• Journal of Korean Society of Forest Science
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• v.40 no.1
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• pp.19-24
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• 1978

The study was conducted to find out the relationship between land cost and financial yield earned by the plantations of Pinus koraiensis, Pinus densiflora and Cryptomeria japonica, and to investigate possible land investment for the given rates of return. The result of the study could be summarized as follows: 1. In the case of Pinus koraiensis plantation on site index 12, the finnancial yield was 6.4 percent when the land cost was 0.5 million Won per hectare, but the yield was reduced to 2.1 percent when the cost was 2.5 million Won. It would be therefore necessary for inducing plantation investment to raise financial yield by control of forest land price. 2. The financial yield on land of zero expectation value, in other words, internal rate of return of land investment was estimated at 10 percent. If the opportunity cost of forest land is higher than this, the economic plantation is not visible even though the land is free. 3. With the expected financial yield of 3 percent, the possible land investment of poor sites was estimated at 1.24, 0.28 and 0.80 million Won per hectare for the plantation of Pinus koraiensis, Pinus densiflora and Cryptomeria japonica, respectively. In any case, however, land cost could not be over 3 million Won per hectare. 4. The rate earned from forest land investment was generally less than 10 percent. Therefore, the annual interest rate in forestry could not be higher than this, and hopeful rate is not exceeding 6 percent.

• Communications for Statistical Applications and Methods
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• v.15 no.6
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• pp.925-937
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• 2008

In this study, we considered the clustering analysis for stock return traded in the stock market. Most of financial time-series data, for instance, stock price and exchange rate have conditional heterogeneous variability depending on time, and, hence, are not properly applied to the autoregressive moving-average(ARMA) model with assumption of constant variance. Moreover, the variability is font and center for stock investors as well as academic researchers. So, this paper focuses on the generalized autoregressive conditional heteroscedastic(GARCH) model which is known as a solution for capturing the conditional variance(or volatility). We define the metrics for similarity of unconditional volatility and for homogeneity of model structure, and, then, evaluate the performances of the metrics. In real application, we do clustering analysis in terms of volatility and structure with stock return of the 11 Korean companies measured for the latest three years.

• Journal of Navigation and Port Research
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• v.41 no.2
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• pp.71-78
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• 2017

This paper aims to investigate the time-varying systematic risk of the stocks of Korean logistics firms. For this purpose, the period from January 1991 to October 2016 was examined with respect to 21 logistics companies that are listed on the Korea Exchange. The systematic risk of the logistics stocks is measured in terms of the Capital Asset Pricing Model (CAPM) beta for which the sensitivity of a stock is compared to the return changes of the whole market. Overall, the betas of the stocks of the Korean logistics companies are significantly lower than those of the market unity; however, it was revealed that the logistics betas are not constant, but are actually time-varying according to different economic regimes, which is consistent with the previous empirical findings. This finding is robust across different measurements of the logistics betas. In addition, the impact of macroeconomic factors on the logistics betas was examined. The present study shows that the logistics betas are positively associated with foreign exchange-rate changes.

• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.239-246
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• 2021

Unification means the change of the economic system from 'Planned Economy' of the North Korea to 'Market Economy' of the South Korea. Therefore, it may cause confusions and difficulties for North Koreans who have been under planned economy for ages. So, we need to take the perspective of behavioral economics for the effective education. First of all, it is about overall finance, which contains the record of financial transactions, effect of inflation, investors' bounded rationality, and choice difficulty of financial products. Second, it is about borrowings, which includes the credit management, interest rate of difference among financial institutions. Third, it is about investment on financial products, which includes the effect of cost on returns, difference between compound interest and simple interest, trade-off between expected return and risk, market and non-market risks, the importance of diversification, and passive & aggressive investments.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.4
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• pp.63-71
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• 2009

The traditional portfolio optimization problem is to find an investment plan for securities with reasonable trade-off between the rate of return and the risk. The seminal work in this field is the mean-variance model by Markowitz, which is a quadratic programming problem. Since it is now computationally practical to solve the model, a number of alternative models to overcome this complexity have been proposed. In this paper, among the alternatives, we focus on the Mean Absolute Deviation (MAD) model. More specifically, we developed an algorithm to obtain an optimal portfolio from the MAD model. We showed mathematically that the algorithm can solve the problem to optimality. We tested it using the real data from the Korean Stock Market. The results coincide with our expectation that the method can solve a variety of problems in a reasonable computational time.

• The Korean Journal of Financial Management
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• v.24 no.4
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• pp.75-106
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• 2007

In this study, it is analyzed whether oil price plays a major role in the pricing return on Koran stock market and examined why the covariance risk between oil and return on stock is different in each industry. Firstly, this study explores whether the expected rate of return on stock is pricing due to global oil price factors as a function of risk premium by using a two-factor APT. Also, it is examined whether spill-over effects of oil price volatility affect the beta risk to oil price. Considering the asymmetry of oil price volatility, we use the GJR model. As a result, it shows that oil price is an independent pricing factor and oil price volatility transmits to stock return in only electricity and electrical equipment. Secondly, the two step-analyzing process is introduced to find why the covariance between oil price factor and stock return is different in each industry. The first step is to study whether beta risk exists in each industry by using two proxy variables like size and liquidity as control variables. The second step is to grasp the systematic relationship between the difference of liquidity and size and beta to oil price factor by using the panel-data model which can be analyzed efficiently using the cross-sectional data formed with time series. Through the analysis, we can argue that oil price factor is an independent pricing factor in only electricity and electrical equipment having the greatest market capitalization, and know that beta risk to oil price factor is a proxy of size in the other industries. According to the result of panel-data model, it is argued that the beta to oil price factor augments when market capitalization increases and this fact supports the first assertion. In conclusion, the expected rate of return of electricity and electrical equipment works as a function of risk premium to market portfolio and oil price, and the reason to make beta risk power differentiated in each industry attributes to the size.

• Journal of Navigation and Port Research
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• v.43 no.4
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• pp.264-272
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• 2019

In this study, the rate of return on investment used as a proxy variable for the entity's value and financial structure (liability ratio) is related to positive balance. This is consistent with the Static Tradeoff Theory (STT) that the entity's value and financial structure are related to a positive balance because the capital expense of a debt (tax-saving effects) that is less than its equity cost before it is in financial difficulty. Also, operating profitability (EBITDA/Sales), investment safety, total asset growth, net working capital and depreciation expenses are related to negative (-) with financial structure (liability ratio). This is the result of an analysis consistent with the Pecking Order Theory (POT). Fuel costs, borrowing, total asset turnover, financial costs, and tangible asset ratios have a significant positive relationship with the debt ratio. This is consistent with the agency theory and confirms that excessive chartering expenses, such as the bankrupt H company, are the main factors that pressure the financial structure of Korean ocean carriers.

• Journal of the Korea Convergence Society
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• v.12 no.6
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• pp.9-16
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• 2021

In the past, there have been various studies on predicting the stock market by machine learning techniques using stock price data and financial big data. As stock index ETFs that can be traded through HTS and MTS are created, research on predicting stock indices has recently attracted attention. In this paper, machine learning models for KOSPI's up and down predictions are implemented separately. These models are optimized through a grid search of their control parameters. In addition, a hybrid machine learning model that combines individual models is proposed to improve the precision and increase the ETF trading return. The performance of the predictiion models is evaluated by the accuracy and the precision that determines the ETF trading return. The accuracy and precision of the hybrid up prediction model are 72.1 % and 63.8 %, and those of the down prediction model are 79.8% and 64.3%. The precision of the hybrid down prediction model is improved by at least 14.3 % and at most 20.5 %. The hybrid up and down prediction models show an ETF trading return of 10.49%, and 25.91%, respectively. Trading inverse×2 and leverage ETF can increase the return by 1.5 to 2 times. Further research on a down prediction machine learning model is expected to increase the rate of return.

• Land and Housing Review
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• v.6 no.3
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• pp.117-127
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• 2015

Korean government has launched a new public rental housing policy for younger generation suffering from instable housing conditions in CBD area. This paper is to analyze the financial feasibility of urban public rental housing projects, based on its cash flows. Urban rental housing projects should find out the way to reduce costs and to secure cheap land, because of the high land price in CBD area and complex relationship of legal rights. Project types are categorized by the land acquisition method and district characteristics. For 10 sample projects, financial feasibility was analyzed. Cash flows were calculated on the design plan and 16 scenarios were made by combining 4 important variables. The variables are increase rate of land price, increase rate of monthly rents, ratio of public and market rents, and the interest rate of National Housing Fund. The findings are as follows. Government land rent-type can reduce initial costs because it is not necessary to buy land. However, total NPV is lowered at the time of liquidation due to the land return. Private land acquisition-type require more initial costs. But the NPV at liquidation time increases with land disposal. To improve financial feasibility, acquisition-type should be preferred in high land-price area and rent-type should be preferred in low land-price area. Among influencing variables, the rate of increase in land price and the ratio of public and market rents turned out to be the most important. Although the ratio of public and market rents can be controllable, high ratio will cause the burden of tenants. Therefore, interest rate adjustment of National Housing Fund is more desirable.

• Korean Chemical Engineering Research
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• v.47 no.1
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• pp.127-132
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• 2009

This report examines the economic feasibility of a commercial 50,000 barrel per day direct coal liquefaction(DCL) facility to produce commercial-grade diesel and naphtha liquids from medium-sulfur bituminous coal. The scope of the study includes capital and operating cost estimates, sensitivity analysis and a comparative financial analysis. Based on plant capacity of 50,000BPD, employing Illinois #6 bituminous coal as feed coal the total capital cost appeared $3,994,858,000. Also, the internal rate of return of DCL appeared 6.60% on the base condition. In this case, coal price and sale price of products were the most influence factors. And DCL's payback period demanded a long time(12.3 years), because of high coal price at the present time. According to sensitivity analyses, the important factors on DCL processes were product sale price, feed coal price and the capital cost in order.