• Journal of the Korean Institute of Intelligent Systems
• /
• v.18 no.5
• /
• pp.632-637
• /
• 2008

In real system application, the propeller shaft rate (PSR) estimation algorithm for the feature extraction of the sonar target operates with the following problems: it requires both accurate and efficient the fundamental finding method because it is essential and difficult to distinguish harmonic family composed of the fundamental and its harmonics from the multiple spectral lines in the frequency spectrum-based sonar target classification, and further, it requires an easy design procedure in terms of its structures and parameters. To solve these problems, an evolutionary PSR estimation algorithm using an expert knowledge and the evolution strategy, is proposed. To verify the performance of the proposed algorithm, a sonar target PSR estimation is performed. Simulation results show that the proposed algorithm effectively solves the problems in the realtime system application.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2008.08a
• /
• pp.149-150
• /
• 2008

Generally, the propeller shaft rate (PSR) estimation algorithm for the classification of the sonar target has the following problems: it requires both accurate and efficient the fundamental finding method because it is essential and difficult to distinguish harmonic family from the frequency spectrum, and further, it requires an easy design procedure in terms of its structures and parameters. To solve these problems, an evolutionary PSR estimation algorithm using an expert knowledge and the evolution strategy, is proposed. Simulation results show that the proposed algorithm effectively solves the problems in the realtime system application.

• The Korean Journal of Financial Studies
• /
• v.7 no.1
• /
• pp.71-98
• /
• 2001

본 연구는 절대가치 추정방법인 EVA모형과 FCFF모형, 그리고 상대가치 추정방법인 PER모형, PBR모형 및 PSR모형의 한국기업에의 적합성을 검증하는 것을 목표로 하고 있다. 분석대상기간은 1992년$\sim$1996년까지 5년 간으로 하였으며 수익률 자료를 획득할 수 있고 괴리율을 계산할 수 있는 207개 기업을 전체 표본기업으로 선정하였다. 절대가치평가모형에 의한 집단간 차이분석에서는 EVA모형과 FCFF모형 모두 집단간에 유의적인 차이를 보이는 것으로 나타났다. 그리고 상대가치평가모형에 의한 집단간 차이분석에서는 PBR모형과 PSR모형은 분석기간 동안 집단간에 유의적인 차이를 보이는 것으로 나타났다. PER모형의 경우에는 재무제표 공시일 이전에 이미 반영되고 공시일 이후에는 차이를 보이지 않는 것으로 나타났다. 회귀분석 결과 주식수익률은 산업평균수익률인 Rc와 FCFF모형에 의한 괴리율과 강한 유의적인 관계를 갖고 PBR모형에 의한 괴리율과는 약한 유의적인 관계를 갖는 다는 것을 확인할 수 있었다. 이상의 연구결과는 절대가치 추정방법인 FCFF모형과 상대가치 추정방법인 PBR모형에 의한 기업평가모형이 제한적이지만 한국주식시장에서 어느 정도 적합성을 가질 수 있다(재무제표 공시일 기준)는 가능성을 보여주고 있다.

• Management & Information Systems Review
• /
• v.29 no.2
• /
• pp.1-25
• /
• 2010

This study attempted to empirically test the determinants of stock returns in Korean stock market applying multi-factor model proposed by Haugen and Baker(1996). Regression models were developed using 16 variables related to liquidity, risk, historical price, price level, and profitability as independent variables and 690 stock monthly returns as dependent variable. For the statistical analysis, the data were collected from the Kis Value database and the tests of forecasting power in this study minimized various possible bias discussed in the literature as possible. The statistical results indicated that: 1) Liquidity, one-month excess return, three-month excess return, PER, ROE, and volatility of total return affect stock returns simultaneously. 2) Liquidity, one-month excess return, three-month excess return, six-month excess return, PSR, PBR, ROE, and EPS have an antecedent influence on stock returns. Meanwhile, realized returns of decile portfolios increase in proportion to predicted returns. This results supported previous study by Haugen and Baker(1996) and indicated that firm-characteristic model can better predict stock returns than CAPM. 3) The firm-characteristic model has better predictive power than Fama-French three-factor model, which indicates that a portfolio constructed based on this model can achieve excess return. This study found that expected return factor models are accurate, which is consistent with other countries' results. There exists a surprising degree of commonality in the factors that are most important in determining the expected returns among different stocks.