한국 이동통신시장에 대한 기업가치평가에 관한 사례 연구

정세윤 Graduate School, Korea University 2010 국내석사

This study is a case analysis report of equity valuation for Korean mobile telecommunication industry. There are three companies in Korean mobile telecommunication industry, that is, SK Telecom(SKT), KT Freetel(KTF), LG Telecom(LGT). We will conduct an equity valuation of these companies in this study. This case study begins to discuss the theoretical background of Residual Operating Income (ReOI) valuation model which is derived from Ohlson(1995) model. Then, we will analyze the implemental framework of ReOI valuation model. Since residual income is created by operating activity, ReOI model focuses on operating income ignoring the effects of financial activity. We will explain how to separate the results of operating activity from them of financial activity within balance sheet and income statement. This will lead to reformulated financial statements(both of balance sheet and income statement). After analyzing the reformulated financial statements, we will show where those three companies are and explain how to forecast the main value drivers for ReOI model. Lastly, we will finalize our equity valuation by incorporating the forecasts into ReOI valuation model. Although there are many theoretical and empirical research papers regarding to the equity valuation, there is no case analysis report for the practical implementation of equity valuation model for Korean companies. This case study aims to fill this void in the academic literature. This case study will contribute to both industry and academic communities by describing how to implement theoretical valuation model in practice. Keywords: Equity Valuation, Forecasting, Residual Operating Income Valuation Model, Reformulation of Financial Statements

Comparison of methods to calculate the implied cost of equity capital for Korean firms

이호석 서울대학교 대학원 2012 국내석사

This thesis reviews five recent methods of calculating the implied cost of equity capital, and then attempts to apply the Korean firms’ ex-post financial and accounting data to those models and verify which of those proved to be the most reliable proxy for the realized returns of the Korean stock market between 1981 and 2010. Korean firm data between 1981 and 2010 are applied to each model to calculate the implied cost of equity capital estimates between 1981 and 2010. Then the estimates are regrouped into quintile portfolios according to their magnitude. Finally, the average estimate of each portfolio is compared with the average realized return of each quintile portfolio created by order of realized returns of the same sample firms during the same period. The model with the least difference is declared to be the one producing the best estimates as a proxy for the realized returns in the Korean stock market. The Capital Asset Pricing Model still seems to produce the best estimates as a proxy for the realized returns of the Korean firms. The other four methods, depending on what equity valuation model they are based on, exhibit different level of performance at different quintiles; the ones based on the residual income valuation model perform better at higher quintiles while the ones based on the abnormal earnings growth valuation model perform better at lower quintiles. Among the four models Gode and Mohanram (2003), in general, is the best when tested with the extreme estimates included. Hou et al. (2010), however, is the best at all of the 2nd, 3rd, and 4th quintiles when considered without the highest and the lowest quintiles and with a longer time horizon. Both models exhibited almost identical performance when the extreme values are removed and the time horizon is short. 본 학위논문은 자기자본비용을 도출하기 위하여 비교적 최근에 고안되어 널리 사용되고 있는 다섯 개의 모델들을 검토하고, 1981~2010년 사이 이들 중 어떤 모델이 한국 주식 시장의 실제 사후 실현수익률에 가장 가까운 예측치를 도출하였는지 검증하였다. 이를 위하여 동기간 1981~2010년 한국 상장기업 데이터를 각 모델에 대입하여 동기간 자기자본비용 예측치를 도출하였다. 다음으로 각 모델별로 계산된 예측치들을 크기에 따라 10개의 포트폴리오로 구성하여 각 포트폴리오별로 평균 자기자본비용 예측치를 계산하였으며, 한편 동 기간 실제 수익률 또한 크기에 따라 5개의 포트폴리오로 구성하여 역시 각 포트폴리오별로 평균 사후 실현수익률을 계산하였다. 그리고 최상위에서부터 최하위 포트폴리오에 이르기까지 다섯 개의 평균 예측치와 평균 사후수익률을 짝지어 비교하여 그 차이를 분석하였다. 다섯 개의 모델 별로 이 과정을 되풀이하여 그 차이의 합이 가장 작은 모델이 2005~2009년 한국 주식시장의 사후 실현수익률에 가장 근접한 자기자본비용 예측치를 도출하는 모델로 결정하였다. 분석 결과, 예상과는 달리 수십 년 전 개발된 자본자산가격결정모형이 여전히 한국 기업들의 사후 실현수익률에 가장 근접한 예측치를 제시하는 것으로 나타났다. 다섯 개의 모형 중 하나는 한국 기업 데이터를 대입하여 계산하는 과정에서 제대로 답이 도출되지 않는 경우가 많아 사용이 불가하였으며, 나머지 네 개의 모형은 잔여이익모형에 기반한 경우 상위 포트폴리오에서 상대적으로 더 나은 예측력을 보였으며, 이익초과성장률모형에 기반한 경우 하위 포트폴리오에서 상대적으로 더 나은 예측력을 보였다. 극단값까지 모두 포함하여 분석하였을 때에는 네 모델 중 Gode and Mohanram (2003)에 제시된 모형이 가장 나은 결과를 보여 주었다. 그러나 극단값을 제거하기 위하여 최상위 및 최하위 포트폴리오를 제외하고 전 기간을 대상으로 분석하였을 때에는 Hou et al. (2010)이 2, 3, 4번째 포트폴리오 모두에서 가장 나은 예측력을 보여 주었다. 한편 모델의 특성에 따라 예측치를 도출할 수 있는 기간이 각기 다르기에 모든 모델이 공통적으로 예측치를 낼 수 있는 1990~1998년만을 대상으로도 극단값을 제거하여 분석하였는데, 이 경우에는 두 모델 모두 비슷한 예측력을 나타내었다.

Lotte shopping valuation using residual operating inocme model

박인우 서울대학교 대학원 2008 국내석사

(An)Alternative valuation model based on Shareholders' real options

손병철 서울대학교 대학원 2006 국내박사

Three essays on the fundamental value and the predictability of stock returns

남혜정 서울대학교 대학원 2008 국내박사

How do institutional investors interact with sell-side analysts?

강일주 Graduate School Korea University 2015 국내박사

This paper examines how institutional investors interact with sell-side analysts in Korean stock market. I focus on the role of institutional investors as sophisticated stock market participants who may analyze sell-side analysts’ information components as earnings forecast in addition to using their outputs as recommendation, target price. Furthermore, I examine whether institutional investors can differentiate between good information and bad information provided by sell-side analysts. By using a sample of 1,421 firm/year observations in Korean stock market from 2001 to 2011, the results indicate that institutional investors may take an active role as a mechanism to incorporate V/P ratios (value to price) derived from earnings forecast information to analyze sell-side analysts’ information components, in addition to using the outputs as recommendation. Moreover, I find that institutional investors are more likely to use sell-side analysts’ information when the earnings forecast is more accurate, meaning that institutional investors can differentiate between good information and bad information. On the other way round, I examine if institutional investors’ trading behavior affects sell-side analysts’ information, and find that sell-side analysts do not use information produced from buy-side investors’ trading behavior. In sum, I can conclude that the main results support the causality relationship that institutional investors trade by looking at the sell-side analysts’ information components as earnings forecast in detail, and by using their information only when the earnings forecast information is more accurate, not the other way round. This study can shed some lights on the knowledge about the unobserved interaction between the most sophisticated stock market participants who are considered to have taken a role to enhance stock market efficiency, and extends the prior literature which factors bring about institutional investors’ sophistication.