• The Journal of Fisheries Business Administration
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• v.44 no.2
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• pp.1-17
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• 2013

We investigate the appropriateness of the fixed 12% discount rate to be used in estimating the amount of compensation for revoking a license for fishery business by the Enforcement Decree of Fisheries Act in Korea. We also suggest the appropriate discount rate fully reflecting the change of market interest rate in the Korean financial market. The capital asset pricing model, or, CAPM is the best known model of risk and return, and is widely used to estimate the expected rate of return for the risky projects. Even though the CAPM implies that the discount rate or the expected rate of return should change as the related market factors do, the discount rate used to estimate compensation for revoking a license for fishery business remains to be the same 12% rate for the last 15 years by law. During this period, however, the yield to maturity for the 5-year government bonds in Korea has dramatically changed from about 12% to less than 3%. In order to provide the fair compensation for the damages against the coastal fisheries and evaluate the intrinsic value of fishery resources in the coastal areas, we suggest that the appropriate discount rate should be determined by the yield to maturity of the government bonds with 5-year maturity, instead of the current fixed 12% interest rate.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.11a
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• pp.417-426
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• 2000

This study suggests integrated neural network models for Interest rate forecasting using change-point detection, classifiers, and classification functions based on structural change. The proposed model is composed of three phases with tee-staged learning. The first phase is to detect successive and appropriate structural changes in interest rare dataset. The second phase is to forecast change-point group with classifiers (discriminant analysis, logistic regression, and backpropagation neural networks) and their. combined classification functions. The fecal phase is to forecast the interest rate with backpropagation neural networks. We propose some classification functions to overcome the problems of two-staged learning that cannot measure the performance of the first learning. Subsequently, we compare the structured models with a neural network model alone and, in addition, determine which of classifiers and classification functions can perform better. This article then examines the predictability of the proposed classification functions for interest rate forecasting using structural change.

• The Journal of Asian Finance, Economics and Business
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• v.3 no.3
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• pp.57-65
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• 2016

The purpose of this paper is to investigate the volatility of both Islamic and conventional stock market in Indonesia with the aim of identifying the most appropriate model for risk management practice. The study considers GARCH as a genre of model to measure the volatility of stock market movement. The results support the view that each model shows specific volatility from both Islamic and conventional stock market in Indonesia. In Islamic stock market, volatility is affected by exchange rate and money supply (M1) but not interest rate as interest is prohibited in Islam. However, interest rate is found as a principal factor that affects volatility of conventional stock market. The outcomes of this paper are of particular significance to policy makers, as it provides guidelines to maintain economic health. Furthermore, the findings may assist practitioners to understand the consequences of macroeconomic factors such as exchange rate, money supply and interest rate, which are very crucial for the market stability of Indonesian stock market. The paper enhances the understanding of stock market volatility and proposes guidelines risk management practices.

• The Korean Journal of Financial Management
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• v.20 no.2
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• pp.73-94
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• 2003

In general, the interest rate is forecasted by the parametric method which assumes the interest rate follows a certain distribution. However the method has a shortcoming that forecasting ability would decline when the interest rate does not follow the assumed distribution for the stochastic behavior of interest rate. Therefore, the nonparametric method which assumes no particular distribution is regarded as a superior one. This paper compares the interest rate forecasting ability between the two method for the Monetary Stabilization Bond (MSB) market in Korea. The daily and weekly data of the MSB are used during the period of August 9th 1999 to February 7th 2003. In the parametric method, the drift term of the interest rate process shows the linearity while the diffusion term presents non-linear decline. Meanwhile in the nonparametric method, both drift and diffusion terms show the radical change with nonlinearity. The parametric and nonparametric methods present a significant difference in the market price of interest rate risk. This means in forecasting the interest rate and the market price of interest rate risk, the nonparametric method is more appropriate than the parametric method.

• Journal of Arbitration Studies
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• v.31 no.1
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• pp.55-81
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• 2021

Awarding interest in international arbitration remains one of the most challenging areas for tribunals and parties given the myriad of issues that arise. This article seeks to provide an overview of how international arbitral tribunals grant delay interest. It reviews the various issues that international arbitral tribunals face concerning pre-award and post-award interest, determining the appropriate interest rate, surrounding simple or compound interest, and the complex issue of choice of law. A comparative context is provided by surveying the laws of major jurisdictions from both the common law and civil law and the regulations of leading arbitral institutions. It concludes with a review of the law, jurisprudence, and practice in Korea related to delay interest and how Korean tribunals under the KCAB Domestic and International Rules have determined delay interest in recent years.

• Journal of Distribution Science
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• v.11 no.10
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• pp.63-72
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• 2013

Purpose - This study analyzes the relationship and dynamic interactions between stock price index, interest rate, price index, and housing price indices using Korean monthly data from 2000 to 2013, based on a VAR model. This study also examines Granger causal relationships among these variables in order to determine whether the time series of one is useful in forecasting another, or to infer certain types of causal dependency between stochastic variables. Research design, data, and methodology - We used Korean monthly data for all variables from 2000: M1 to 2013: M3. First, we checked the correlations among different variables. Second, we conducted the Augmented Dickey-Fuller (ADF) test and the co-integration test using the VAR model. Third, we employed Granger Causality tests to quantify the causal effect from time series observations. Fourth, we used the impulse response function and variance decomposition based on the VAR model to examine the dynamic relationships among the variables. Results - First, stock price Granger affects interest rate and all housing price indices. Price index Granger, in turn, affects the stock price and six metropolitan housing price indices. However, none of the Granger variables affect the price index. Therefore, it is the stock markets (and not the housing market) that affects the housing prices. Second, the impulse response tests show that maximum influence on stock price is its own, and though it is influenced a little by interest rate, price index affects it negatively. One standard deviation (S.D.) shock to stock price increases the housing price by 0.08 units after two months, whereas an impulse shock to the interest rate negatively impacts the housing price. Third, the variance decomposition results report that the shock to the stock price accounts for 96% of the variation in the stock price, and the shock to the price index accounts for 2.8% after two periods. In contrast, the shock to the interest rate accounts for 80% of the variation in the interest rate after ten periods; the shock to the stock price accounts for 19% of the variation; however, shock to the price index does not affect the interest rate. The housing price index in 10 periods is explained up to 96.7% by itself, 2.62% by stock price, 0.68% by price index, and 0.04% by interest rate. Therefore, the housing market is explained most by its own variation, whereas the interest rate has little impact on housing price. Conclusions - The results of the study elucidate the relationship and dynamic interactions among stock price index, interest rate, price index, and housing price indices using VAR model. This study could help form the basis for more appropriate economic policies in the future. As the housing market is very important in Korean economy, any changes in house price affect the other markets, thereby resulting in a shock to the entire economy. Therefore, the analysis on the dynamic relationships between the housing market and economic variables will help with the decision making regarding the housing market policy.

• International Area Studies Review
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• v.13 no.1
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• pp.3-16
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• 2009

This paper investigates the existence of uncovered interest rate parity between the Korea-USA as well as the Korea-Japan. We may ascertain the existence of uncovered interest rate parity by examining the empirical relationship between real exchange rates and interest rate differentials in the Korea-USA as well as in the Korea-Japan. The empirical relationship between real exchange rates and interest rate differentials in the Korean-USA and Korean-Japanese economies is investigated using cointegration tests. In the context of this study, cointegration technique is appropriate to examine the relationship between two(or more) nonstationary time series. Also, this method is useful to detect the possibility that the nonstationarity in both series can be explained by a single factor. The empirical results support the nonexistence of a long run equilibrium relation between real exchange rates and interest rate differentials. Also, the results show that the nonstationarity cannot be explained by a single factor.

• Communications for Statistical Applications and Methods
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• v.29 no.1
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• pp.85-101
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• 2022

Derivative-linked securities (DLS) is a type of derivatives that offer an agreed return when the underlying asset price moves within a specified range by the maturity date. The underlying assets of DLS are diverse such as interest rates, exchange rates, crude oil, or gold. A German 10-year bond rate-linked DLS and a USD-GBP CMS rate-linked DLS have recently become a social issue in Korea due to a huge loss to investors. In this regard, this paper accounts for the payoff structure of these products and evaluates their prices and fair coupon rates as well as risk measures such as Value-at-Risk (VaR) and Tail-Value-at-Risk (TVaR). We would like to examine how risky these products were and whether or not their coupon rates were appropriate. We use Hull-White Model as the stochastic model for the underlying assets and Monte Carlo (MC) methods to obtain numerical results. The no-arbitrage prices of the German 10-year bond rate-linked DLS and the USD-GBP CMS rate-linked DLS at the center of the social issue turned out to be 0.9662% and 0.9355% of the original investment, respectively. Considering that Korea government bond rate for 2018 is about 2%, these values are quite low. The fair coupon rates that make the prices of DLS equal to the original investment are computed as 4.76% for the German 10-year bond rate-linked DLS and 7% for the USD-GBP CMS rate-linked DLS. Their actual coupon rates were 1.4% and 3.5%. The 95% VaR and TVaR of the loss for German 10-year bond rate-linked DLS are 37.30% and 64.45%, and those of the loss for USD-GBP CMS rate-linked DLS are 73.98% and 87.43% of the initial investment. Summing up the numerical results obtained, we could see that the DLS products of our interest were indeed quite unfavorable to individual investors.

• Journal of Navigation and Port Research
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• v.44 no.2
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• pp.119-127
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• 2020

In this study, the current state of management efficiency of ocean carriers in Korea and the factors affecting them were analyzed. The purpose of this research is to enhance global competitiveness of ocean carriers by presenting suggestions that can improve management efficiency based on the analysis results. The measurement of management efficiency was made using the DEA model. The results of testing the adequacy of the input and output variables used are as follows. Appropriate inputs are total assets, cost of goods sold, charter expenses, sales and general management expenses, and interest expenses. Appropriate variables are sales, operating income, and operating cash flow. According to the analysis results of the DEA model by these variables, inefficient carriers (78%) are nearly four times more than efficient carriers(22%). However, container carriers have the most improved management efficiency compared to 2016 and 2017. According to the panel regression analysis, the charter rate has the greatest negative impact on efficiency (CRS), and the debt rate has a significant negative impact. Thus, it appears that reducing the charter size and the debt-to-sale rate facilitate improvement of the management efficiency of ocean carriers. Additionally, the pre-sales tax return rate, value added rate, total asset turnover rate, and the scale variable and interest coverage rate have a positive (+) effect. Thus ocean carriers should restore their global competitiveness by improving management efficiency by securing stable cargoes increasing sales profitability from the cost management perspective, increasing productivity, and enhancing the efficiency of their total assets through efficient fleet management.

• Magazine of the Korean Society of Agricultural Engineers
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• v.40 no.3
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• pp.83-92
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• 1998

Field experiment was performed from August 1996 to January 1998 to examine the applicability of constructed wetland system for wastewater treatment in rural area. The pilot plant was installed in Kon-Kuk University and the school building septic tank effluent was used as an influent to the treatment basin. Hydraulic loading rate was about 0.1 6$0.16^3/m^2$ day and theoretical detention time in the system was 1.38 days. The treatment basin was composed of sand and reed. The influent DO concentration was low and many cases close to zero, but effluent concentration was higher than the influent which implies that oxygen was supplied naturally. The average concentration of influent BOD was 126mg/L, and with average removal rate of 69 % the average effluent concentration was 4Omg/L which satisfied the effluent water quality standard for the system of interest. The average influent concentration of COD was 2Olmg/L and average effluent concentration was 75mg/L with average removal rate of 60%. The performance of BOD and COD tends to deteriorate in the low temperature, and appropriate action needs to be taken during the cold winter time for stable operation. The average influent concentration of SS was 5Omg/L, and effluent was 1 1mg/L with average removal rate of 76% which satisfied the effluent water quality standard for the system of interest. The results for the regulated components, SOD and SS, from the experiment showed that constructed wetland system can meet the effluent water quality standards. The average influent concentration of total phosphorus was 25.6mg/L and average effluent concentration was 7.8mg/L with average removal rate of 63%. Not like the performance of the above components, average nitrogen removal rate was only 11.2% which is not satisfactory. Although, nitrogen is not regulated at this moment, it can cause many environmental problems including eutrophication. Therefore, nitrogen removal efficiency should be improved for actual application. From the result of the field experiment, constructed wetland system was thought to be an appropriate alternative for wastewater treatment in rural area.