• International Journal of Naval Architecture and Ocean Engineering
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• v.3 no.3
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• pp.181-192
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• 2011

Recently, the speed of change related with enterprise management is getting faster than ever owing to the competition among companies, technique diffusion, shortening of product lifecycle, excessive supply of market. For the example, the compliance condition (such as delivery date, product quality, etc.) from the ship owner is getting complicated and the needs for the new product such as FPSO, FSRU are coming to fore. This paradigm shift emphasize the rapid response rather than the competitive price, flexibility and agility rather than effective and optimal perspective for the domestic shipbuilding company. So, domestic shipbuilding companies have to secure agile and flexible ship production environment that could respond change of market and requirements of customers in order to continue a competitive edge in the world market. In this paper, I'm going to define a standard shipbuilding production management system by investigating the environment of domestic major shipbuilding companies. Also, I'm going to propose a unified ship production management and system for the operation of unified management through detail analysis of the activities and the data flow of ship production management. And, the system functions for the strategic approach of ship production management are investigated through the business administration tools such as performance pyramid, VDT and BSC. Lastly, the research of applying strategic KPI to the digital shipyard as virtual execution platform is conducted.

• The Korean Journal of Financial Studies
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• v.3 no.1
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• pp.233-265
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• 1996

We examine the impact of public and private information on price movements using the thirty DJIA stocks and twenty-one NASDAQ stocks. We find that the standard deviation of daily returns on information days (dividend announcement, earnings announcement, insider purchase, or insider sale) is much higher than on no-information days. Both public information matters at the NYSE, probably due to masked identification of insiders. Earnings announcement has the greatest impact for both DJIA and NASDAQ stocks, and there is some evidence of positive impact of insider asle on return volatility of NASDAQ stocks. There has been considerable debate, e.g., French and Roll (1986), over whether market volatility is due to public information or private information-the latter gathered through costly search and only revealed through trading. Public information is composed of (1) marketwide public information such as regularly scheduled federal economic announcements (e.g., employment, GNP, leading indicators) and (2) company-specific public information such as dividend and earnings announcements. Policy makers and corporate insiders have a better access to marketwide private information (e.g., a new monetary policy decision made in the Federal Reserve Board meeting) and company-specific private information, respectively, compated to the general public. Ederington and Lee (1993) show that marketwide public information accounts for most of the observed volatility patterns in interest rate and foreign exchange futures markets. Company-specific public information is explored by Patell and Wolfson (1984) and Jennings and Starks (1985). They show that dividend and earnings announcements induce higher than normal volatility in equity prices. Kyle (1985), Admati and Pfleiderer (1988), Barclay, Litzenberger and Warner (1990), Foster and Viswanathan (1990), Back (1992), and Barclay and Warner (1993) show that the private information help by informed traders and revealed through trading influences market volatility. Cornell and Sirri (1992)' and Meulbroek (1992) investigate the actual insider trading activities in a tender offer case and the prosecuted illegal trading cased, respectively. This paper examines the aggregate and individual impact of marketwide information, company-specific public information, and company-specific private information on equity prices. Specifically, we use the thirty common stocks in the Dow Jones Industrial Average (DJIA) and twenty one National Association of Securities Dealers Automated Quotations (NASDAQ) common stocks to examine how their prices react to information. Marketwide information (public and private) is estimated by the movement in the Standard and Poors (S & P) 500 Index price for the DJIA stocks and the movement in the NASDAQ Composite Index price for the NASDAQ stocks. Divedend and earnings announcements are used as a subset of company-specific public information. The trading activity of corporate insiders (major corporate officers, members of the board of directors, and owners of at least 10 percent of any equity class) with an access to private information can be cannot legally trade on private information. Therefore, most insider transactions are not necessarily based on private information. Nevertheless, we hypothesize that market participants observe how insiders trade in order to infer any information that they cannot possess because insiders tend to buy (sell) when they have good (bad) information about their company. For example, Damodaran and Liu (1993) show that insiders of real estate investment trusts buy (sell) after they receive favorable (unfavorable) appraisal news before the information in these appraisals is released to the public. Price discovery in a competitive multiple-dealership market (NASDAQ) would be different from that in a monopolistic specialist system (NYSE). Consequently, we hypothesize that NASDAQ stocks are affected more by private information (or more precisely, insider trading) than the DJIA stocks. In the next section, we describe our choices of the fifty-one stocks and the public and private information set. We also discuss institutional differences between the NYSE and the NASDAQ market. In Section II, we examine the implications of public and private information for the volatility of daily returns of each stock. In Section III, we turn to the question of the relative importance of individual elements of our information set. Further analysis of the five DJIA stocks and the four NASDAQ stocks that are most sensitive to earnings announcements is given in Section IV, and our results are summarized in Section V.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.65-82
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• 2021

Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.39-55
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• 2019

Recently banks and large financial institutions have introduced lots of Robo-Advisor products. Robo-Advisor is a Robot to produce the optimal asset allocation portfolio for investors by using the financial engineering algorithms without any human intervention. Since the first introduction in Wall Street in 2008, the market size has grown to 60 billion dollars and is expected to expand to 2,000 billion dollars by 2020. Since Robo-Advisor algorithms suggest asset allocation output to investors, mathematical or statistical asset allocation strategies are applied. Mean variance optimization model developed by Markowitz is the typical asset allocation model. The model is a simple but quite intuitive portfolio strategy. For example, assets are allocated in order to minimize the risk on the portfolio while maximizing the expected return on the portfolio using optimization techniques. Despite its theoretical background, both academics and practitioners find that the standard mean variance optimization portfolio is very sensitive to the expected returns calculated by past price data. Corner solutions are often found to be allocated only to a few assets. The Black-Litterman Optimization model overcomes these problems by choosing a neutral Capital Asset Pricing Model equilibrium point. Implied equilibrium returns of each asset are derived from equilibrium market portfolio through reverse optimization. The Black-Litterman model uses a Bayesian approach to combine the subjective views on the price forecast of one or more assets with implied equilibrium returns, resulting a new estimates of risk and expected returns. These new estimates can produce optimal portfolio by the well-known Markowitz mean-variance optimization algorithm. If the investor does not have any views on his asset classes, the Black-Litterman optimization model produce the same portfolio as the market portfolio. What if the subjective views are incorrect? A survey on reports of stocks performance recommended by securities analysts show very poor results. Therefore the incorrect views combined with implied equilibrium returns may produce very poor portfolio output to the Black-Litterman model users. This paper suggests an objective investor views model based on Support Vector Machines(SVM), which have showed good performance results in stock price forecasting. SVM is a discriminative classifier defined by a separating hyper plane. The linear, radial basis and polynomial kernel functions are used to learn the hyper planes. Input variables for the SVM are returns, standard deviations, Stochastics %K and price parity degree for each asset class. SVM output returns expected stock price movements and their probabilities, which are used as input variables in the intelligent views model. The stock price movements are categorized by three phases; down, neutral and up. The expected stock returns make P matrix and their probability results are used in Q matrix. Implied equilibrium returns vector is combined with the intelligent views matrix, resulting the Black-Litterman optimal portfolio. For comparisons, Markowitz mean-variance optimization model and risk parity model are used. The value weighted market portfolio and equal weighted market portfolio are used as benchmark indexes. We collect the 8 KOSPI 200 sector indexes from January 2008 to December 2018 including 132 monthly index values. Training period is from 2008 to 2015 and testing period is from 2016 to 2018. Our suggested intelligent view model combined with implied equilibrium returns produced the optimal Black-Litterman portfolio. The out of sample period portfolio showed better performance compared with the well-known Markowitz mean-variance optimization portfolio, risk parity portfolio and market portfolio. The total return from 3 year-period Black-Litterman portfolio records 6.4%, which is the highest value. The maximum draw down is -20.8%, which is also the lowest value. Sharpe Ratio shows the highest value, 0.17. It measures the return to risk ratio. Overall, our suggested view model shows the possibility of replacing subjective analysts's views with objective view model for practitioners to apply the Robo-Advisor asset allocation algorithms in the real trading fields.

• Environmental and Resource Economics Review
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• v.21 no.2
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• pp.301-319
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• 2012

The primary purpose of Renewable Portfolio Standard (RPS) is to facilitate investment in renewable energy technology. Since emission trading program has similar purpose, it is conceivable to attempt to link RPS and emission trading program through interlinked markets. RPS in Korea with single REC and emission allowance markets has particular advantages for constructing linkages between two markets. This paper provides a real option model to examine investment effects of linkage of RPS to the trading program. Emission permit price and REC price are assumed to follow stochastic processes and renewable investment is irreversible. The result shows that linked market provides further incentive for renewable investment by raising managerial flexibility for power companies.

• Korean Journal of Organic Agriculture
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• v.32 no.1
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• pp.25-37
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• 2024

This study is to apply behavioral economics-an economics that studies actual human behavior based on cognitive psychology-to the farming decision-making process of onion and garlic farmers. Of behavioral economic theories, dual system theory and prospect theory (value function), heuristic and bias were surveyed and examined in the field. The reference point of farmers was farming experience of the previous year, and so they showed reference dependence and anchoring heuristic, not rational thinking on production cost plan. And they showed status quo bias that cultivated continuously the previous year or the present crop. This status quo bias is related to loss aversion propensity. Farmers did not usually change cultivating crops, in other words, they showed diminishing sensitivity-insensitive to those that the more revenue or loss was increased. This diminishing sensitivity is related to loss aversion propensity and status quo bias. Also, farmers had representativeness heuristic because they regarded auction price of Garakdong wholesale market as the standard price level despite various prices by production region. And farmers had the affect heuristic that they depended on producers' organization data more than the state-run research institute ones about cultivation intentions and actual situations.

• Korean Journal of Construction Engineering and Management
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• v.18 no.6
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• pp.47-56
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• 2017

As of 2017, there are 848 million households living in apartment and 55.87% of Aged apartments over 15 years old. The allowable standard for remodeling the apartment is more than 15 years and the market for remodeling the apartment will continue to increase. For the success of the remodeling project feasibility analysis is important but the existing feasibility analysis of new construction and reconstruction is being used for remodeling feasibility analysis. Therefore, it is necessary to study the feasibility analysis of customized remodeling without increasing the number of households according to the building law. Purpose of this paper is to develop a feasibility analysis methodology for customized remodeling projects by deriving the factors affecting the formation of land prices and building prices in apartment. According to the concept of price formation of the apartment, the analysis method of the customized remodeling of the old apartment using the factors affecting the Land Price Indexes, Officially Assessed Individual Land Price, House Price Indexes, and Officially Assessed Individual House Price was suggested. The Stair Price Algorithm developed in this research can be utilized at the stage of selecting remodeling contractors after the remodeling housing association is established.

• Journal of Fashion Business
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• v.7 no.4
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• pp.67-77
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• 2003

This study investigated the difference of the purchasing realities and the degree of satisfaction of maternity dress according to occupation and age. The purpose of this study was to collect data needed to the maternity dress maker for the better quality of their product and the more comfortable maternity dress wearing of pregnant women. The results of study were as follows. The attitude of purchasing and the degree of satisfaction of maternity dress according to age showed significant differences as follows. First, the dress styles were the significant difference in the kind of formal trousers and casual trousers, one-piece dress, jumper skirt+shirt, vest+trousers. Second, the purchase place was the significant difference in the shop of clothes made, market, maternity dress shop, wearing together. Third, at the purchase time of dress, the satisfactory degree of an appraised standard was the significant difference in the period of wearing, the easiness of exchange and repayment, the wearing numeral degree of other people, price, discount sale, degree of brand recognition, encouragement of other people.

• Proceedings of the Korean Society of Postharvest Science and Technology of Agricultural Products Conference
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• 2003.10a
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• pp.51-70
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• 2003

In recent years, Korean rice must compete with the rice of advanced countries under Doha Development Agenda(DDA) and free Trade Agreement(FTA). Therefore we should find more active and positive solution in rice industry according to the inncreasing power of international pressure. Increasing rice production was the most important policy during the past food-deficient days, but recently, with overproduction of rice, various circulation system by the brand(price)-differentiation should be settled in a recent market of Korea. Nowadays, some advanced rice farmers and Rice Processing Complex(RPC) managers developed new brands of rice with high-quality, adding healthy materials and environment-friendly farming methods. Therefore, the future strategy of making a new brand rice should be planned including selection of rice variety, cultural and post-harvest techniques, circulation and processing methods to compete against foreign rice. And environment-friendly farming is also recommendable for food safety and differentiate from imported rice. For the purpose of successful brand-rice, the following points might be considered. Firstly, selection of good quality rice and continual development of good variety must be conducted for the differentiation of Korean rice from foreign rice. Secondly, a special contract between producer and consumer with functional-rice, organic filming-rice, specific-rice will be recommendable. Thirdly, improvement of post-harvest management and milling system are necessary for the production of differentiated-rice. Fortunately, standard of inspection, rules of description for brand-rice must be developed by a more scientific examination in order to settlement of trust for consumer. Finally, provincial or regional-representative brand rice must be settled and conducted for the development of agreement market system between producer and consumer.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.2
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• pp.247-255
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• 2019

This study examines the different roles of cash flow in assessing investment returns in the Association of Southeast Asian Nations (ASEAN). The analysis covers over 900 listed firms across Malaysia, Indonesia, Philippines, Singapore and Thailand for the period post the Asian financial crisis of 2001-2017. Firm-level panel data analysis shows that cash flow factors are important in all contexts of cash return on assets, earnings quality and market value multiple across the region even after controlling for typical measures of profitability. The results suggest that firms should manage cash flow prudently in considerations of firm value from the shareholder's perspective, measured directly using stock return. Cash profitability on assets should become an important firm performance indicator, whilst higher cash component over reported earnings is preferred. The market also tends to respond favourably to cash flow yield as a price multiple in valuation, outpacing the role of earnings yield. Such findings are robust across the pre and post subprime crisis periods, across estimation methods pertaining to finance panel standard errors, as well as across static and dynamic considerations of returns. It is hence sensible to consider cash flow factors in the research pertaining to asset pricing and factor investing in the ASEAN region.