eliminate the non-tail information, in which case we consider the whole return distribution equality tests by using the Berkowitz methodology. In this way, we aim to investigate whether the estimated densities are equal to the true densities not only in the tails of the density but also in the full range area of the density. Back-testing results of VaR show that, of all the models, GEV yields the least number of violations for the industry standard for 10 day VaR at the high confidence level of 99%. Because the risk-neutrality assumption was strongly rejected by the market data due to the second state variables such as the negative risk premium for the stochastic volatility and jump fear, the preference for moments of higher order than the variance, heterogeneous beliefs and risk preferences and market inefficiency and imperfections, call option prices are not perfectly correlated with put option prices and the information contents of the call option price are different from those of put options market price. So, under the non-complete market and the limited arbitrage, we examine whether the information implied in call(or put) option market price is more useful than that which is inferred from both call and put option market prices. The results show that for the non-complete put option market, the performance of GEV is improved much more incrementally than that of the other models. However, in the entire density forecast evaluation, GEV is not as useful as it is for the performance in the tail portions of the implied distribution.

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Employee stock options have been the representative compensation system since they were adopted in 1997 in Korea with the change into the performance culture. Recently fair valuation of employee stock options(ESOs) has become a significant issue not only because they can measure their incentive effects but also because the Accounting Standards require ESOs value to be expensed for documenting financial statements. ESOs, which are inalienable and forfeitable, exhibit different exercise patterns from standard options. Prior researches related with empirical exercise patterns of ESOs exhibit that ESOs are prematurely exercised soon after the vesting period is over and the early exercise patterns are influenced particularly by risk aversion(Huddart and Lang, 1996; Carpenter, 1998; Bettis et al., 2005; Boyd et al., 2007). Kim and Jung (2009) analyzed the Korean ESOs and showed that stock options are exercised approximately 3.15 years after being granted, and these early exercise patterns were found to be influenced by risk aversion, profitability through exercise and firm characteristics. There are ESO valuation models reflecting these ESOs features such as extended American option model(Carpenter, 1998) and Utility-maximization model(Huddart, 1994; Kulatilaka and Marcus, 1994). The one adjusted the simple American option model by adding an exogenous parameter, ‘stopping state’, in which the employees or executives automatically exercise or forfeit the option. The other adopted the employee’s utility function of CRRA(constant relative risk aversion). Employees exercise their stock options when their expected utility, influenced by their risk aversion and outside wealth as well as stopping state, is maximized. But, generally, accounting practitioner estimate the fair valuation of ESOs using just either the modified Black-Scholes model, which adjusts the option’s life to the expected life and subtracts the cancelation, or typical American option model, which can be exercised prior to maturity. The aim of this study is both to look for an ESO valuation model that can best predict the actual exercise pattern. Furthermore, we are to review whether the expected life of ESOs that are currently posted on the financial statements fits the actual exercise pattern. This analysis helps us know if accounting practitioner estimate the expected life of ESOs appropriately considering the ESOs’ features and the correlation between stock price and the timing of exercise. The process of analysis is like followings; First, we have to calibrate some unobserved parameters; stopping state in extended American option model and risk aversion, outside wealth, and stopping state in utility-maximization model according to the method of Carpenter (1998) and Bettis et al. (2005). To do this, we set the mean exercise pattern of sample the base exercise pattern, searching the best unobserved parameters showing the closest to the base exercise pattern through the grid-search method. Second, we calculate the expected exercise pattern of each firm using calibrated parameters(stopping state, risk aversion, outside wealth) and observed parameters of its own; volatility, dividend rate, vesting date, risk-free rate, expected return. Third, we evaluate which option model forecasts most accurately among models; modified Black-Scholes model, American option model, extended American option model, Utility-maximization model. Also we analyze whether the expected life of ESOs that is currently posted on the financial statements forecast properly by comparing the forecast error such as the mean error, the percentage error, the mean absolute error, and the square root of the mean squared percentage error, and by the regressions of the actual exercise variable on the model forecast. We analyzed a total of 159 exercised employee stock options for the years between 2000 and 2008. We limited the sample to ones that we can obtain the characteristics of stock option grant and exercise and the firm specifies the estimates of the characteristics of ESOs on the footnote of financial statement such as expected life of their own. The results are like followings; First, the analysis of 159 stock options in this study indicates that among many theoretical ESO models, the extended American option model appears to be the best valuation model in predicting the expected stock-to-strike ratio and the expected life of ESOs. This result is encouraging and practicable because extend American option model doesn’t assume the risk aversion which is very difficult to observe and presume. So, we can estimate the fair valuation of ESOs without using the elaborate model such as utility-maximization model. Second, the officially posted estimate on the financial statements, on the other hand, didn’t have as good a predictability as the model, and the correlation with the actual exercise period was not even close to the statistics. Consequently, proper measures should be taken in order to estimate the expected life based on the ESOs features such as early exercise and forfeiture rate in the process of fair valuation of ESOs for documenting financial statements.

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The relationship between fund performance and cash flows is very important to fund investors, fund managers, and management companies alike. As is the case in the U. S., many studies have shown that better-performing funds have larger cash flows. This study investigates the relationship between fund performance and cash flows in Korean equity fund markets, and shows the behavior of investors in response to fund performance. Very few studies have considered Korean fund market's unique features. In 2005, the Korean fund markets and industry have faced structural changes that affected the behavior of investors. Based on the structural changes, we show the relationship between fund performance and cash flows. Since 2000, Korea has witnessed great capital influx due to great market expansion. Investors began to be aware of the risk and reward relation of equity funds, and are able to distinguish equity funds from bond funds and bank savings. At the same time, nominal interest rates have drastically declined. As a consequence, the equity fund market has started to attract investors seeking higher returns on their investments. In line with the changing climate of financial markets, the Korean government has allowed commercial banks to conduct fund sales business using their extensive retail networks. As expected, sales businesses by commercial banks have helped accelerate the rapid growth of equity funds. To meet growing investors’ demands, investment management companies have devised dollar cost averaging techniques for equity mutual fund investments. They could succeed in launching a host of new equity funds that were designed specifically for dollar cost averaging investments. As a result of these adjustments, by the end of 2004, the demand base of equity funds was further strengthened with much larger market share. Moreover, the assets under management of equity funds following the preponderant dollar cost averaging investments have also begun to grow rapidly, which has provoked structural changes in the Korean mutual fund market. By fully taking into account such unique features and developments in the Korean fund markets, we investigate the relationship between fund performance and cash flows. For this study, fund data are generously provided by Zeroin and FN Guide, Korean financial data providers. The period for empirical analysis runs from January 2001 through December 2007. A total of 223 equity funds are selected among 1,117 public equity funds which have total net assets over 50 billion Korean won on average. One thing that should be noted here is ways in which class funds are handled to make sure to prevent the problems of fund replication. Nowadays, like in the U. S., most funds in Korea are established as class funds which can be included in the same portfolio but with different fee structures. For the purpose of empirical analysis, hence, just a fund should be selected among the same class funds. In this study, in order to prevent the replication bias, only the largest class fund is selected. To investigate the effect of equity fund performance on fund flows, we regress fund flows on equity fund performance and other control variables. According to the previous literature, control variables include standard deviation of past fund returns, past fund flows, market flows, log of total net assets, fund age, and some related dummy variables. Additionally, we employ a switching regression model to reflect the effect of structural changes of fund markets on the relationship between fund performance and flows. The overall results are as follows. First, as expected from the previous U.S. studies, better-performing funds have larger monthly cash flows than the other worse-performing funds. That is to say, investors base their fund investment decisions on the performance. Second, we find that fund performance and cash flows are positively related only for the period of 2005∼2007, based on which we conclude that the structural changes of the fund market affect the performance-flow relationship. Third, we observe the effect of start- up funds caused by enormous cash flows into start-up funds, but it does not affect the conclusion of this study. Also, we do not find any survivorship bias in the Korean fund market. To empirically prove the absence of start-up fund and survivorship biases, we employ both the direct and indirect approaches. Fourth, the best-performing funds in general induce greater cash inflows than do the worst-performing funds. As is the case in the U. S., therefore, we conclude that there exists an asymmetric relationship between fund performance and cash flows for the Korean equity fund markets. We also find evidence supporting the effect of structural changes on the relationship between fund performance and cash flows. Unfortunately in Korea, due to its relatively short history of fund markets and lack of data availability thereof, sufficient studies have not been conducted to fully understand the behavior of fund investors. The increasing number of behavioral finance analyses underlines the importance of understanding the behavior of fund investors for both protecting fund investors and further advancing fund industry. Therefore, we believe that this study could effectively stimulate further research.

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The previous literature on the effect of corporate governance on firm values raises a question on the efficiency of the stock market. One line of research involves many papers supporting that good corporate governance leads to higher firm values as measured by the Tobin’s Q. Papers by Ashbaugh et al. (2004), and Byun et al. (2008) among others belong to this group claiming that reduction in agency costs helps to increase firm value by reducing the cost of capital. On the other hand, there are papers showing that the information on corporate governance is not fully reflected in the stock prices; therefore, investors may still realize abnormal returns by investing in firms with good corporate governance (Gompers et al., 2003; Bebchuk et al., 2009). These two results are not consistent in terms of market efficiency since the first group of papers implies that information on corporate governance is already reflected on the stock price of the firms while the second group of papers implies that the information is not fully reflected on the stock prices. In this paper, we attempt to reconcile these two contradictory findings by providing evidence that the realization of the effect of good corporate governance is contingent on the level of firms’ information asymmetry. We empirically show that good corporate governance of a firm reduces the cost of equity capital only when the information asymmetry of the firm is relatively at a low level. Practically, the information on corporate governance such as ownership structure, board of directors, shareholder right protection, and audit committee is abstruse as well as hard to access. In Korea for example, the Corporate Governance Service evaluates the governance level of the firms listed on the Korea Exchange, but does not disclose corporate governance scores to investors except for the best and second-best firms. Because of the incomprehensibility of corporate governance level, stock investors may not fully reflect the information on the corporate governance of a firm on its stock price, so that reduction in the cost of equity capital of the firm may not be attained. Investors’ perception of corporate governance, therefore, is an important issue for the efficiency of a stock market and the financing costs of related firms. We hypothesize that the level of information asymmetry of a firm affects the level of the investors’ understanding of the corporate governance of the firm and, accordingly, the value of the firm. To the authors’ knowledge, this is the first study ever conducted to show that the effect of good corporate governance on the firm value depends on the level of information asymmetry of a firm. Previous studies have investigated the relation between corporate governance and firm value without taking into account investors’ perception of corporate governance. This paper, however, complements the existing results by considering the impact of investors’ understanding of their firms’ corporate governance. For the analysis, we divide the sample firms into two groups based on their level of information asymmetry. The number of analyst coverage is used as a proxy for information asymmetry. Then, we construct a hedge portfolio which is long in good governance firms and short in weak governance firms by each group, and estimate the abnormal return of the hedge portfolio of each group using CAPM and Fama-French (1993) three-factor model. The results show that the abnormal return of the hedge portfolio is statistically not different from zero for the low information asymmetry group, which implies that information on corporate governance is efficiently reflected on stock prices for the group. On the other hand, the abnormal return is significantly positive for the high information asymmetry group, which suggests that information on corporate governance of those firms is not fully understood by the investors and, therefore, is not fully reflected on the stock prices. We also regress Tobin’s q on corporate governance scores and find that corporate governance has significantly positive effect on Tobin’s q only for the low information asymmetry group. The effect of corporate governance on Tobin’s q is insignificant for the high information asymmetry group. In summary, we find that investors do not really reflect the information on the corporate governance of firms on their stock prices and their financing costs in case of higher information asymmetry. On the contrary, we show that good corporate governance positively affects firm values with lower level of information asymmetry.

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This paper investigates the spill-over effects of the U.S.’s and the euro area’s macroeconomic news on the Asia-Pacific interest rates. We find that higher than expected news from these two economies raises the conditional mean, and most news, regardless of signs, elicits the associated volatility of daily returns of the Asia-Pacific interest rates. We also find supporting evidence for the two possible channels of the spillover effects of macroeconomic news, namely the policy reaction expectation and the integration mechanisms. More importantly, we reveal that the U.S.’s unemployment rate news and the euro area’s inflation news have the strongest impact on the first two moments of the Asia-Pacific interest rates daily returns. These findings are consistent with the relative size of these two economies and the monetary policy frameworks conducted at the U.S.’s Federal Reserve and the European Central Bank.

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The smart money hypothesis states that investor money is “smart” enough to flow into the funds that will outperform in the future; that is, the investors have an ability to identify superior managers and invest accordingly. The first studies to address this issue (Gruber, 1996; Zheng, 1999) find that, indeed, funds that receive greater net money flows subsequently outperform their less popular peers. This pattern was termed the “smart money effect.” Also, more recent research (Keswani and Stolin, 2008) finds a robust smart money effect in the United Kingdom and the U.S. The effect is caused by buying (but not selling) decisions of both individuals and institutions. On the other hand, Sapp and Tiwari (2004) could not detect the smart money effect when they applied a more appropriate performance evaluation procedure that takes the stock returns momentum effect into account. To understand better how different types of investors make their fund buying and selling decisions, we briefly present evidence on the determinants of mutual fund money flows in Korea. Our dependent variables are net flows and their components that are expressed as proportions of fund value at the end of the month. We would expect lagged fund cash flows and fund returns to be the primary determinants of the fund cash flows. Control variables are logarithms of fund total net assets (TNA) and fund age, as well as fund total expenses (Chevalier and Ellison, 1997; Sirri and Tufano, 1998). Our results, based on the time series of cross-sectional regression coefficient estimates, indicate that our flow variables are persistent. Coefficient estimates for lagged flows and TNA are always positive and significant. But those for past performance, fund age, and fund expenses are negative and significant. In this paper, we examine the smart money issue with Korean daily data (January 2002 to May 2008). Owing to data constraints, all of the above studies work with the aggregate money flows to funds. All investors are aggregated, and sales are offset by repurchases. Furthermore, not having access to exact net flows, these papers approximate such flows using fund TNA and fund returns. But our data allow us to conduct a stronger test for the smart money effect by using daily data on exact fund flows, and to gain greater insight into investors’ decisions by considering separately the sales and purchases of individual and institutional investors in the Korean fund market. So we observe exact flows rather than approximations based on fund values and fund returns. To examine the smart money controversy, a simple way is to evaluate the performance of all “new money” put into mutual funds by investors. A natural benchmark against which to measure the success of these new investments is the performance of “old money”, that is, of assets already in place before the latest round of investments. We characterize our fund portfolios using what Zheng (1999) calls “the portfolio-level approach.” Specifically, each month we conduct a Carhart (1997) four-factor regression for every fund portfolio to obtain our four estimated factor loadings. Our new money portfolios don’t deliver higher alphas than old money fund portfolios. In other words, new money is not, in fact, smart. We also use a different methodology above, which involves sorting funds into positive and negative flow groups. The results are similar. On the other hand, in order to examine the pervasiveness of Korean investors’ ability to select superior funds, we compare equally weighted groups of popular and unpopular funds. This approach curtails the influence of funds with extreme flow observations. To understand which flow components drive this result, it is desirable to apply the same methodology to all the flow variables comprising net flows. Specifically, each month we sort funds using our measures of normalized money flows into high flow portfolios and low flow portfolios. We then compare the risk-adjusted performance of equally weighted high and low flow portfolios. The results show that the average alphas of the high flow portfolios are not larger than those of the low flow portfolios. This means that we no longer find this smart money effects. Only the result from the trading strategies confirms adverse Zheng (1999)’s information effect, that is, relatively investors can beat the market by investing in negative money flow, low money flow funds. To verify that the smart money effect holds throughout the empirical period and appraising methodology, we use alternatives approach. First, we repeat our analysis separately for the first and last halves of our Jan. 2002 to May 2008 study full period. Indeed, the contributions of the two subperiods are of similar results. Second, we show portfolio-level approach results using Ferson and Schadt’s (1996) conditional performance evaluation. Specifically, we follow Wermers (2003) and Kacperczyk et al. (2005) in implementing the conditional version of the Carhart (1997) model with the risk-free rate and term structure premium and credit spread representing the conditioning set of publicly available information. The results are qualitatively similar to those under the unconditional portfolio approach. There is no smart money effect on the basis of net flows, inflows and outflows. The results once again confirm that inflows and outflows don’t give rise to the smart money effect in the Korean fund market.

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The financing market accessibility is an important factor to consider when investigating firms’ financing choices. However, many studies on the capital structure adjustment speed, derived from traditional capital structure theories, have largely ignored the importance of financing market accessibility especially when they investigate the speed toward the target debt ratio. Thus, this paper investigates the role of financing market accessibility in the process for a firm to adjust their debt ratio to its target debt ratio. Since Modigliani and Miller suggested irrelevance proposition regarding the relationship between leverage and firm value in 1958 (Modigliani and Miller, 1958), many researchers have raised the question about the validity of the argument. Initially, they questioned whether the Modigliani and Miller’s irrelevance proposition is well supported by the available firms’ data and whether the imperfections of capital market make firm value links to debt ratio. A trade off theory was created on the basis of the latter case, claiming that a firm would select a target debt ratio by taking into consideration both costs and benefits of the debts. While Modigliani and Miller (1963) suggested a correction theory about irrelevance proposition, Baxter (1967) presented the bankruptcy cost theory arguing that the increase of the expected bankruptcy costs could countervail the tax shield of debt as the debt ratio increases. Jensen and Meckling (1976) showed the optimal debt ratio could be influenced by the agency cost occurring because stockholders entrust managers with the firm’s management. Since Modigliani nd Miller’s correction theory (Modigliani and Miller, 1963), the trade off theory developed by many researchers suggest that the optimal capital structural is determined by the relationship (trade off) between cost and benefit of using of debts. Survey result suggested by Graham and Harvey (2001) shows that 81% of 392 firms indeed consider a target debt ratio (or range) an important factor when they make their financing decisions. However, Myers (1984) refutes this trade off theory of capital structure with an updated version of Donaldson’s (1961) pecking order theory, according to which asymmetric information leads managers to believe that the market generally underprices their shares (Flannery and Rangan, 2006). As a result, a firm’s investment is financed first with internal funds before the firm gets into debt if internally generated funds are not sufficient, and equity financing is used only as a last choice of financing instrument. In a pecking order theory, the observed firm’s leverage shows primarily the result of a firm’s historical profitability and investment opportunities. Firms have no strong preferences about their debt ratios and no obvious propensity toward adjusting leverage alteration caused by financing needs or operating profit (loss). Other theories about capital structure also do not support the view of timely convergence toward a target debt ratio. Baker and Wurgler (2002) argue that a firm’s observed debt ratio shows its cumulative ability to catch the opportunity which equity shares are highly evaluated; that is, stock prices fluctuate around their true values, and managers tend to issue shares when the firm’s market-to-book ratio is high (Flannery and Rangan, 2006). This market timing theory, on the other hand, argues that a firm’s manager continuously takes the advantage of information asymmetries to benefit current shareholders. Thus, this theory suggests, like the pecking order hypothesis, that there is no reversion to a target debt ratio if market timing is the dominant determinant on firm’s leverage. The pecking order and market timing theories suggest that firms’ managers, generally not aware of any leverage effect on firm value, do not endeavor to modify changes in leverage. On the other hand, the tradeoff theory of capital structure implies that the factors of market imperfection can damage both leverage and firm value, thereby forcing firms to take management initiatives to offset deviations from their optimal debt ratios (Flannery and Rangan, 2006). Thus, estimating the adjustment speed of capital structure could be an important first step in verifying conflicting theories of capital structure. Using manufacturing firms listed on Korean security markets from Jan. 1, 2001 to Dec. 31, 2008, this study analyses the relationship between financing market accessibility and capital structure adjustment speed toward target debt ratio. This paper shows that the capital structure adjustment speed overall increases when the debt and equity financing market accessibility is good. This result holds regardless of the use of book and market debt ratio as dependent variable. Furthermore, firms can adjust their leverage toward the target faster when they have good equity financing market accessibility than debt financing market accessibility. These results suggest that financing market accessibility is the crucial determinant of capital structure adjustment speed, and this finding should shed important light into ways for policy makers to support firms’ smooth debt and equity financing.

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The protection of environment in parallel with firms’ sustainable growth has never been such an important issue as it has become today when the environmental damages have begun to threaten the global ecosystem and the survival of many plants and animals including human beings. Evidently, increasing consumption and mass production of goods to satisfy incessant consumption needs are the most significant culprit of environmental damages. Therefore, companies must take responsibilities by changing their production processes and establish procedures to control the pollution created by their production processes. But firms would not initiate such environmental management activities unless they are certain of the positive effects of incorporating environmental elements in the company management since the major goal of firms is to maximize the profit. With this issue in mind, we attempt to provide a scientific evidence that is related to the environmental management of companies. Specifically, we investigate the effect of environmental management on firm value based on the sample of firms that received the National Environmental Management Award. This award was initiated by the Korean government in 1999 and is now the most prestigious prize in the environmental management area. It has been given to firms that invest a significant portion of their resources on the environmental activities. In order to win the Grand Prize the firm must have the records of continuous environmental management activities for at least three years. As such, these firms can serve as a good proxy for the better environmental management. The environmental management could have both positive and negative impacts on firm value. Typically, firms must spend a substantial amount of capital to install and implement the pollutant control, and it is definitely a cost factor in the short-run. However, the environmental management enables firms to upgrade their corporate image as a good global citizen, which can contribute to a sales increase. It also makes firms reduce the unnecessary or marginal inputs in the manufacturing process which can lead to a decrease in production costs. Or under the circumstances wherein many countries and regions strengthen the regulation on environmental protection, the environmental management could be especially effective in preventing costly environmental lawsuits that may occur when a company ignores the environmental factors. These long-term effects will have a positive influence on firm value. Therefore, the overall impact of the environmental management must be measured by an empirical investigation. In this regard, our OLS regression results indicate that firms with significant environmental management activities have a higher Tobin’s q value. Thus, we conclude that the environmental management activities by firms are not a waste of resources but actually contribute to the improvement of firm value. However, the positive relationship between environmental activities and the firm value could be spurious, since there could exist the endogeneity problem in the underlying process. In other words, it is possible that the firms with a higher value could engage in environmental management since they have resources to invest in such activities, not the other way around. In order to control the confounding effects caused by endogeneity among variables, we employ three different methods when analyzing the impact of environmental management on firm value. First, we control the firm fixed effects in panel data analysis to eliminate the possibility that the unobserved firm characteristics may generate spurious results. Second, we estimate the simultaneous equation model with two dependent variables where one of the endogenous dependent variables is a dummy variable that is also an independent variable employed to explain the other continuous dependent variable. Third, we examine the difference in firm value increase between environmental management firms and control firms by the difference-in-difference test. The difference-in-difference method allows us to observe the increase of firm value caused purely by the environmental management after controlling for the firm value changes over time and the firm value difference without environmental management. Even after controlling the endogeneity problem we obtain the results that environmental management has a strong positive relationship with firm value and the increase in firm value is economically significant. We also examine the characteristics of the firms engaging in environmental management. The results indicate that the environmental management firms are bigger in terms of total assets and sales. Most of them are also members of the 10 biggest chaebol groups and other remaining business groups that are subject to the regulation on shareholdings in other domestic companies. Since the environmental management often requires a huge amount of capital expenditure, these companies can reap the benefit of economies of scale in this regard. Then, it is understandable that bigger firms can more easily employ environmental management while, in fact, most of bigger firms are chaebol firms. Further, they should have an additional incentive to engage in environmental management, which is to countervail the negative publicity of chaebol as a whole. In addition, we find that environmental management firms spend more on advertisement and R&D and have a higher profitability and a larger cash flow from operating activities compared to the firms in control group. We conjecture that profitable firms with high cash flows are better positioned to perform environmental management since they have more resources to allocate on environmental activities. However, environmental management firms in general have shorter business histories and higher fixed debt ratios.

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This paper explores the impact of multidimensional uncertainty on people’s incentives to acquire information using the Kyle model of informed trading. In a single period Kyle model, the informed trader is worse off if he acquires information (called non-fundamental information) about the level of noise trading. This is due to the fact that the informed trader, by betting against noise traders, reduces the variance of the total noise related trading; he gains from such a bet, but loses part of profits from fundamental trading. If there is a speculator who trades only on non-fundamental information, the informed trader is better off acquiring information that is dominated by the speculator’s whereas acquiring non-fundamental information that is not dominated could make the informed trader worse off than without such information. Moreover, the informed trader is much better off sharing such dominated information with the speculator after acquiring it. When there are two traders who have fundamental information, the less informed trader has stronger incentives to acquire non-fundamental information. We also show that non-fundamental information provides a better return if the noise trading has a bigger variance than the asset value. The overall picture emerging from this exercise is that traders who focus on fundamentals do not have strong incentives to acquire non-fundamental information.

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