No abstract

No abstract

This paper represents an attempt at empirically assessing the applicability of the Fama and French five-factor model in explaining the cross-sectional variation of stock returns for the South Korean market. The Fama and French (2015) five-factor model is an augmentation of the existing and widely recognized Fama and French (1993) three-factor asset pricing model that incorporates two additional factors, namely the profitability and investment factors. Although the three-factor model has been shown to explain the cross-section of stock return for the U.S. and other developed countries reasonably well, it has not had much success in explaining the cross-section of stock returns for the Korean market. Many researchers have since sought to identify alternative asset pricing models that could serve as the benchmark empirical asset pricing model that would be more applicable for Korea. Along the same lines, the analysis conducted in this paper hopes to test if the revised five-factor model that incorporates the profitability and investment factors is able to alleviate some of the issues the three-factor model has had in explaining the cross-section of stock returns for Korea. Monthly returns on common stocks of non-financial firms listed on the Korea Composite Stock Price Index (KOSPI) as well as the relevant accounting information were obtained for the 1992~2013 period. This data was used to obtain the Size (market capitalization), B/M (book-to-market), OP (operating profitability), and Inv (investment) variables, which are subsequently used to obtain the Size-B/M, Size-OP, and Size-Inv portfolios. In order to investigate the Size-B/M, Size-OP, and Size-Inv effects, we construct portfolios by independently sorting firms into four groups for each of the two variables under observation (three 4x4 independently sorted factor portfolios), similar to the way in which Fama and French (1993) constructed their Size-B/M portfolios. Following the methodology outlined in Fama and French (2015), the Size-B/M, Size-OP and Size-Inv patterns in average returns were first examined in order to determine if the size, value, profitability and investment effects can be explained. The average excess returns for portfolios formed on Size-B/M, Size-OP, and Size-Inv displayed patterns that we expected them to have, whereby average excess return decreases with Size and investment but increases with B/M and profitability. These results showed that the spread in average excess returns for our sample of Korean stock returns exhibits patterns that are in line with the five factors used in the model. In order to estimate the magnitude of the risk premium associated with the size, value, profitability and investment effects, factor mimicking portfolios designed to capture the impact of the various effects were constructed, similar to the methodology used by Fama and French (1993, and 2015). The five constructed mimicking portfolios consists of the MKT, SMB, HML, RMW, and CMA factors whereby MKT represents the market risk premium factor, SMB represents the size factor (Small-Minus-Big), HML represents the value factor (High-Minus-Low), RMW represents the profitability factor (Robust- Minus-Weak), and CMA represents the investment factor (Conservative-Minus-Aggressive). Using these factors, cross-sectional regressions based on the Fama and MacBeth methodology (1973) were conducted on the Size-B/M, Size-OP and Size-Inv value-weighted portfolios in order to determine model performance by looking at the intercepts and relevant slopes for the three (MKT, SMB, and HML) or five factors (MKT, SMB, HML, RMW, and CMA) depending on the model used.

The traditional view that firms have target leverage ratios has been challenged given that a firm’s leverage ratio could mechanically mean revert whether or not a target leverage level actually exists. Evidence of leverage ratio mechanical mean reversion for U.S. firms has been well documented by Chang and Dasgupta (2009). A replication of the analysis using data on South Korean firms highlight the potential that the mechanical mean reversion of the leverage ratio also exists for South Korean firms, challenging the interpretation of prior research that infers target behavior of firms based on tests using target adjustment models. Although one might be tempted to deduce that South Korean firms follow target behavior based on the fact that the mean reversion parameter obtained from the regression analysis yields statistically significant parameter values, our analysis shows that similar statistically significant values for the mean reversion parameter can also be obtained when simulation samples with non-target random financing is used. The stock and financial accounting data for South Korean firms was obtained from FnGuide’s Data Guide database for all firms listed on the Korea Composite Stock Price Index (KOSPI) and the Korean Securities Dealers Automated Quotations (KOSDAQ) over a period of 16 years starting from 2000 to 2015. All values were converted into 2010 constant values in order to eliminate the effects of inflation with industry effects being controlled for within the regression analysis using the KSIC (Korea Standard Industrial Classification) codes at the twenty-one single alphabet level. Following the exclusion of non-financial firms, as well as firms with missing book value of assets, an additional requirement that firms have at least five years of continuous and non-missing accounting and stock price information for inclusion was imposed. This particular requirement was imposed to ensure that the leverage ratios in the simulation samples are given an acceptable length of time to evolve differently from the actual leverage ratio when random financing is assumed. Finally, firm-year observations with negative or greater than one book leverage or that have incomplete data were dropped to produce a final unbalanced panel data set that has 20,102 firm-year observations for 1,689 firms. Using the obtained panel data, three different simulation samples were generated by assuming different financing behavior and using data from the actual sample. The first simulation sample, denoted by S(p= 0.5, actual deficit), assumes an equal probability of debt issuance and repurchase, that is p is assumed to be 0.50. The second simulation sample obtains p using the actual financing deficit and newly retained earnings in the actual data and is denoted by S(p=empirical frequency, actual deficit). The third simulation sample, denoted by S(p=0.5, random deficit), was generated to remove any potential effects of endogeneity in the actual financing deficit as endogeneity could cause the simulated sample to produce results that are consistent with target behavior. Panel regression of these simulation samples, along with the actual sample, was conducted using a modified version of the leverage model that has leverage ratio as the dependent variable and the lagged leverage ratio as well as various firm-specific variables as the independent variables. The parameter coefficient estimates for the simulation samples were obtained by taking the average of 500 replications of the particular simulation. The signs for the coefficients on the lagged leverage ratio and firm-specific variables obtained from the leverage regressions were in the expected directions with respect to the leverage ratio. The significance of the coefficients can be viewed as verification that the leverage ratio for South Korean firms is related to the firm-specific variables selected for the leverage regression analysis.

No abstract