We examined in this paper whether the impact of liquidity on the expected stock return varies according to a firm’s payout policy. We used the daily relative spread as the proxy for illiquidity and treated it by the means of linear spline functions in order to measure the change of its impact on the expected return in each sub-range specified by those functions. KRX market data excluding the financial sector were used for the analysis during the sample period from 1999 to 2008. We had the following results. First, we found clear convexity for the stock-repurchasing portfolios when we checked the influence of liquidity on the expected return using the 2SLS regression including instrumental variables to control the potential endogeneity of the dummy variables indicating payout choice. The slope of the relative spread jumped precipitously to the sub-range [0.0044, 0.0070). On the other hand, mere concavity existed for the cash-dividend portfolios. The slope of the relative spread was nearly horizontal, and its statistical significance was also pretty low. This result supports the proposition that the relationship between the relative spread and the expected return could be convex for the repurchasing firms. If so, this would be due to the tax effect, proposed by Gottesman and Jacoby (2006) who modify the Amihud and Mendelson (1986) proposition that the relationship between them is concave piecewise- linear. Second, the robustness test using Heckman’s (1976) two-step estimation also confirmed the result above. The slope of the relative spread soared sharply in the same sub-range as above for the stock-repurchasing portfolios, although its statistical significance somewhat decreased overall. Therefore, we found the relationship between the relative spread and the expected return convex irrespective of the estimation methods; one method stresses the control of the endogeneity while the other emphasizes sample selection correction. Third, we also carried out a probit regression analysis to examine which of the stock’s attributes influences payout decisions. As a result, we found that the more liquid the stock is, the more likely stock repurchases are preferred over cash dividends. Further, the smaller the share of the largest shareholder is, the larger the share of foreign investors become, or the younger the age of the firm, the more likely stock repurchases are adopted as the firm’s payout policy. This conclusion was robust when i) we divided the sample into 4 groups according to the possible combinations of whether each payout policy was chosen or not; and ii) we retested the result using the multinomial logit regression model in which we controlled for the additional financial variables. Thus, we found liquidity is a critical factor in deciding payout policy, and every exogenous variable (the share of the largest stockholder, that of foreign investors, and the age of the firm) influences the choice of the payout policy. These variables were used to control for endogeneity and to correct sample selection. Existing studies thus far have focused on the overall positive relation between the relative spread and the expected return. For instance, recent studies like Park and Eom (2008) and Yun, Ku, Eom, and Hahn (2009) merely confirmed that liquidity is an additional pricing factor in explaining the excess return of the stock. This paper differs from these in that it explores the curvature as well as the direction of the coefficient of the relative spread by applying the spline regression function in examining the relationship between them, which has turned out to vary according to the payout policy, the typical financial decision making initiated by the management of the firm. Thus, we attempted to make an integrated approach that combines payout policy as a corporate finance issue with asset pricing as the essence of investments. This paper’s finding is unique in the respect that it is internationally the first confirmation of Gottesman and Jacoby (2006)’s proposition. From the results, we can also expect that firms may exert more efforts to enhance the liquidity of their stocks when they adopt stock repurchases as their payout policy. As stocks are very sensitive to liquidity change, they can improve the market value by reducing the required rate of return of their stocks. In this context our results can be extended to the study under the market microstructure framework in which we can discuss how the market mechanism should be constructed to boost the liquidity so as to help stock-repurchasing firms level up their firm value. To follow up, it will be very interesting to see whether those repurchasing firms indeed take actions to increase the liquidity of their stocks and what measures they actually use to accomplish that aim. This will require more research.

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Although initial public offerings (IPO) are one of the most important issues in corporate finance, academic research in this area has been rather minimal. The absence of academic interests can be accounted by the prevalent assumption in the market that IPO is just a standard procedure toward a firm’s growth. The view was not challenged until the early 1990s when Pagano (1993) and Zingales (1995) presented their seminal works. Then a recognition has been built that entrepreneurs actually make a conscious decision whether to go public by evaluating the benefits and costs of going public. Further, it is difficult to collect detailed information such as accounting and ownership data for private firms. For this paper, we analyze the determinants of IPOs using a large database of the private firms that meet the listing requirements of the Korea Exchange (KRX). In doing so, we basically follow the approach of Pagano et al. (1998) by comparing the ex ante and ex post characteristics of IPO firms with those of private firms. First, our main variable in the analysis is the ownership structure which differentiates the paper from the existing ones. As the prior and post IPO ownership structure would be one of the main concerns of the controlling shareholders, we conjecture that owners when designing the sale of new shares will definitely have the final ownership structure in mind. Second, this paper focuses on firms that are controlled by their founders, or the founders’ families since they are the ones who are most likely to face the tradeoff between the benefits and costs of going public. Accordingly, family firms account for 95.3% of our sample. In this study, we hypothesize that (1) the probability of an IPO increases with the ownership by the controlling family, but decreases with the ownership by member firms in a business group, and (2) this relationship is stronger for non-chaebol firms than for chaebol-affiliated firms. These hypotheses are built upon the common understanding that less diversified owners are more likely to resort to the IPO, since they have more to gain from diversifying their investments. We test the hypotheses by studying 491 non-financial firms that went public through the KOSPI market of the KRX during the period of 1987 through 2005. To investigate the determinants of Korean IPOs, the characteristics of these IPO firms are compared with those of non-IPO firms that still met the listing requirements of the KRX but chose to remain private. In addition, we investigate what types of changes resulted from going public especially in their financial characteristics and the ownership structures . We also analyze the determinants of changes in the ownership by the controlling family over the three years before and after the IPO. Our findings are summarized as follows. ∙ Ex ante determinants of an IPO: From a logit model of the probability of going public, we find that firms are more likely to go public in the following cases: if the median market- to-book ratio of listed firms in the same industry is higher; and if the ownership by the controlling family is higher while the ownership by member firms in the same group is lower. We also find that these results are stronger for non-chaebol firms than for chaebol firms. The overall results support our hypotheses that controlling shareholders decide to go public in order to diversify their own wealth and maximize the proceeds by carefully timing the IPO. ∙ Ex post consequences of an IPO: By examining the dynamics of firm characteristics before and after the IPO through a regression framework of Chemmanur et al.(2010), we find that the following firm characteristics notably decline after the IPO: profitability, sales growth, investment, leverage, the industry market-to-book ratio, family ownership, and the ownership by affiliated firms. The ex post effects of the IPO complement our results for the ex ante analysis. Subsequent to the IPO, investments in tangible assets also decrease while investments in affiliated firms’ equity increase, especially for non-chaebol firms. This result implies that the proceeds from the IPO are not used for future investments, but to diversify the business group or secure control over the group of a controlling shareholder. ∙ Determinants of the changes in ownership by the controlling family: Finally, we run each regression for the two separate periods before and after the IPO to examine the determinants of changes in the ownership by controlling families. For the periods prior to the IPO, the ownership by a controlling family is positively related to the investments in affiliated firms’ equity. After the IPO, this relationship is no longer significant, and family ownership increases with the Tobin’s Q. These results suggest that controlling shareholders maximize their private benefits by securing their control over business groups before the IPO, but pursue higher investment value after an IPO when the control issue tends to be less important.

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The intertemporal relation between risk and return has long been an important topic in asset pricing literature. Most asset pricing models postulate a positive relationship between a stock portfolio’s expected returns and risk, which is often modeled by the variance or standard deviation of the portfolio’s returns, claiming that idiosyncratic risk has no significant effect on returns. However, no agreement has been met about the existence of such a trade-off for stock market indices. While return volatility is an intuitively appealing measure of risk, the difference approaches used by previous researchers suggest that no clear consensus has emerged regarding its relevance. Yet, whether investors require a larger risk premium on average for investing in a security during times when the security is more risky remains an open question. This paper, therefore, makes a contribution by exploring the relationship between return and risk as proxied by firm-volatility, comprised of both systematic and idiosyncratic volatility. As for the predictability of stock market returns, Goyal and Santa- Clara(2003) propose a new approach to test the presence and significance of a time-series relationship between risk and return for the aggregate stock market. They find a positive relation between the equal-weighted average stock volatility and the value-weighted portfolio returns. They also show that the lagged volatility of market returns has no predictive power for the expected return on the market. Bali, et al.(2005), on the other hand, find that Goyal and Santa-Clara’s empirical results based on the equal-weighted average stock risk are not robust across different stock portfolios and sample periods. That is, their conclusions do not hold when either the more natural value-weighted measure of average stock risk or the more robust median stock volatility is used in predictive regressions. Ang, Hodrick, Xing and Zhang(2006) further suggest that volatility of market return is a priced cross-sectional risk factor based on their observation that US stocks with high lagged idiosyncratic volatility earn very low future average returns, and these assets are indeed mispriced when applying the Fama-French model. Their results of the negative relationship between idiosyncratic volatility and expected returns are surprising for two reasons. First, the difference in average returns across stocks with low and high idiosyncratic volatility is rather large. Second, their findings cannot be explained by either exposure to aggregate volatility risk or other existing asset pricing models. On the other hand, in order to capture the time-varying property of idiosyncratic risk, Fu(2009) uses the exponentially generalized autoregressive conditional heteroskedasticity (EGARCH) models and out-of-sample data to estimate expected idiosyncratic volatilities, and find that idiosyncratic risk is positively related to expected returns. Views on the relationship remain divergent: asset pricing theory implies that expected returns should be positively related to model-implied systematic volatility; various theoretical studies suggest that idiosyncratic volatility should be positively related to expected returns; and several empirical studies suggest that idiosyncratic volatility has explanatory power for the cross-section of expected returns. As such, this paper examines the explanatory power of idiosyncratic volatility estimated by three asset pricing models(CAPM, Fama-French 3 factor model, and Alternative 3 factor model suggested in Yun, et al.(2009)), and total volatility, a model-free quantity, for the cross-section of stock returns. Total volatility is the sum of systematic volatility relative to some asset pricing model and idiosyncratic volatility relative to the same model. As a result, no significant link between expected returns and idiosyncratic volatility in Korea stock market (KOSPI) data is traced while some cross-sectional evidence for a negative relationship between total volatility and expected return is detected. In addition, the portfolios of lower volatility stocks achieved a higher expected return than those of higher volatility stocks. We could ascertain that the effect is driven mainly by systematic volatility by applying AHXZ(2006)’s method. We also investigate the implications of the findings above for asset pricing and construct a total volatility factor via the factor mimicking portfolio for total volatility. Following the Fama and French(1992, 1993) model, we construct the factor mimicking portfolio as the zero cost portfolio which is long for the quintile of stock with lowest total volatility and short for the quintile with highest total volatility. We estimate the factor price of total volatility risk using the Fama and MacBeth(1973) procedure for individual stocks in our data. During the research period, the factor price of total volatility risk is positive and significant, indicating that the variation in systematic risk has notable implications for asset pricing. We also conclude based on the multi-factor models of risk that aggregate volatility should be a cross-sectional risk factor. Our finding is that the total volatility has a negative cross-sectional relationship with expected returns of individual stocks. Moreover, when we decompose the total volatility factor into systematic and idiosyncratic components, we find that the factor price of total risk is positive while that for idiosyncratic is insignificant. This negative relationship corroborates the results from the past research in option pricing that has shown a negative price of risk for systematic volatility, by reassuring that stocks with high past exposure to innovations in aggregate market volatility earn low future average returns.

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What is the economic role of the bankruptcy court(judge)? The general answer is that it serves to play key roles in valuation, distribution, and procedure. Yet, the bankruptcy courts are often considered passive and procedural participants in bankruptcy game literature. Indeed, the mainstream themes are more often focused on the optimal bankruptcy law than the court’s strategic role with primary emphasis on the workout negotiation game between the debtor firm and its creditors in the shadow of the bankruptcy law. This paper, therefore, examines the game between the bankruptcy court and the firms that file for bankruptcy protection (Chapter 11). The adopted model is a dynamic game under incomplete information. The perfect Bayesian equilibrium concept is used to refine the resulting equilibriums. By doing so, we construct that the player’s movement is determined according to the sequential rationality and the Bayesian consistency, thereby disallowing empty threats in the process. In this paper, for simplicity, the creditors are assumed to be made of only one class of passive participants; when the firm is liquidated, they receive the proceeds first, and when the firm is reorganized, they are given new equity. The debtor firm chooses between self-liquidation and filing for bankruptcy protection. The self-liquidation leaves something for the debtor firms, but the ex-post liquidation leaves nothing because of bankruptcy costs which reduce the liquidation value. The bankruptcy court maximizes the social welfare which is the sum of the debtor firm’s and the group of creditors’ gains. The court is assumed to have the authority to set the recovery ratio and to reject the petition. Here, the recovery ratio means the ratio between the original debt amount and the value of new equity that is paid to the creditors when the firm is reorganized. In the case of rejection, the firms are assumed to be liquidated(Chapter 7). The judicial intervention or discretion means the strategic decision of the court in the corporate bankruptcy game. There are two types of firms: good firms and bad firms. Good firms’ going concern value is higher than the liquidation value; vice versa for bad firms. The proportion of the two types of firms is determined by nature. The firms know their own type but that information is not verifiable to a the third party. The court only knows the ex-ante probability distribution of the firm types. Therefore, there is a possibility that the two types are pooled, and the court cannot distinguish between them, which leads to the pooling equilibrium. Sometimes, however, the bankruptcy court has strategic measures to prevent the bad firms from filing for bankruptcy protection, which leads to the separated equilibrium. Based on the recovery ratio set by the bankruptcy court, which subsequently becomes common knowledge, the bankrupt firms decide whether to file for bankruptcy protection. Sometimes, the firm type can be publicly revealed as a good or bad one before the court decision is made. In that case, generally good firms are reorganized and bad ones are liquidated. The court can also decide whether to reorganize the firm or reject the petition. If rejected, the firm is liquidated, and the proceeds are paid to the creditors. Because of the bankruptcy costs, the ex-post liquidation leaves nothing for the debtor firms. Reorganization means the debt-equity swap, i.e., the new equity claim, claim is given to the creditors according to the preset recovery ratio. Using the above game structure, this paper provides the following implications. First, the bigger the difference between the expected going-concern value and the liquidation value, the more important the strategic role of bankruptcy court becomes. On the contrary, when the expected going concern value and the liquidation value are the same (or similar), the strategic role of the bankruptcy court does not make any difference. In that case, it does not matter whether the firm is reorganized or liquidated. Second, when the going-concern value is higher, the court decision should be made favorable to the reorganization. This policy implication is especially important when systemic bankruptcy occurs. In that case, many good firms could go bankrupt due to the externality of macroeconomic shocks. Third, when the liquidation value is higher, the court should set the recovery ratio higher and take more selective approach when reviewing the petitions. These measures could help discern the opportunistic behaviors of bad firms. Fourth, when the bankruptcy law is pro-debtor, the strategic role of bankruptcy court gains more importance. In this paper, we can interpret the lower recovery ratio as the proxy for the pro-debtor law. When the recovery ratio is deemed low, the court should reject the petition more often than when the ratio is high. Fifth, the better the court’s information capability is, the higher the social welfare becomes. This result suggests that the court and judges should improve their expertise. This also implies that any legal uncertainties can produce significant impacts on the overall process of corporate bankruptcy.

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This paper reviews 30 years of empirical research on asset pricing models in the Korean stock markets. The validity of the Capital Asset Pricing Model (CAPM) has been seriously challenged in Korea as in the other countries. The overall empirical results in Korea show, as they do in other countries, that the static CAPM fails to explain for stock returns in Korea. Contrary to the prediction of the CAPM, firm characteristic variables such as firm size, book-to-market, and earnings-to-price ratio have significant explanatory power for average stock returns in the Korean stock markets. Because of these CAPM-anomalous phenomena, various asset pricing models such as the types of Arbitrage Pricing Theory (APT), the Consumption-based Capital Asset Pricing Model (C-CAPM), and the types of the Intertemporal Capital Asset Pricing Model (I-CAPM) have been introduced and tested in the literature. The Fama and French(1993) three-factor model is arguably acceptable in explaining Korean stock returns. This paper also provides some explanations of various testing methodologies used in the literature for asset pricing models and discusses the related econometric issues.

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This paper reviews major studies accumulated over the last two decades in finance literature on the impacts and roles of foreign portfolio investors in emerging markets, and more specifically, reviews the studies on Korea in detail. The Korean economy successfully overcame two financial crises in 1997 and 2008, and stands out as the 15th largest economy in the world based on GDP in 2009, with foreign equity ownership composing about 40% of total market capitalization. Such growth of the Korean economy could be partly due to the benefits of capital market liberalization policies conducted since 1992. In fact, the literature provides generally positive evidence of the benefits gained after liberalization through a reduction in the cost of capital, increased economic growth, and better corporate governance; however, it provides very little consensus on the destabilizing effect of foreign capital flows. In reality, Korea experienced a severe credit crunch until early 2009 due to massive capital outflows during the global financial crisis, despite the Korean economy’s sound corporate performance and ample foreign currency reserves. Hot money flowing into the Korean bond and stock markets reached 40 trillion won by the end of 2010, which require Korea to take steps to control a potential sudden outflow of these funds and further capital in flows. This aspect of foreign capital flows is potentially damaging for emerging markets and may substantially weaken the benefits of opening capital markets. Regarding the issue of the information advantage between domestic vs. foreign investors, the empirical evidence in the literature is mixed and varies across studies, depending on the specific markets or countries examined and the specific methods or horizons employed for the comparison of investment performances across different types of investors. More comprehensive analysis in this area would be desirable.

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This study surveys research into mutual funds, with special emphasis placed on the implications for Korean markets. Mutual fund studies, here in this study, are divided into three important categories: The economics of mutual funds, agency problems, and other issues. The category of the economics of mutual funds is again divided into 7 sub-categories, the category of agency problem sinto 5 sub-categories, and the category of other issues into 8 sub-categories. For each category, we review the overall trend of overseas mutual fund studies from the 1960s through 2010. After that, the period spanning 1991 through 2010 is focused primarily on Korea. The number of mutual fund articles in academic journals has increased at a surprising rate since the 1990s. In this review, we propose possible directions for future studies with special emphasis on both the protection of investors and the investment behavior of investors. We are confident that careful studies will prove quite helpful in resolving a variety of agency problems in Korean fund markets, and should also help provide investors with efficient investment opportunities in a fair manner. We also hope that mutual fund studies will ultimately bridge the gap between academia and the practical society of mutual funds.

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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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