• Proceedings of the Society of Korea Industrial and System Engineering Conference
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• 2002.05a
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• pp.343-348
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• 2002

We are concerned with a long-term replenishment contract for the ARIMA demand process in a supply chain. The chain is composed of one supplier, one buyer and consumers for a product. The replenishment contract is based upon the well-known (s, Q) policy but allows us to contract future replenishments at a time with a price discount. Due to the larger forecast error of future demand, the buyer should keep a higher level of safety stock to provide the same level of service as the usual (s, Q) policy. However, the buyer can reduce his purchase cost by ordering a larger quantity at a discounted price. Hence, there exists a trade-off between the price discount and the inventory holding cost. For the ARIMA demand process, we present a model for the contract and an algorithm to find the number of the future replenishments. Numerical experiments show that the proposed algorithm is efficient and accurate.

• The KIPS Transactions:PartB
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• v.14B no.7
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• pp.531-540
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• 2007

In this research, we proposed a two-phase hybrid stock price forecasting model with cointegration tests and artificial neural networks. Using not only the related stocks to the target stock but also the past information as input features in neural networks, the new model showed an improved performance in forecasting than that of the usual neural networks. Firstly in order to extract stocks which have long run relationships with the target stock, we made use of Johansen's cointegration test. In stock market, some stocks are apt to vary similarly and these phenomenon can be very informative to forecast the target stock. Johansen's cointegration test provides whether variables are related and whether the relationship is statistically significant. Secondly, we learned the model which includes lagged variables of the target and related stocks in addition to other characteristics of them. Although former research usually did not incorporate those variables, it is well known that most economic time series data are depend on its past value. Also, it is common in econometric literatures to consider lagged values as dependent variables. We implemented a price direction forecasting system for KOSPI index to examine the performance of the proposed model. As the result, our model had 11.29% higher forecasting accuracy on average than the model learned without cointegration test and also showed 10.59% higher on average than the model which randomly selected stocks to make the size of the feature set same as that of the proposed model.

• Korean System Dynamics Review
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• v.3 no.1
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• pp.43-60
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• 2002

This paper describes the forecast of wholesale price in competitive Korean electricity market using the system dynamics approach. The system dynamics concepts have been implemented with the Ithink software. This software facilitates the development of stock and flow model with information feedback. Using this model, the future wholesale electricity price can be computed hour by hour, quarterly, and yearly. This model also gives the energy planner the opportunity to create different scenarios for the future of deregulated wholesale markets in Korea. Also It will lead to increased understanding of competitive wholesale market as a complex, dynamic system. Research results show that the plant construction appeared in waves of boom and bust in Korean electricity market like real estate construction. That is, the Korea wholesale market's new power plants and the market price will appear the Boom and Bust cycle. It is very similar behavior as real estate industry. In case of consideration of DSM program, The DSM savings lead to a somewhat different timing of the booms in construction and of price spikes. But the DSM programs do not eliminated the fundamental dynamics of the boom and bust. And the wholesale price is maintained at the lower level compared to the case of without DSM program. However, the unexpected result is found that due to the lower market price, Investor make significantly less investment in new CCs, which leads to the higher wholesale price after 2010. It suggests that the DSM Policy must be implemented with the dynamics of competitive Electricity Market.

• Journal of the military operations research society of Korea
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• v.30 no.2
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• pp.96-107
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• 2004

This paper deals with $\ulcorner$Requirement Decision Model for Repair Parts supplied by the Government$\lrcorner$ which is to reduce Aircraft Contract Maintenance Cost. It aims to find solutions to the fundamental problems of the Aircraft Contract Maintenance System. Under the current Aircraft Contract Maintenance System, it is hard to forecast the exact demand of repair parts, so support rate of Repair Parts supplied by the Government is restricted under 50 percent. It is inevitable to purchase Repair Parts from the firm with much higher price than those of Government source. However, absence of fixed demand pattern makes it difficult to improve accuracy of demand forecast. As a solution to these problems, this model prevents a cost increase due to the unit price difference between Repair Parts supplied by the Government and Repair Parts purchased by the Firm. It also reflects demand characteristics of each repair part, and prevents continual stock increase by setting an upper limit on the amount of Repair Parts supplied by the Government. The effectiveness of this model is verified by empirical analysis using the latest raw data. By applying this model to real situation, we expect to reduce about 4 billion won every year.

• Journal of Internet Computing and Services
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• v.9 no.1
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• pp.129-135
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• 2008

This paper presents a methodology to forecast KOSPI index by extracting fuzzy rules based on the neural network with weighted fuzzy membership functions (NEWFM) and the minimized number of input features using the distributed non-overlap area measurement method. NEWFM classifies upward and downward cases of KOSPI using the recent 32 days of CPPn,m (Current Price Position of day n for n-1 to n-m days) of KOSPI. The five most important input features among CPPn,m and 38 wavelet transformed coefficients produced by the recent 32 days of CPPn,m are selected by the non-overlap area distribution measurement method. For the data sets, from 1991 to 1998, the proposed method shows that the average of forecast rate is 67.62%.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.105-117
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• 2022

This study analyzes the effects between stock returns and interest rate spread, difference between long-term and short-term interest rate through the polynomial linear regression analysis. The existing research concentrated on the business forecast through the interest rate spread focusing on the US market. The previous studies verified the interest rate spread based on the leading indicators of business forecast by moderating the period of long-term/short-term interest rates and analyzing the degree of leading. After the 7th reform of composite indices of business indicators in Korea of 2006, the interest rate spread was included in the items of composing the business leading indicators, which is utilized till today. Nevertheless, there are a few research on stock returns of each industry and interest rate spread in domestic stock market. Therefore, this study analyzed the stock returns of each industry and interest rate spread targeting Korean stock market. This study selected the long-term/short-term interest rates with high causality through the regression analysis, and then understood the correlations with each leading period and industry. To overcome the limitation of the simple linear regression analysis, polynomial linear regression analysis is used, which raised explanatory power. As a result, the high causality was verified when using differences between returns of corporate bond(AA-) without guarantee for three years by leading six months and call rate returns as interest rate spread. In addition, analyzing the stock returns of each industry, the relation between the relevant interest rate spread and returns of the automobile industry was the closest. This study is significant in the aspect of verifying the causality of interest rate spread, business forecast, and stock returns in Korea. Even though it could be limited to forecast the stock price by using only the interest rate spread, it would be working as a strong factor when it is properly utilized with other various factors.

• The Journal of Bigdata
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• v.1 no.2
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• pp.21-34
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• 2016

There are various investment strategy reports available online, prepared by many financial analysts. If the correlation between the title of the report and analyst forecast can be found, we can tell from the title whether analyst' forecast will be reliable or not. The objective of this study is to see the correlation between the title of analyst investment strategy report and the actual result of forecast by using the Text Mining technique. The result of actual analysis showed that "strong buy and sell call" appeared in the title lead the higher accuracy of analyst forecast and fulfillment ratio. The results that potential investors can get better information by reading the title of the analyst report. We hope that this study could be the basis for new methodologies in this area.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.50
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• pp.105-125
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• 1999

The results of analysis on foreign exchange market, stock and financial market after January of 1997 are that foreign exchange market will be affected by stock and financial market volatility about 1999. This means that stock and financial market are more stable than foreign exchange market. This also is supported by ‘financial market forecast of 1999 in Daewoo Economic Research Institute’. After won/dollar (end of period) will be increasing in 1,430 at second quarter of 1999, this is to downward 1,200 fourth quarter of 1999. This is somewhat based on government's higher exchange rate policy. But, after yield of corporate bond is to 11.0% at first quarter of 1999, this will be stable to 10.2% at fourth quarter. During the first quarter of 1999, yield of corporate bond is to somewhat increasing through sovereign debt and public bonds, technical adjustment of interest rate. After this, yield of corporate bond will be stable according to stability of price, magnification of money supply, restucturing of firms. So, stock market is favorably affected by stability of financial market. But, the pension and fund of USA, i.e., long-term portfolio investment fund, are injected through international firm's management. It is included by openness of audit, fair market about foreign investors. Finally, Moody's strong rating on the won-denominated bonds suggest that Korea's sovereign debt ratings could be restored to an investment grade in the near future. It sequentially includes inflow of foreign portfolio investment fund, fall of won/dollar foreign exchange rate (appreciation of won) and stability of yield of corporate bond.

• Management & Information Systems Review
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• v.12
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• pp.137-160
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• 2003

The association between accounting earnings and the stock price of an entity is the subject that has been most heavily researched during the past 25 years in accounting literature. Researcher's common finding is that there are positive relationships between accounting earnings and stock prices. However, the explanatory power of accounting earnings which was measured by $R^2$ of regression functions used was rather low. To be connected with these low results, The prior studies propose that there will be additional information, errors in variables. This study investigates empirically determinants of earnings response coefficients(ERCs), which measure the correlation between earnings and stock prices, using earnings level / change, as the dependent variable in the return/earnings regression. Specifically, the thesis tests whether the factors such as earnings persistence, growth, systematic risk, image, information asymmetry and firm size. specially, the determinable variables of ERC are explained in detail. The image / information asymmetry variables are selected to be connected with additional information stand point, The debt / growth variables are selected to be connected with errors in variables. In this study, The sample of firms, listed in Korean Stock Exchange was drawn from the KIS-DATA and was required to meet the following criteria: (1) Annual accounting earnings were available over the 1986-1999 period on the KIS-FAS to allow computation of variables parameter; (2) sufficient return data for estimation of market model parameters were available on the KIS-SMAT month returns: (3) each firm had a fiscal year ending in December throughout the study period. Implementation of these criteria yielded a sample of 1,141 firm-year observation over the 10-year(1990-1999) period. A conventional regression specification would use stock returns(abnormal returns) as a dependent variable and accounting earnings(unexpected earnings) changes interacted with other factors as independent variables. In this study, I examined the relation between other factors and the RRC by using reverse regression. For an empirical test, eight hypotheses(including six lower-hypotheses) were tested. The results of the performed empirical analysis can be summarized as follows; The first, The relationship between persistence of earnings and ERC have significance of each by itself, this result accord with one of the prior studies. The second, The relationship between growth and ERC have not significance. The third, The relationship between image and ERC have significance of each by itself, but a forecast code doesn't present. This fact shows that image cost does not effect on market management share, is used to prevent market occupancy decrease. The fourth, The relationship between information asymmetry variable and ERC have significance of each by. The fifth, The relationship between systematic risk$(\beta)$ and ERC have not significance. The sixth, The relationship between debt ratio and ERC have significance of each by itself, but a forecast code doesn't present. This fact is judged that it is due to the effect of financial leverage effect and a tendency of interest.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.49
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• pp.43-57
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• 1999

The recent trend is that risk management has more and more its importance. Neverthless, Korea's risk management is not developed. Even most banks does gap, duration in ALM for risk management, development and operation of VaR stressed at BIS have elementary level. In the case of Fallon and Pritsker, Marshall, gamma model is superior to delta model and Monte Carlo Simulation is improved at its result, as sample number is increased. And, nonparametric model is superior to parametric model. In the case of Korea's stock portfolio, VaR of Monte Carlo Simulation and Full Variance Covariance Model is less than that of Diagonal Model. The reason is that VaR of Full Variance Covariance Model is more precise than that of Diagonal Model. By the way, in the case of interest rate, result of monte carlo simulation is less than that of delta-gamma analysis on 95% confidence level. But, result of 99% is reversed. Therefore, result of which method is not dominated. It means two fact at forecast on volatility of stock and interest rate portfolio. First, in Delta-gamma method and Monte Carlo Simulation, assumption of distribution affects Value at Risk. Second, Value at Risk depends on test method. And, if option price is included, test results will have difference between the two. Therefore, If interest rate futures and option market is open, Korea's findings is supposed to like results of other advanced countries. And, every banks try to develop its internal model.