• Communications for Statistical Applications and Methods
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• v.14 no.1
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• pp.241-254
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• 2007

This paper propose a new short-term interest rate model having a different nonlinear drift function and the same diffusion coefficient with Chan et al. (1992) model. The fractional polynomial power of the drift function in our model is linked to the local volatility elasticity of the diffusion coefficient. While the nonlinear drift function estimated by $A\"{\i}t$-Sahalia (1996a) and others has a feature that higher interest rates tend to revert downward and low rates upward, the drift function estimated by our nonlinear model shows that higher interest rate mean-reverts strongly, but, medium rates has almost zero drift and low rates has a very small drift. This characteristic coincides the empirical result based on the nonparametric methodology by Stanton (1997) and the implication by the scatter plot of the short rate data.

• The Journal of the Convergence on Culture Technology
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• v.4 no.4
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• pp.155-160
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• 2018

The article studies the effect of US real effective exchange rate and short-term interest rate on Chnise exports and imports using the EGARCH-GED model. This article analyze the effect of US major economic variables on China's exports and imports as the US pushes for interest rate hikes and worsens trade wars with China. The main results are as follows. The US short-term interest rate has a significant positive effect on China's trade volume. Even in the case of China's exports, US short-term interest rate has a significant positive effect. However, in the case of China's imports, in contrast to exports, US short-term interest rate do not have a significant effects and US real effective exchange rate has a significant positive effect. On the other hand, China's policy interest rate has a negative impact on China's imports and not statistically significant, but it has a significant positive effect on China's exports.

• Journal of the Chungcheong Mathematical Society
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• v.34 no.2
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• pp.157-168
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• 2021

This study uses the benchmark interest rate of the Federal Open Market Committee (FOMC) to predict gold futures prices. For the predictions, we used the support vector machine (SVM) (a machine-learning model) and the long short-term memory (LSTM) deep-learning model. We found that the LSTM method is more accurate than the SVM method. Moreover, we applied the Boruta algorithm to demonstrate that the FOMC benchmark interest rates correlate with gold futures.

• KDI Journal of Economic Policy
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• v.31 no.2
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• pp.15-45
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• 2009

This paper estimates the term structure of interest rates with the setup of 3-factor no arbitrage model and investigates the trend of term premia and the effectiveness of changes in policy interest rates. The term premia are found to be high in a three-year medium term objective, which can be interpreted as reflecting the recognition of investors who expect a higher uncertainty in real activities for the coming three years than for a longer term. Then, in order to look into the effect of policy interest rates after the recent change of benchmark interest rate, this paper analyzes the effects of the changes in short-term interest rates of the financial market on the yield curve of the bond market at time of change. Empirical results show that the discrepancy between call rate, short-term rate in money market, and instantaneous short rate, short-term rate in the bond market, is found to be significantly widened, comparing to the periods before the change in benchmark interest rate. It is not easy to conclude clearly for now whether such a widening gap is caused by the lack of experiences with managing new benchmark interest rate or is just an exceptional case due to the recent turmoil in the global financial market. However, monetary policy needs to be operated in a manner that could reduce the gap to enhance its effectiveness.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.6
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• pp.676-686
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• 2016

This study analyzed the long term relationship between the K-REITs' lending rate and interest rate variables based on ARDL (autoregressive distributed lag) and also examined the short term relationship based on the ARDL-ECM model. In the results of the empirical test, there is a co-integration relationship among the K-REITs' lending rate, 3 year government bond (rate), 3 year government bond (rate), corporation bond (rate) (AA-, 3year) and general fund loan rate. This means that the K-REITs' lending rate is related to the long term interest rate. The corporate general fund loan rate has a significant correlation with the K-REITs' lending rate in the long term relation and short term adjustment process. The establishment of a management plan by the REITs considering the trends in the corporate general fund loan rate in the decision making process for finance sector borrowings can be practically helpful for the K-REITs.

• The Journal of Industrial Distribution & Business
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• v.11 no.8
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• pp.31-38
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• 2020

Purpose: This study uses 'Autoregressive Integrated Moving Average Model' to predict the impact of a sharp drop in the base rate due to COVID-19 at the present time when government policies for stabilizing house prices are in progress. The purpose of this study is to predict implications for the direction of the government's house policy by predicting changes in house transaction prices and house rental prices after a sharp cut in the base rate. Research design, data, and methodology: The ARIMA intervention model can build a model without additional information with just one time series. Therefore, it is a time-series analysis method frequently used for short-term prediction. After the subprime mortgage, which had shocked since the global financial crisis in April 2007, the bank's interest rate in 2020 is set at a time point close to zero at 0.75%. After that, the model was estimated using the interest rate fluctuations for the Bank of Korea base interest rate, the house transaction price index, and the house rental price index as event variables. Results: In predicting the change in house transaction price due to interest rate intervention, the house transaction price index due to the fall in interest rates was predicted to change after 3 months. As a result, it was 102.47 in April 2020, 102.87 in May 2020, and 103.21 in June 2020. It was expected to rise in the short term. In forecasting the change in house rental price due to interest rate intervention, the house rental price index due to the drop in interest rate was predicted to change after 3 months. As a result, it was 97.76 in April 2020, 97.85 in May 2020, and 97.97 in June 2020. It was expected to rise in the short term. Conclusions: If low interest rates continue to stimulate the contracted economy caused by COVID-19, it seems that there is ample room for house transaction and rental prices to rise amid low growth. Therefore, In order to stabilize the house price due to the low interest rate situation, it is considered that additional measures are needed to suppress speculative demand.

• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.655-663
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• 2003

The fundamental tenn structure model is based on the modelling of the short rate. It is well-known that the short rate depends on the interest rate policy of monetary authorities, especially on the official rate. Babbs and Webber(1994) modelled the tenn structure of interest rates using the official rate. They assume that the official rate follows a jump process. This reflects that the official rate infrequently changes. In this paper, we test this official tenn structure model and compare the jump-diffusion model with the pure diffusion model.

• Proceedings of the Korean Statistical Society Conference
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• 2005.05a
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• pp.179-184
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• 2005

Empirical findings on interet rate dynamics imply that short rates show some long memories and non-Markovin. It is well-known that fractional Brownian motion(fBm) is a proper candidate for modelling this empirical phenomena. fBm, however, is not a semimartingale process. For this reason, it is very hard to apply such processes for asset price modelling. With some modifications, this paper investigate the fBm interest rate theory, and obtain a pure discount bond price and Greeks.

• Korea Trade Review
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• v.42 no.4
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• pp.49-68
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• 2017

This paper investigates the spillover effect of the U.S. Interest on Korea's interest rate as well as the role of exchange rate in the spillover effects, by utilizing a open macro model on the determinants of long-term interest rates. According to the cointegration estimation and the Impulse response function, it is found that, across both long-term and short-term, there exist the spillover effect of the U.S. Interest on Korea's interest rate. The fiscal deficit and expected exchange rate have significantly positive relationship with the Koreas's long-term interest rate. Further, foreign exchange market intervention in Korea did not have significant effect on the spillover effect. Thus, this study suggests that exchange rate flexibility would not be enough to restrain the spillover effects of the U.S. interest rate.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.647-654
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• 2021

This study examines the non-performing loans of rural banks and macroeconomic factors in Indonesia, including inflation, exchange rates, and interest rates. Theoretically, the existence of erratic macroeconomic conditions can affect the level of non-performing credit risk in rural credit banks in Indonesia. The effect of macroeconomic conditions on non-performing loans has a different response for each economic sector. The main objective of this study is to determine the effect of macroeconomic factors (inflation, exchange rates, and interest rates) and bank-specific factors (credit) on the Non-Performing Loans (NPL) of Rural Banks in Indonesia for the period from January 2015 to December 2018. This study uses a Vector Error Correction Model (VECM) estimation to determine the effect of independent variables consisting of macroeconomic factors and bank-specific factors. Based on the estimation results of the Vector Error Correction Model, three variables that have a positive and significant effect on long-term non-performing loans are credit, inflation, and interest rates. Meanwhile, in the short term, there are only two variables that have a positive and significant effect on non-performing loans, namely, credit and interest rates. Inflation and exchange rate variables have a negative and insignificant effect on bad credit in the short term.