• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2000년도 추계정기학술대회:지능형기술과 CRM
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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.

• International Journal of Advanced Culture Technology
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• 제9권3호
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• pp.174-180
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• 2021

The necessity of this study is as follows. A decrease in the number of newborns, an increase in the youth unemployment rate, and a decrease in the employment rate are having a fatal impact on universities. To help increase the employment rate of universities, we intend to utilize Big Data of university public information. Big data refers to the process of collecting and analyzing data, and includes all business processes of finding data, reprocessing information in an easy-to-understand manner, and selling information to people and institutions. Big data technology can be divided into technologies for storing, refining, analyzing, and predicting big data. The purpose of this study is to find the vision and special department of a university with a high employment rate by using big data technology. As a result of the study, big data was collected from 227 universities on www.academyinfo.go.kr site, We selected 130 meaningful universities and selected 25 universities with high employment rates and 25 universities with low employment rates. In conclusion, the university with a high employment rate can first be said to have a student-centered vision and university specialization. The reason is that, for universities with a high employment rate, the vision was to foster talents and specialize, whereas for universities with a low employment rate, regional bases took precedence. Second, universities with a high employment rate have a high interest in specialized departments. This is because, as a result of checking the presence or absence of a characterization plan, universities with a high employment rate were twice as high (21/7). Third, universities with high employment rates promote social needs and characterization. This is because the characteristic departments of universities with high employment rates are in the order of future technology and nursing and health, while universities with low employment rates promoted school-centered specialization in future technology and culture, tourism and art. In summary, universities with high employment rates showed high interest in student-centered vision and development of special departments for social needs.

• Journal of the Korean Data and Information Science Society
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• 제24권4호
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• pp.737-753
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• 2013

금리변동형 보험상품은 시장금리에 연동하여 이자율 (공시이율)을 적용하는 보험상품이지만, 시장금리의 하락시에도 해약환급금의 이자율을 보증하기 위해 최저보증이율을 설정하도록 하고 있다. 즉, 공시이율이 계약할 당시 설정한 최저보증이율을 하회할 경우 보험사는 공시이율과 최저보증이율 중에 큰 금액으로 책임준비금을 적립하고 계약자가 보험계약을 해지할 경우 해약환급금을 지급해야 한다. 이러한 이자율 보증옵션은 시장금리가 하락하는 최근의 저금리 기조에서 생명보험회사의 손익을 악화시키는 요인이 되고 있다. 본 논문에서는 현재의 저금리 상황과 이자율 보증옵션 적용방식 현황을 살펴보고, 금리변동형 종신보험과 금리변동형 연금보험의 이차손익 구조 및 이자율 보증옵션의 가치와 리스크를 분석한다. 그리고, 이자율 보증옵션의 분석 결과를 토대로 시장이율과 최저보증이율의 금리차와 이차손익과의 관계에 대한 시사점을 제시한다.

• The Journal of Asian Finance, Economics and Business
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• 제8권12호
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• pp.31-38
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• 2021

This study contributes to the existing literature and tries to analyze the validity of the Fisher hypothesis in the Philippines. Using monthly data from January 1995 to December 2020, the empirical analysis used the Engle-Granger and Johansen cointegration testing technique. The correlation coefficient suggests a strong positive association. All things being equal, a rise in inflation leads to a rise in the nominal interest rate. The unit-root tests show that inflation and the nominal interest rate are both stationary. Based on both Engle-Granger and cointegrating regression Durbin-Watson tests, the nominal interest rate and inflation are cointegrated. Likewise, the results from Johansen cointegration indicate that there exists a long-run relationship between the variables. However, we rejected a one-to-one relationship between nominal interest rate and inflation. The error correction term coefficient (ECM) shows that it is statistically significant suggesting that the nominal interest rate adjusts to the inflation rate with a lag. The Pair-wise Granger Causality test reported a bi-directional causal relationship between nominal interest rate and inflation. Inflation targeting has been the monetary policy framework of choice for most central banks. In essence, the conclusions of this study are useful to central banks because they help them better comprehend the long-run equilibrium relationship between the nominal interest rate and inflation.

• 산경연구논집
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• 제11권8호
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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.

• The Journal of Asian Finance, Economics and Business
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• 제7권12호
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• pp.43-52
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• 2020

This paper examines how macroeconomic variables, such as interest rate differences, inflation, exchange rates, economic growth and external debt growth, affect capital flight in the ASEAN-8 countries. We apply a panel data model with fixed effect estimation for the data for eight countries from the period 1994 to 2018. We use the residual approach used by the World Bank to measure the value of capital flight. The results show that the interest rate differences, exchange rates, economic growth and foreign debt growth had a positive and significant effect on outward capital flight. A further implication of this finding is that the interest rate differences, exchange rate, economic growth and foreign debt growth are factors that trigger an increase in capital outflow in the ASEAN-8 countries. Nonetheless, inflation rate is not considered to be the main factor influencing capital flight, as average inflation in the ASEAN-8 countries remains relatively stable. This paper will be beneficial for policymakers in the ASEAN-8 countries and encourage them to constantly pay attention to these four variables, as they significantly influence capital flight, whereas they can disregard the impact of the inflation variable that is not significant in influencing capital flight.

• The Journal of Asian Finance, Economics and Business
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• 제7권12호
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• pp.123-129
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• 2020

This scholarly work is an effort to capture the effects of oil prices on the actual exchange rate between dollar and rupee. This is done with reference to the U.S. dollar as oil prices are marked in USD (U.S. Dollar) in the international market, and India is among the top five importers of oil. Using monthly data from January 2001 to May 2020. The study used the real GDP, money supply, short-term interest rate difference between two countries, and inflation apart from the crude oil prices per barrel as the factors that help define the exchange rate. The analysis, through cointegration and vector error correction method (VECM), suggests long and short-run causality amid prices of oil and the rate of exchange fluctuations. Oil prices are found to be negatively related to the exchange rate in the long term but positively related in the short term. The result of the Wald test also indicates the short-run causation from the short-term interest rate and the prices of crude oil towards the exchange rate. The present study shows that oil prices are evidence of the existence of short-term and long-term driving associations with short-term interest rates and exchange rates.

• 대한조선학회논문집
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• 제51권6호
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• pp.451-458
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• 2014

The purpose of this study is to compare the economics between a diesel propulsion vessel and a LNG fuel propulsion vessel through the analysis of the present value using the LCC(Life Cycle Cost) method. This study is also to judge the economics for long-term operation of a LNG fuel propulsion vessel as a result of analysis about the equivalent uniform annual cost. In particular, LCC method was strengthened by sensitivity analysis based on combined interest rate which is considering discount rate and inflation rate simultaneously.

• The Journal of Asian Finance, Economics and Business
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• 제6권2호
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• pp.119-122
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• 2019

The study aims to investigate factors influencing business households' decision for borrowing credit: the case of commercial banks in Tra Vinh Province, VietNam. The study was conducted by collecting data from 300 business households traded at four commercial banks in Tra Vinh province (Viet Nam bank for agriculture and rural development, Tra Vinh Branch; Viet Nam jointstock commercial bank industry and trade, Tra Vinh Branch; Asia joinstock commercial bank, Tra Vinh Branch; Viet Nam jointstock commercial bank for foreign trade, Tra Vinh Branch). By the use of the Binary Logistic regression method, the research found out that the factors influencing to borrow c redit of household business's decision including: banks brand names, loan interest rates, service attitude, and loan procedures. Of those, the banks brand names and lending interest rates have the strongest impacts on borrow credit decision of business households at commerc ials banks in Tra Vinh province. Since then, the study has proposed solutions to improve access to credit of business households in commercial banks in Tra Vinh province in the coming time, such as: developing a bank brand; the development of flexible lending interest rate policies; improve service style of bank staff; at the same time, simplifying lending procedures.

• The Journal of Asian Finance, Economics and Business
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• 제8권10호
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• pp.297-303
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• 2021

The performance of the retail industry in a country, which simultaneously reflects the demand for retail space, is significantly influenced by the macroeconomic environment of said country. However, in the case of Malaysia, studies regarding this issue are limited. Therefore, this paper aims to identify the macroeconomic determinants of the demand for retail space in shopping centers in Malaysia through the study of six variables: per capita income, private expenditure, inflation rate, interest rate, total population, and the number of tourists arrival. The nexus between these variables and the demand for retail space in shopping centers were examined by cointegration and causality tests, and regression analysis using quarterly data for the period 1993Q1 to 2016Q4. The results from bivariate cointegration tests indicate that inflation rate, interest rates, population size, and the number of tourists arrival have significant long-run relationships with the demand for retail space of Malaysian shopping centers. Meanwhile, the Granger causality tests show that only population size can cause the demand for shopping centers' retail space. Finally, the results from the regression analysis revealed that income per capita, private expenditure, interest rates, and population are the variables that significantly influence the demand for the retail space of the Malaysian shopping centers.