Artificial neural networks (ANNs) with the logistic transforms are popular methods to increase the accuracy of performance forecasting due to their functional flexibility. In this paper, we estimate the accuracy of the ANNs models by conducting a data-driven search for optimal specifications. Our tests on foreign exchange rate forecast for the Korean won/US dollar show that the ANNs are superior to linear models. The superiority of the ANNs, however, does not hold for the Japanese yen/US dollar exchange rates. We use the success ratio (SR) as the out-of-sample forecasting performance evaluation. The directional accuracy (DA) test and the forecast comparison statistics of Diebold and Mariano (DM) are applied to assess the relative forecast performance of the ANNs as well. For the Korean won spot rate, it seems that there is much to be gained by using the ANNs for predicting the direction of change. The DA test results also show that the SR from the ANNs is generally greater than that from the AR models. For the Japanese yen, the ANNs achieve a lower SR in most cases. The balance between the in-sample fit and the out-of-sample forecast performance is well achieved for the Korean won exchange rate, but not for the Japanese yen exchange rate. This study is significant in that no previous works that evaluated the accuracy of exchange rate forecasts have applied a variety of tests in order to ascertain whether the ANNs of out-of-sample forecast performance actually achieve directional accuracy as economic criteria.

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This paper analyzes the liquidity component of corporate bond spreads using a new illiquidity measure for corporate bonds in Korean bond market. We perform the empirical study during 2005~2012, which spans before and after global economic crisis exacerbated by the collapse of Lehman Brothers. At first, we estimated directly liquidity measure λ with four liquidity variables: Amihud measures of price impact, turnover, zero trading days, and the variability. Next, we regressed corporate bond spreads on λ after controlling for another explanatory variables within each rating before and after global economic crisis period. Lastly, we calculated the size of liquidity component to look directly at the impact of corporate bond illiquidity on corporate bond spreads. Through this study of liquidity component, we could compare the size of liquidity premium on corporate bond spreads within each rating, and maturity before and after global economic crisis period. As results, before andafter the global economic crisis period, the effect of illiquidity on spreads was positive and statistically significant for AA and A-rated bonds meanwhile only for AA-rated bonds during the period. The size of liquidity component has become bigger since the global economic crisis period and was peaked at A-rated bonds with 2- to 5-year maturities. Those results shows that the liquidity component is comprised of important parts of issuing price of A-rated bonds whose maturities at the time of issuance are mostly 3 to 5 years.

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By the name of financial innovations, a large number of new financial products related to derivatives have been introduced into the global financial market for the last few decades. The Korean financial market was not an exception to this development. Among new financial products in Korea, the Equity-Linked Securities (hereafter ELS) may be considered one of the most successful products, judging from its market size. Since it was first introduced in 2002, the ELS have been very popular to individual investors who were cautious of downside risk of their investments. The ELS provided them with new tools to manage their future wealth. Therefore, the ELS can be thought as a good example of financial innovations in the Korean financial market. It is broadly accepted that financial innovations are originated by market imperfections, whereas there have been two competing theories about what drives financial institutions to invent new products. Because, unlike innovations in other industries, new products in financial industry are not protected by the patent law and should be disclosed publicly, financial innovations may have some different features from those in other industries. For instance, one could argue that that the benefit to financial innovator is not an excess profit. Bhattacharyya and Nanda (2000) assumed that the imitation occurred immediately in the financial market, so they suggested that an innovator made an effort to increase the market share rather than to take excess profits. Herrera and Schroth (2003) also agreed that financial innovators could notmake more profits than imitators could. Moreover, they thought that the information about potential clients was the main source for innovators to be able to increase their market shares. These theories were supported by the empirical research of Tufano (1989). He tested this hypothesis with data related to corporate securities and MBS (Mortgage-Backed Securities) and found that financial innovators could not impose higher margin, while they could extend their market shares. In contrast, Van Horne (1985) argued that financial innovators could take profits before imitators appeared even though there was no legal protection in the financial market. His theory was based on the traditional monopoly theory and it was empirically supported by Carrow (1999) and Schroth (2002). Carrow (1999) found that innovator’s profit decreased as more rivals came into the market and Schroth (2002) reported that the source of innovator’s excess margin was the superior knowledge about a new product. Using 4,521 issuance data during the early stage of ELS market in Korea, this paper empirically examines whether first movers, or innovators, earn more profits than imitators do. We also test whether the profit of innovators declines as the time passes by. As a proxy for profit, we estimate the total margin of ELS, the difference between the actual issue price and the theoretical price of ELS divided by the actual issue price. This measure represents the proportion of issuer’s margin to the total price of ELS and it gives us the information about how much innovators charge on different products. In creating new products, the characteristics of embedded option in ELS are at the issuer’s discretion and the issuer’s profit is mainly determined by how the embedded option component is valued. Thus, for the robustness of our empirical results, we also estimate the margin of embedded option in ELS, the difference of the value of the embedded option in ELS and its theoretical value divided by the value of embedded option. Then we perform regression analysis with the total margin or the option margin as a dependent variable. To control the effects of hedging costs, we also use the product type, the number of underlying asset type, the maturity, and the embedded option type, and issue type (private/public issue) for controlling variables. The empirical results show that innovators in the ELS market could earn more margin than imitators do. These results are inconsistent with the theory of Bhattacharyya and Nanda (2000). However, margins decline as the market becomes more competitive. The results also show that the large sized financial institutions innovate more frequently and earn higher margins than lower sized firms do. Our empirical results have important implications for regulatory policy regarding entry barrier. To issue the ELS in the Korean market, securities firms should get permission from the regulatory authority. Therefore, in the Korean ELS market, innovators protected by the regulatory barrier could have taken excess profits, despite of the fact that some competitors exist in the market. Moreover, they can maintain their margin policies after competitors come in. The regulation of Korean ELS market was aimed to protect investors from issuers’ insolvency. However, it resulted in protecting first-movers from followers as well. As a consequence, innovators in the ELS market become superior to imitators, which prevent a fair competition. In the future, the regulation authority should consider both the investor protection and the market competition.

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To better understand the nature of family-owned firms, one must distinguish management from control rights (Villalonga and Amit, 2006). Also not all controlling sh-areholders in family firms serve as CEOs. When professional managers serve as CEOs of family firms, the controlling shareholders often assume the role of monitoring the hired managers. Therefore, these firms end up bearing some agency costs that incur between the owner and professional managers. While the owner-manager conflict can be mitigated in firms in which family members serve as CEOs (henceforth, ‘family CEO’), the agency problem between controlling shareholders and minority shareholders can be also intensified (Shleifer and Vishny, 1997). Taken all factors into consideration, family CEOs can affect firm performance in both positive and negative ways. By definition, controlling shareholders of any business groups face the dilemma whether to get involved in the firm management. And yet, not much research has been conducted on this issue as to address the question which is better for the firm. This must have been so perhaps because of data limitations. In fact, Lin and Hu (2007) is the only study that directly addresses the selection issue. However, their sample is limited to listed Taiwanese firms, not sufficient to account for general characteristics of business groups including unlisted firms. To the best of my knowledge, this paper is the first study of its kind to analyze the determinants of family CEO using information of all affiliatesboth listed and unlisted- belonging to the same business groups. When a family keeps control of a firm, its controlling shareholders can get involved in the management as CEOs or the like to maximize the sum of the value of the retained block and the private benefits obtained (Burkart, Panunzi, and Shleifer, 2003). If maximizing the former is intended, family CEO can positively affect firm performance as long as he/she has good management skills. But if maximizing the latter is intended, family CEO can be negatively related to firm performance. Stein (1989) and James (1999) develop a model illustrating the positive effect of long-term investors on firms’ investment efficiency especially when they are the members of the family that owns the firm. The study explains that such long-term investors can minimize myopic investment decisions by managers. Anderson and Reeb (2003) empirically find that firms with family CEOs outperform those with professional CEOs for this reason. On the other hand, controlling shareholders of family firms don’t tend to take enough advantage of competitive managerial labor market since they are likely to limit management control to their own family circles. Such practice of ‘nepotism’ can harm firm performance (Perez-Gonzalez, 2006). As such, existing theoretical and empirical studies about the effect of family CEO on firm performance are contradictory. To draw its own conclusion, this paper first investigates the precise determinants of family CEO before probing the question of family CEO’s effect on firm performance. Finally to reflect the endogenous nature inherent in family CEOs, the self-selection or reverse causality issue is addressed through modeling family CEO as an endogenous choice. Using the Korean business group data from 2001 through 2011, the following results are found. First, firms with higher cash flow rights of controlling shareholders and larger equity portion in affiliates are more likely to have family CEOs. This means that controlling shareholders tend to serve as CEOs to maximize their control rights over the business group as well as the value of their stake, supporting a proposition of Burkart et al. (2003). Second, family CEO negatively affects firm profitability measured by EBITDA. This implies that when controlling shareholders serve as CEOs, agency costs between themselves and minority shareholders increase. Also, only for firms with non-family CEOs, their investments have a significantly positive impact on EBITDA, indicating that professional CEOs commit more to efficient investments than family CEOs do. Third, for firms with family CEOs, higher cash flow rights and larger equity portion in affiliates are associated with lower firm values measured by Tobin’s q. This implies that the concentration of ownership and management by controlling shareholders induces agency problems due to the entrenchment effect, making them commit to maximizing control rights over the business group although the value of their shares is damaged. On the other side, for non-family CEO, larger equity portion in affiliates is associated with higher firm value, implying that professional CEOs invest more efficiently in affiliates’ equity than family CEOs do. But the effect of cash flow rights on firm values is insignificant for these firms. Just like the results on EBITDA, investments have a significantly positive impact on firm values only for the sample with non-family CEO. Fourth, controlling the endogeneity of family CEO through Heckman (1979)’s model, family CEO still negatively affects value as well as profitability of firm. Fifth, through a robustness check we found that firm profitability worsens only when family CEO runs the firm; if professional managers are CEOs and family members are not involved in the management position, those firms show higher value. This finding suggests that securing an independent professional management system without family members can be the most effective way to maximize corporate value in the business group. Overall, the findings indicate that when controlling shareholders with potentially powerful influence over the business group directly manages the firm, they are highly like to be driven by the self-serving incentive to maximize their controlling rights over the business group, rather than to commit themselves to increasing firm value through efficient investments. By drawing this conclusion, this study sheds more light on this unexplored yet salient question of which organizational structure, with or without family CEOs, is more efficient.

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In financial economics, it is assumed that individual and institutional investors behave differently in the market. While institutions are viewed as informed traders, individuals are considered as noise traders with psychological bias as in Kyle (1985) and Black (1986). In particular, Choe et al. (1999) and Kaniel et al. (2008) examine the difference of individual investor trading in stock markets and its impact on the dynamics of stock prices. Based on these works, this paper aims to show how individual investors affect volatilities as well as stock returns, and whether individuals are uninformed traders of volatility trading. Our study, however, differs from the previous studies in that we focus on options markets instead of stock markets. There are two reasons that we examine the behavior of individual investors in options market other than in the stock market. First, according to the previous studies individual investors’ behavior in options markets is inconsistent with their behavior in stock markets. Individual traders heavily depend on the changes of past prices and prefer out-of-the money options that have a severe leverage effect, which is significantly different from institutional and foreign investors. These unique characteristics of individual investors in options markets have made us interested in looking into the relationship between individual investors and options markets. Second, the structure of options markets is, in nature, optimal for analyzing the effect of each type of investors. When studying its impact using stock returns, we have to pay much attention in order to adjust for the effects by various factors such as dividends and stock-splits. However, we an easily adjust the effect of underlying asset returns on option returns using the series of options with different strike prices and different maturities, thereby simplifying our research design. As well-known, volatility is the measure of the price level which is adjusted for the effect of underlying asset. In short, if stock trading is based on the prospect about the future direction of underlying asset prices, option trading is based on that about the future direction of volatility. Therefore, it is called volatility trading. Although this paper investigates the behavior of individual investors in stock markets based on the idea of Kaniel et al. (2008), it differs from the study. While it solely focuses on the role of individual investors as liquidity providers in stock markets, our paper deals with the change of volatility by the behavior of individuals in the options market. Thus the aim of this paper is to see whether their interpretation holds valid in the volatility trading in the options market. In this paper, we analyze the autocorrelation between implied volatilities, including implied volatility of at-the-money options, and VKOSPI 200 index which results from calculating one-month model-free implied volatility using out-of-the-money KOSPI 200 index options. In addition, we examine whether volatility changes can be explained by the intensity of the buying/selling of individual investors using regression analysis, even after adjusting for the mean reverting of implied volatilities. For our second study, we sort data into ten decile groups according to the intensity of the buying/selling of individuals as a proxy for trading imbalances. Decile 1 is the most intense selling period and decile 10 is the most intense buying period. Then we examine buying/ selling imbalances and trading patterns of individuals in terms of the trend in simultaneous and cumulative volatility changes of deciles 1 and 2 and deciles 9 and 10, prior to, current, and after trading week separately, and calculate t-statistics of cumulative volatility changes for testing significance. The main results of this paper can be summarized as follows. First, we find that implied volatility is mean-reverted and that as the intense buying by individuals increases, so do current and future implied volatilities. Second, the imbalance of volatility between intense buying and selling is analyzed for each decile. According to the results, volatility significantly increases when individuals become only intensely buying options, which is likely to be consistent with the fact that individuals are net buyers in options markets. Finally, we investigate volatility change prior to, current, and after trading week and recognize that individuals are volatility-momentum traders who tend to buy options after volatility increases. Also the results of the robustness test indicate that the effect of individual investors on volatility is still significant after controlling for the total volume of options and the realized volatilities of underlying assets. Therefore, we can conclude that the information contained in the intensity of individual buying and selling is independent of information contained in the total volume and realized volatility.

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The globalization and integration of financial markets across border is an inevitable phenomenon, in line with which even emerging economies including Korea have opened their financial markets to international investors. With increasing globalization in capital markets, the cross border capital flow has become an important issue because it is directly related to vulnerability of small and open economies. In the past decades, the international financial economics literatures examine the effect in relation of the return of price and volatility transmission between stock markets (Hamao et al., 1990, Karolyi, 1995; Ng, 2000; Singh et al., 2010) or between index or commodity futures markets (Roope and Zurburegg, 2002; Xu and Fund, 2005; Liu and An, 2011). Although some studies examine the relation in currency markets, their focus is limited to price return and volatility transmission between major currencies such as Japanese Yen, Deutsch Mark, and British Pounds (Baillie and Bollerslev, 1991; Hong, 2001) or between European currencies (Baele, 2005; Bubák et al., 2011). No study so far has examined those between the currencies in the Asian region, so this paper is in fact the first of its kind to do so. As such, the purpose of this paper is to examine the dynamics of price discovery and volatility transmission between Korean Won (KRW), Chinese Yuan (CNY), and Japanese Yen (JPY). We use the US dollar, which has been used for payment and settlement in international trades, as the numeraire for evaluating the three currencies and gold. Historically, Japan has been the most influential economy for Korea next to the US. Korea and Japan have similar economic structure and geographical proximity to each other. Meanwhile, China’s economy has grown rapidly since 1990’s and has become the second largest economy in term of GDP in the world. Accordingly, its economic influence on Korea has also rapidly grown, and since 2006 it has been Korea’s biggest trade partner, replacing Japan. Hence, we conjecture that some power shift must take place from Japanese yen to Chinese yuan in terms of these currencies’ influence on Korean won. Subsequently, we conduct studies to understand how the three currencies are interrelated in term of the price discovery and volatility transmission. Our study period is from Aug. 1, 2005 to Nov. 7, 2012 since China was under the fixed exchange rate regime before Aug. 1, 2005. We also remove the period from Jul. 1, 2008 to May 31, 2010 from the above because China temporally enforced the fixed rate system during this global financial crisis (hereafter GFC) period. As a consequence, our sample period is divided into two sub-sample periods. The first one is from Aug. 1, 2005 to Jun. 30, 2008, which is before the GFC period. The other one is from Jun. 1, 2010 to Nov. 7, 2012, which is after the GFC period. To investigate the price discovery, we employ Hasbrock’s (1995) information share measurement method. Our findings are follows: Before the GFC, the contribution of JPY for the price discovery of KRW is rather high while the contribution of CNY for the discovery of KRW is low. However, after the GFC, the price discovery contribution of CNY on KRW becomes quite significant whereas that of JPY diminish. To identify the volatility transmission, we use a multivariate volatility model, BEKK. However, since we should analyze four variables, we decide to employ the rotated multivariate GARCH model (hereafter MRARCH) of Noureldin et al. (2012) for numerical stability. Using this model, we find that there is no significant volatility transmission between JPY, CNY, and KRW before the GFC. However, the influence of CNY towards KRW and JPY in volatility transmission becomes apparent after the GFC. We suggest that increased role of CNY in volatility dynamics for Korea is caused both by the increase in the trade volume between China and Korea and by the rise of China’s economic status in the world market. Although we can not get some strong evidences in terms of statistical significances, our empirical results support that there is a relative influence power shift from JPY to CNY before and after the GFC. This is the first systematic empirical work to find the linkage between the major currencies in Asia region. We hope that this study trigger further research on the multivariate currencies dynamics in the region.

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This paper develops a new credit risk model for small and medium-sized enterprises (SMEs) based on the DSW model of stochastic default intensity and the dynamics of underlying time-varying covariates. In particular, our model incorporates the default probability with the probability of initial public offerings (IPOs) in the framework of a censored stopping-time model. Default stopping time comprises of such variables as total borrowings/total assets in the stability, ROA in the profitability, account payable/sales in the activity, and financial expenses/total cost in the etc. As for the IPO stopping time, the natural log of total assets in the stability, net income/net sales in the profitability, and cash flows from operating activities/ net sales in the etc. are significant for the IPO stopping time. It is found that our model based on DSW model outperforms the multi-period logit model consistently and robustiously according to various prediction horizons and lag orders of VAR for macro-variates because the continuous stopping-time framework emphasizing on the stochastic default intensity accurately calculates the default probability superior to the discrete-time model equivalently computing the survival and default probability. In addition, it captures countercyclically monthly-frequency movement of capital requirements in compliance with the new Basel Accord. The implication is that our model as the early warning system may help the financial supervisory authority to predict the expected loss due to the sudden collapse of economic fundamentals such as rapid transfer of debtors' credit risks.

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Household debts have become an increasingly influential factor in holding financial assets (Cocco, 2005; Yao and Zhang, 2005; Chetty and Szeidl, 2009; Becker and Shabani, 2010). This paper therefore investigates the impact households’ debts have on their holding status of various financial instruments by examining the data of 10,000 households from the 2011 and 2012 Household Financial Survey conducted by Statistics Korea. In exploring the relations between household debts and household financial asset holdings, this study specifically addresses two issues. One is about the extent to which household debts across household income classes have an impact on the shareholdings of each financial instrument. The other is about the sway of household debts on the choices of three financial instruments at the moment households make asset allocation decisions. Some evidences are found on the relation of households’debt and financial asset holdings. First, while financial asset holdings as well as household debts increase in proportion to a certain age up to 60, they drop sharply afterwards. The ratio of financial asset over total asset exhibits a U-shaped distribution. This result can be explained by the fact that Korean households in general have strong tendency to demand real estate relative to financial assets, and this preference is more pronounced as age increases. In addition, both financial asset holdings and household debts increase proportionally to the education level of households, while the ratio of financial asset or financial debts over total asset shows a moderately inverted U-shaped pattern. These results seem to imply that the better educated and the older households, the more capable they become in employing debt instruments either in financial or real assets as tools to accumulate wealth. To explore the relation of household debt and financial asset holdings, dependent variables such as fin, risky assets, and cash are normalized by dividing financial wealth, risky assets, and cash by total assets. With the scaling of dependent variable being equal to or greater than zero, Tobit regressions are conducted while, for the purposes of model setting, controlling for either one or combination of categories of different levels of education, industries, and occupations. Besides, to control for the endogeneity of household debts with financial asset holdings, I use the predicted household debt ratio as an instrument variable estimator obtained from running 2SLS. The second finding is that the impact of household debt ratio on financial wealth holdings is plainly pronounced among household income classes based on the analysis of the samples of 2010 in quintiles, although the household debt ratio in the whole sample negatively dominates the holdings of three financial instruments. In particular, the household debt ratio negatively affects the holdings of financial wealth in middle income class, whereas it positively does in high income class. This result indicates that the debt ratio of high income households plays a complementary role to financial wealth holdings, but, in contrary, the debt ratio of the middle income households substitutes financial asset holdings. Further, this finding implies that high income households take advantage of debt to accumulate wealth by investing in both financial assets (Pollin, 1988, 1990) and real estate, while middle income households do not hold both together, probably owing to credit constraint. However, high income households owning real estates are more inclined to reduce the holdings of both risky assets and cash holdings. Third finding is about asset allocation across household income classes. The financial debts in middle income households shrink the holdings of financial wealth, risky assets, and cash, whereas the disposable income in middle income class raises the holdings of the three major financial vehicles. But the financial debts in high income class increase the financial wealth, but reduce the cash holdings. Additionally, when the sample is restricted to households with debts, then financial debts reduce both financial wealth and risky assets, but raise the level of cash holdings. Taken together, these results generate two possible interpretations: the extent of the impact of financial debts over asset allocation varies depending on either household income classes or the levels of household debts. As a robustness check, I carry out the Tobit models using the 2011 sample. Unfortunately, the effect of household debts on financial wealth for the high income class only is consistent with the result in the prior year sample. This research is restricted to the two survey period samples and there are, therefore, limitations to fully take in the features of households behaviors on asset holdings and asset allocation in relation to household characteristics over time. I have a good guess about the asset holdings and choices by households in 2010 and 2011, which were unduly influenced by the 2008 Subprime Mortgage disaster. One of future research is possibly the comparison with changes in households asset holdings in terms of household debts and income before and after 2008 financial crisis.

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To examine the common assumption that the monetary fundamentals are stationary, we test the monetary model of exchange rate determination. In specific, we test whether nominal exchange rates are cointegrated with the monetary fundamentals, using data spanning from January 1971 to March 2011. The results show that the Phillips and Ouliaris test fails to reject the null of no cointegration while we reject the null hypothesis of no cointegration with Johansen’s trace test. We also explore the out-of-sample forecasting performance of the long-horizon regression of exchange rate returns on the deviation of the log exchange rate from the monetary fundamentals. For the sample of data, the DOLS estimation does not yield cointegrating coefficient estimates that accord with the theoretical values implied by the monetary model of exchange rate determination. This may bring about critical results asserting that there is no evidence of exchange rate predictability based on the monetary fundamentals in the sample. Despite the use of long span data, no evidence is found in favor of the monetary exchange rate model using the Johansen procedures. We compare the out-of-sample forecasting performance of the monetary model and confirm that forecasting power of the monetary model is insignificant.

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Up to now, major Korean data vendors have provided financial researchers with partially adjusted stock price data. As a result, holding period returns and the number of shares outstanding are sometimes inaccurate. This is a serious problem since stock price data are the most important ingredient for financial studies. To remedy this problem, benchmarking the methodologies used in the Center for Research in Security Prices (CRSP), we construct the Korean stock price data (1999. 12~2011. 09) which fully reflect corporate actions. We then investigate how security prices affect empirical studies in financial economics, with a particular focus on the effect of cash dividends. To begin with, we compute holding period returns and the number of shares outstanding by taking into account the effect of any corporate action. Though our approach is based on the methodology of the CRSP, it is modified to reflect the Korean stock market practices. By crosschecking several corporate event data sources, we build fully adjusted stock price data. The construction procedures are as follows. First, we categorize corporate events into nine large groups: Cash dividends, liquidations and transfers of exchange, mergers and splits, paid-in capital increases, capital increases without consideration and stock dividends, capital decreases and retirements of shares, stock splits and reverse stock splits, stock conversions and stock options, and other outstanding share changes. The nine large groups are subdivided into the smaller groups. Second, we examine all corporate events during our sample period. Since all corporate events except cash dividends, and liquidations and transfers of exchange entail the change of outstanding shares, we can inversely trace the corresponding corporate event when changes in outstanding shares are discovered. Although there are a few corporate actions in which outstanding shares are unchanged, those actions can be checked by the Korea exchange (KRX) corporate action data. Examples include stock split after reduction of capital stock without any refund. Third, we investigate the corresponding effective-dates of all the corporate events. Generally, there are two-or three-week gaps between the dates in which outstanding shares actually changed and the corresponding effective-dates, and this time disparity stems from related administration processes. Yet, these time gaps cause some erratic results because investors recognize that corporate events take place at the effective date but the changes of outstanding shares happen a few weeks later. Due to this time gap, firm sizes can be miscalculated. Accordingly, we revise the stock price data so that the changes of outstanding shares occur at the corresponding effective-dates and thus the gaps are removed. Basically, we check the effective-dates in Data Analysis of the Retrieval and Transfer System (DART) of Financial Supervisory Service (FSS). Also, the excess of daily limit of price variation is helpful in detecting the effective-dates because the excess indicates that there is a corporate event such as stock split and capital reduction. Fourth, we calculate corresponding holding period returns at the effective-dates. For each event, the cash dividend amount and price adjust factor are figured out. Using the values, we calculate the accurate holding period returns at each effective-date through a simple equation. Then, we finally obtain the fully adjusted stock price data. With the accurately constructed stock price data, we study how our construction of security prices affects empirical studies in financial economics. To this end, we need a proxy for the risk-free rate. In this study, we use one month spot rate of a monetary stabilization bond as a proxy for the risk-free rate. Certificate of Depository (CD) rate, the prevailing alternative of risk-free rate in Korean financial market research, bears the default risk of banks as they are the issuers of CDs. Thus, CD rate has a serious flaw to be an alternative of risk-free rate. In contrast, monetary stabilization bonds issued by the Bank of Korea do not have default risk. Therefore, we adopt one month spot rate of the monetary stabilization bond from Korea Asset Pricing (KAP) as an alternative of risk-free rate. We then concentrate on the effect of cash dividends because researchers often overlook the effect they bring on the overall outcome when they conduct research. Instead, they usually use value-weighted index of the KOSPI and KOSDAQ as market portfolio. However, since these indices do not contain cash dividend returns, considerable biases can result from relying only them. This paper, therefore, points out that such biases indeed exist and how significant those biases are. The central empirical findings are as follows: First, while the average market excess return which reflects all corporate actions is 0.97% per month, the average market excess return which does not include cash dividends is 0.82% per month. Second, the annual CAPM alphas with security prices reflecting all corporate actions are 1.70%~1.85% lower than the ones that exclude cash dividends during our sample period. Finally, the estimated annual abnormal returns of equity funds are 1.32%~1.80% lower than the abnormal returns estimated with factors that do not include cash dividends. In sum, when the security prices that exclude the cash dividends are used in empirical studies, we find that holding period returns are underestimated, and, consequently, abnormal returns are overestimated.

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