• KDI Journal of Economic Policy
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• v.40 no.1
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• pp.45-66
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• 2018

This paper measures the extent of comovements in stock returns between Korea and three major countries (China, Japan and the U.S.) using industry-level data for Korea from 2003 to 2016 in the spirit of the international capital asset pricing model. It also examines what drives the comovements between Korea and the three countries. We find that the comovements of Korean stock returns with those of the U.S. and Japan became smaller after the global financial crisis. In contrast, the comovement in stock returns between Korea and China became larger after the crisis. After an additional analysis, we conclude that trade linkage is the main driver of the comovements between Korea and the three countries.

• Journal of the Korean Data and Information Science Society
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• v.18 no.1
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• pp.41-50
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• 2007

This study attempts to test the lead-lag relationship between the stock price and the business indicator in the multivariate context. It additionally investigates the short and long-run dynamic relationships among the four market variables. The hypothesis that the stock price leads the business indicator is found to be rejected for the whole study period. When structural change is considered, the statistical result appears to reflect the reality. The causal relationships among the variables in the former period are simpler than those in the latter period, and the stock price significantly appears to lead the business indicator. On the other hand, the relationship between the stock price and the business indicator in the latter period appears to prove the recent hypothesis of their coincidence.

• The Korean Journal of Financial Management
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• v.24 no.2
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• pp.183-206
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• 2007

The price-dividend ratio is one of the most frequently used financial variables to predict long-horizon stock return. However, the persistency of the price-dividend ratio is found to cause the spuriousness of the stock return prediction regression. The stable relationship between the stock price and the dividend, however, seems to weaken after World War II and to experience structural break. In this paper, we identify a structural change in the cointegrating relationship between the log of the stock price and the log of the dividend. Confirming a structural break in 1962, we subdivide the sample and apply the fully modified estimator to correct for the nonstationarity of the regressor. With the subdivided sample, we exercise the nonparametric bootstrap procedure to derive the empirical distribution of the test statistics and fail to find return predictability in each subsample period.

• Journal of Aquaculture
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• v.16 no.2
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• pp.69-75
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• 2003

Genetic variability and population structure of 11 natural ayu, Plecoglossus altivelis populations and one hatchery stock were assessed by starch gel electrophoretic analysis with 10 enzyme coding loci. Three loci were polymorphic (lower than 0.95 in major allele frequency) in natural populations,2 loci in hatchery stock. The average number of alleles per locus was 1.38. Observed heterozygosities ranged from 0.0235 to 0.088 (0.055 on the average) in natural population while 0.0925 in hatchery stock. The genetic distance among natural populations measured 0.000047-0.005407 and no significant differentiation was observed among them. On the other hand, a signifcant genetic distance was found between natural populations and the hatchery stock with measuring 0.002032-0.O08605. The results in this study suggest that the hatchery stock has diverged from natural populations, and also that careful to maintain sustainable and effective population size (parents number) should be made.

• Asia pacific journal of information systems
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• v.9 no.3
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• pp.93-110
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• 1999

The previous studies regarding the stock returns have advocated that industry effects exist over entire industry. As the industry categories are more rigid, the demand for predicting the industry sectors is rapidly increasing. The advances in Artificial Intelligence and Neural Networks suggest the feasibility of a valuable computational model for stock returns prediction. We propose a sector-factor model for predicting the return on industry stock index using neural networks. As a substitute for the traditional models, neural network model may be more accurate and effective alternative when the dynamics between the underlying industry features are not well known or when the industry specific asset pricing equation cannot be solved analytically. To assess the potential value of neural network model, we simulate the resulting network and show that the proposed model can be used successfully for banks and general construction industry. For comparison, we estimate models using traditional statistical method of multiple regression. To illustrate the practical relevance of neural network model, we apply it to the predictions of two industry stock indexes from 1980 to 1995.

• Management Science and Financial Engineering
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• v.15 no.2
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• pp.101-118
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• 2009

In quantitative contexts, data mining is widely applied to the prediction of stock prices from financial time-series. However, few studies have examined the potential of data mining for shedding light on the qualitative problem-solving knowledge of experts who make stock price predictions. This paper presents a GA-based data mining approach to characterizing the qualitative knowledge of such experts, based on their observed predictions. This study is the first of its kind in the GA literature. The results indicate that this approach generates rules with higher accuracy and greater coverage than inductive learning methods or neural networks. They also indicate considerable agreement between the GA method and expert problem-solving approaches. Therefore, the proposed method offers a suitable tool for eliciting and representing expert decision rules, and thus constitutes an effective means of predicting the stock price index.

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.153-166
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• 2003

This study presents the time-divided forecasting model to integrate evolutionary optimization algorithm and change point detection based on artificial neural networks (ANN) for the prediction of (Korea) stock price index. The genetic algorithm(GA) is introduced as an evolutionary optimization method in this study. The basic concept of the proposed model is to obtain intervals divided by change points, to identify them as optimal or near-optimal change point groups, and to use them in the forecasting of the stock price index. The proposed model consists of three phases. The first phase detects successive change points. The second phase detects the change-point groups with the GA. Finally, the third phase forecasts the output with ANN using the GA. This study examines the predictability of the proposed model for the prediction of stock price index.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.40 no.4
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• pp.10-15
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• 2008

Flocculation phenomena of the stock mixed with cellulosic fibers, fillers and polymers were investigated by a new turbidity measurement system consisted of a probe-type turbidimeter, data acquisition system and computer. The probe-type turbidimeter allowed to measure the real time flocculation of the stock induced by single polymer and microparticle systems. Flocculation phenomena were evaluated by average and final relative turbidity indices. Turbidity and flocculation showed inverse relationship, i.e. the turbidity decreased with the formation of flocs. Relative turbidity of the stock treated with microparticle system was lower than that of the stock containing single polymer system, which indicated that the microparticle system showed greater floc forming efficiency than single polymer system.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.806-812
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• 2008

Many kinds of rolling-stocks that have various control methods are being operated by Seoulmetro which is a history of a city railroad rolling-stock. Seoulmetro is being faced with a wheel management comparing of other lines with a perpendicular wear of wheel and a side damage, and so on, by operating several cars at a loop line. This is causing maintenance expenses increase and deteriorating a fusibility of rolling-stock, for it has an effect on a rolling-stock using. A cutting pattern of wheel and a wear form affect the expected span of a wheel. A wheel cutting cause is classifed into cutting for reprofiling of a flange wear of wheel and for removing every kind defect which originates from wheel wear. In this study, Seoulmetro exhibit a stable rolling-stock use method and a reasonable management method of wheel, analysing wheel exchange condition and cutting management of wheel.

• Proceedings of the KSR Conference
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• 2009.05a
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• pp.791-794
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• 2009

Each nation of the world is intensively propelling the R&D investment to solve the financial crisis and worldwide economic recession occurred from last year. This means the world economic is under economic system based on the knowledge. So, The R&D is continuously propelled for possession of the technology through the R&D stock and which is core in the knowledge based economic system. In this world stream, our government is also increasing the R&D investment and checked the technology level through surveying the R&D stock and corn parison of each industry or world. The R&D investment of the railroad is continued but there is no data of the R&D stock. So, surveying the railroad R&D stock and comparing with korea industry is processed.