• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.833-840
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• 2021

This paper examines the effect of the interest rate set by Bank Indonesia on financial system stability as measured by the credit gap in Indonesia for quarterly data for the period 1976 Q1 to 2019 Q4. We suppose that the relationship between the Central Bank rate and the credit gap is non-linear. Hence, this study applies a smooth transition regression (STR) model to investigate the relationship between these variables. Our results are: first, by performing STR estimation we obtained a threshold level of Central Bank rate of 2.01. Second, a decrease in the Central Bank rate results in a reduction in the credit gap when the Central Bank rate is above or below the threshold level. The effect of the Central Bank rate is five times greater for the high regime than for the low regime. Third, we find evidence that the effect of the exchange rate, economic growth, inflation, and GDP per capita on the credit gap for the high regime is the opposite of the low regime. We suggest that policymakers need to keep the Central Bank interest rate low and stable so that the role of the bank as a financial intermediary remains stable and conducive to strengthening financial stability.

• Korean Journal of Agricultural Science
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• v.30 no.1
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• pp.89-101
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• 2003

For the pre-feasibility study and project evaluation, the discount rate or cutoff rate should be given by the government authority. To get the Benefit/Cost Ratio, NPV(Net Present Value) and IRR(Internal Rate of Return) of the public investment projects, the pertinent and realistic discount rate should be determined to be suitable to the present time period. The cut-off rates in Korea were equivalent to 15% in 1970's, 10% in 1980's and 8% in 1990's. The prevailing rate of discount as 8% is considered not to be suitable for the 2000's public project appraisal considering the present interest rates on deposit and national bonds. To determine the socio-economic feasibility of the public projects, the IRR should be bigger than the present cutoff rate. When we still use the high old rate of discount, the analytical results of project appraisal will show always economically unfeasible. Therefore the new rate of discount suitable for present time should be determined by the government. The public projects to be implemented in 2000 year onward are recommended to be adapted 5% of cutoff rate for the project appraisal and evaluation according to the results of reviewing the tendency of discount rates and market rates of interest in Korea.

• East Asian Economic Review
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• v.24 no.2
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• pp.165-184
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• 2020

Applying Ismailov and Rossi (2018), I newly construct the Korea FX uncertainty based on the density distribution of historical forecast errors. This uncertainty index properly captures the rare but significant events in the Korean currency market and provides information distinct from other uncertainty measures in recent studies. I show that 1) FX uncertainty arising from unexpected depreciation has a stronger impact on Korea-U.S. exchange rates and that 2) macro variables, such as capital flows or interest rate differentials, have predictive ability regarding Korea FX uncertainty for short horizons. These findings enable us to predict the events of sudden currency crashes and understand the Korea-U.S. exchange rate dynamics.

• Knowledge Management Research
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• v.22 no.4
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• pp.71-85
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• 2021

The purpose of this study is to find out which artificial intelligence methodology is most suitable for creating a foreign exchange rate prediction model using the indicators of bond market and interest rate market. KTBs and MSBs, which are representative products of the Korea bond market, are sold on a large scale when a risk aversion occurs, and in such cases, the USD/KRW exchange rate often rises. When USD liquidity problems occur in the onshore Korean market, the KRW Cross-Currency Swap price in the interest rate market falls, then it plays as a signal to buy USD/KRW in the foreign exchange market. Considering that the price and movement of products traded in the bond market and interest rate market directly or indirectly affect the foreign exchange market, it may be regarded that there is a close and complementary relationship among the three markets. There have been studies that reveal the relationship and correlation between the bond market, interest rate market, and foreign exchange market, but many exchange rate prediction studies in the past have mainly focused on studies based on macroeconomic indicators such as GDP, current account surplus/deficit, and inflation while active research to predict the exchange rate of the foreign exchange market using artificial intelligence based on the bond market and interest rate market indicators has not been conducted yet. This study uses the bond market and interest rate market indicator, runs artificial neural network suitable for nonlinear data analysis, logistic regression suitable for linear data analysis, and decision tree suitable for nonlinear & linear data analysis, and proves that the artificial neural network is the most suitable methodology for predicting the foreign exchange rates which are nonlinear and times series data. Beyond revealing the simple correlation between the bond market, interest rate market, and foreign exchange market, capturing the trading signals between the three markets to reveal the active correlation and prove the mutual organic movement is not only to provide foreign exchange market traders with a new trading model but also to be expected to contribute to increasing the efficiency and the knowledge management of the entire financial market.

• The Transactions of the Korea Information Processing Society
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• v.13 no.4
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• pp.189-198
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• 2024

Lipreading is one of the important parts of speech recognition, and several studies have been conducted to improve the performance of lipreading in lipreading systems for speech recognition. Recent studies have used method to modify the model architecture of lipreading system to improve recognition performance. Unlike previous research that improve recognition performance by modifying model architecture, we aim to improve recognition performance without any change in model architecture. In order to improve the recognition performance without modifying the model architecture, we refer to the cues used in human lipreading and set other regions such as chin and cheeks as regions of interest along with the lip region, which is the existing region of interest of lipreading systems, and compare the recognition rate of each region of interest to propose the highest performing region of interest In addition, assuming that the difference in normalization results caused by the difference in interpolation method during the process of normalizing the size of the region of interest affects the recognition performance, we interpolate the same region of interest using nearest neighbor interpolation, bilinear interpolation, and bicubic interpolation, and compare the recognition rate of each interpolation method to propose the best performing interpolation method. Each region of interest was detected by training an object detection neural network, and dynamic time warping templates were generated by normalizing each region of interest, extracting and combining features, and mapping the dimensionality reduction of the combined features into a low-dimensional space. The recognition rate was evaluated by comparing the distance between the generated dynamic time warping templates and the data mapped to the low-dimensional space. In the comparison of regions of interest, the result of the region of interest containing only the lip region showed an average recognition rate of 97.36%, which is 3.44% higher than the average recognition rate of 93.92% in the previous study, and in the comparison of interpolation methods, the bilinear interpolation method performed 97.36%, which is 14.65% higher than the nearest neighbor interpolation method and 5.55% higher than the bicubic interpolation method. The code used in this study can be found a https://github.com/haraisi2/Lipreading-Systems.

• The Journal of Asian Finance, Economics and Business
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• v.4 no.1
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• pp.19-23
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• 2017

Based on a simultaneous-equation model consisting of aggregate demand and short-run aggregate supply, this paper estimates a reduced-form equation specifying that the equilibrium real GDP is a function of the real effective exchange rate, the government deficit as a percent of GDP, the real interest rate, foreign income, labor productivity, the real oil price, the expected inflation rate, and the interactive and intercept binary variables accounting for a potential change in the slope of the real effective exchange rate and shift in the intercept. Applying the exponential GARCH technique, it finds that aggregate output in Australia has a positive relationship with the real effective exchange rate during 2003.Q3 - 2013.Q2, the government deficit as a percent of GDP, U.S. real GDP, labor productivity and the real oil price and a negative relationship with the real effective exchange rate during 2013.Q3 - 2016.Q1, the real lending rate and the expected inflation rate. These results suggest that real appreciation was expansionary before 2013.Q3 whereas real depreciation was expansionary after 2013.Q2 and that more government deficit as a percent of GDP would be helpful to stimulate the economy. Hence, the impact of real appreciation or real depreciation on real GDP may change overtime.

• The Journal of Industrial Distribution & Business
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• v.9 no.6
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• pp.15-24
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• 2018

Purpose - The adjustment of one country's monetary policy can cause the macroeconomic change of other countries. Due to this, this paper attempts to analyze the impact of China's monetary policy on South Korea's exchange rate. Research design, data, and methodology - Based on the flexible-price monetary model, sets of annual time series from 1980 to 2017 are employed to perform an empirical estimation. The vector error correction model is also used to exploit the short-run relationship between both of them. Of course, the South Korea's real GDP, the China's real GDP, South Korea's interest rate, the South Korea's interest rate and the South Korea's monetary supply are treated as independent variables in this paper. Result - The long-run findings reveal that the China's money supply has a negative effect on South Korea's exchange rate. Respectively, the short-run findings depicts that the China's money supply has negative a effect on South Korea's exchange rate. Of course, other variables selected in this paper also have an effect on South Korea's exchange rate whatever positive or negative. Conclusions - As the empirical evidence shows, the China's monetary policy has a negative effect on South Korea's exchange rate whenever in the long run or in the short run.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.55
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• pp.155-181
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• 2012

This study considered as precautions in light of practical affairs related to a claim for damages focusing on CISG (1980) and PICC (2004). Given summarizing contents of this study, those are as follows. First, when exercising a claim for damages, proving the damages may be difficult and hard. Thus, there is necessity for stating the liquidated damages clause in contract given conclusion of contract. Second, as for the application of interest rate given a claim for interest, CISG is not covered interest rate. PICC is covered interest rate. However, there is possibility that PICC will not be applied as general principles. Thus, to remove this insecurity and uncertainty, there is necessity for stating this in contract by deciding on the detailed standard stipulation after fully discussing about interest payment with the counterpart given sale contract. Third, when a seller delivered non-conformity of the goods for contract, a buyer is desirable to exercise by discreetly judging the exercise method or limitation element on a problem of selecting and exercising remedy favorable to oneself out of a claim for damages and a right to reduce the price. Finally, There was suggestion that the contract parties are desirable to utilize by modifying and supplementing properly this in line with own business-based necessity and situation based on the ICC Model International Sale Contract, and to state CISG and PICC the governing law clause, in preparing contract. This study is expected to possibly become guideline in which the damaged party exercises a claim for damages or aims to cope with the counterpart's exercising a claim for damages.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.19-22
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• 1996

A traditional approach to the prediction of economic and financial variables takes the form of statistical models to summarize past observations and to project them into the envisioned future. Over the past decade, an increasing number of organizations has turned to the use of neural networks. To date, however, many spheres of interest still lack a systematic evaluation of the statistical and neural approaches. One of these lies in the prediction of corporate bond yields for Korea. This paper reports on a comparative evaluation of ARIMA models and neural networks in the context of interest rate prediction. An additional experiment relates to an integration of the two methods. More specifically, the statistical model serves as a filter by providing estimtes which are then used as input into the neural network models.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.20 no.4
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• pp.277-293
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• 2016

We develop an efficient numerical method for pricing the Derivative Linked Securities (DLS). The payoff structure of the hybrid DLS consists with a standard 2-Star step-down type ELS and the range accrual product which depends on the number of days in the coupon period that the index stay within the pre-determined range. We assume that the 2-dimensional Geometric Brownian Motion (GBM) as the model of two equities and a no-arbitrage interest model (One-factor Hull and White interest rate model) as a model for the interest rate. In this study, we employ the Monte Carlo simulation method with the Compute Unified Device Architecture (CUDA) parallel computing as the General Purpose computing on Graphic Processing Unit (GPGPU) technology for fast and efficient numerical valuation of DLS. Comparing the Monte Carlo method with single CPU computation or MPI implementation, the result of Monte Carlo simulation with CUDA parallel computing produces higher performance.