• KDI Journal of Economic Policy
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• 제31권2호
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• pp.15-45
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• 2009

본고에서는 3요인 무재정거래(3-factor no arbitrage) 조건하에서의 이자율 기간 구조를 추정하고 이를 이용하여 기간프리미엄의 추이 및 정책금리 변경의 유효성을 분석하였다. 기간프리미엄의 경우 3년물에서 높게 나타나고 있는데, 이는 장기적인 경제 상황보다 향후 3년 정도의 시계에서 경제의 불확실성이 높을 것이라는 투자자들의 인식을 반영한 것으로 해석된다. 한편, 최근 기준 지표금리의 변경에 따른 통화정책의 효과성을 살펴보기 위해 지표금리 변경시점을 전후로 하여 금융시장에서의 단기금리 변경이 채권시장의 수익률곡선의 형태에 미치는 효과를 분석해 보았다. 분석 결과, 금융시장에서의 대표적인 단기금리인 콜금리와 채권시장에서의 단기금리인 초단기이자율 간의 괴리가 지표금리 변경 이전과 비교하여 크게 확대된 점을 발견할 수 있었다. 이러한 괴리 확대가 새로운 기준금리에 대한 운용겸험 미숙에 연유한 것인지, 최근의 국제금융시장 불안에 따른 예외적인 경우인지는 현 단계에서는 명확히 결론짓기 어려우나 통화정책의 유효성을 제고하기 위해서는 이러한 괴리를 축소하는 통화정책 운용이 필요할 것이다.

• 대한가정학회지
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• 제49권8호
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• pp.37-46
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• 2011

Using the 1987-2008 quarterly aggregated data of the Household Income and Expenditure Survey, this study investigated the factors influencing household saving rate. The independent variables in the AR regression model were the GDP growth rate, shares of the total household expenditure allocated to tax & social insurance, and education, the variables reflecting the conditions of the asset market including interest rate, stock market index, and real estate price index, and the variables representing the social economic conditions including the index of aging and income inequality. Among the independent variables interest rate, stock market index, and income inequality were found to be significantly associated with the household saving rate. These results suggested that the redistribution and financial market policies favorable to savers may be effective for raising the household saving rate.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2000년도 춘계정기학술대회 e-Business를 위한 지능형 정보기술 / 한국지능정보시스템학회
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• pp.235-241
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• 2000

This article suggests integrated neural network models for the interest rate forecasting using change point detection. The basic concept of proposed model is to obtain intervals divided by change point, to identify them as change-point groups, and to involve them in interest rate forecasting. the proposed models consist of three stages. The first stage is to detect successive change points in interest rate dataset. The second stage is to forecast change-point group with data mining classifiers. The final stage is to forecast the desired output with BPN. Based on this structure, we propose three integrated neural network models in terms of data mining classifier: (1) multivariate discriminant analysis (MDA)-supported neural network model, (2) case based reasoning (CBR)-supported neural network model and (3) backpropagation neural networks (BPN)-supported neural network model. Subsequently, we compare these models with a neural networks (BPN)-supported neural network model. Subsequently, we compare these models with a neural network model alone and, in addition, determine which of three classifiers (MDA, CBR and BPN) can perform better. This article is then to examine the predictability of integrated neural network models for interest rate forecasting using change-point detection.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2012년도 춘계 학술논문 발표대회
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• pp.161-163
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• 2012

Recently on Value Engineering(VE) and Life Cycle Cost(LCC) social interests is increasing. The government Turn Key, BTL projects and public works projects, such as VE and LCC Analysis on the value and economic analysis is mandatory. And accordingly the VE and LCC analysis is underway for the various studies. However, there is a problem existing in the LCC analysis. Worth the cost varies according to the flow of time. However, the real interest rate during the LCC analysis of buildings in calculation time for interest rates and inflation are not considering the value of the flow. In other words, a few years using the average value of the deterministic analysis method has been adopted. These costs for the definitive analysis of the cost of an uncertain future, unforeseen changes resulting hazardous value. In this study of the last 15 years interest rates and inflation targeting by using Monte-Carlo Simulation is to perform probabilistic analysis. This potential to overcome uncertainties of the cost of building a more scientific and LCC Estimation of the probability value of the real interest rate is presented.

• The Journal of Asian Finance, Economics and Business
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• 제8권1호
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• pp.1-6
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• 2021

This research examines the stock market index determinants and the prediction using the FFT curve fitting of the Jakarta Stock Exchange (JKSE) Composite Index during the COVID-19 pandemic. This paper has used daily data of Jakarta Stock Exchange (JKSE) Composite Index, interest rate, and exchange rate from 15 October 2019 to 15 September 2020, and a total of 224 observations, retrieved from Indonesia Stock Exchange (IDX), Indonesia Statistics Central Bureau and Observation & Research of Taxation. The study covers descriptive statistics, multicollinearity test, hypothesis tests, determination test, and prediction using FFT curve fitting. The results unveil four fresh and robust evidence. Partially, the interest rate has affected positively and significantly the stock market index. Partially, the exchange rate has affected negatively and significantly the stock market index. The F-test result, interest rate, and exchange rate have significantly affected the stock market index (JKSE) simultaneously. Furthermore, the FFT curve fitting has predicted that the stock market fluctuates and increases over time. The results have shown a strong influence of the independent variables and the dependent variable. The value of Adjusted R-Square is 0.719, which means that the independent variables have simultaneously impacted the dependent variable for 71.9%; other factors have influenced the remaining 28.1%.

• 노동경제논집
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• 제40권1호
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• pp.37-68
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• 2017

본 연구에서는 재정패널 자료를 이용하여 가계부채와 기혼여성의 노동공급 사이의 관계를 분석하였다. 이를 위해 가구의 이자비용 납부액 대비 가구금융부채 금액을 이용하여 가구의 유효이자율을 구축하였다. 금융부채가 없는 가구의 경우 Heckman Selection 모형을 적용하여 가구의 이자율을 추정하였다. 실증 분석결과 가구에서 부담하는 유효이자율이 상승하게 될 경우 기혼여성의 노동시장 참여가 확대된다는 것을 발견하였다. 이로부터 기준금리가 인상되는 상황에서 예상할 수 있는 부정적인 시나리오를 가구 노동공급 증가와 근로소득의 상승효과를 통해 일정 부분 상쇄할 수 있는 긍정적인 효과를 제시하고 있다.

• 대한수학회지
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• 제57권5호
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• pp.1167-1186
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• 2020

This paper considers the case of pricing discretely-sampled variance swaps under the class of equity-interest rate hybridization. Our modeling framework consists of the equity which follows the dynamics of the Heston stochastic volatility model, and the stochastic interest rate is driven by the Cox-Ingersoll-Ross (CIR) process with full correlation structure imposed among the state variables. This full correlation structure possesses the limitation to have fully analytical pricing formula for hybrid models of variance swaps, due to the non-affinity property embedded in the model itself. We address this issue by obtaining an efficient semi-closed form pricing formula of variance swaps for an approximation of the hybrid model via the derivation of characteristic functions. Subsequently, we implement numerical experiments to evaluate the accuracy of our pricing formula. Our findings confirm that the impact of the correlation between the underlying and the interest rate is significant for pricing discretely-sampled variance swaps.

• The Journal of Asian Finance, Economics and Business
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• 제7권11호
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• pp.127-135
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• 2020

This study aims to measure the effects of real interest rate (RIR), gross domestic savings (GDS), and net exports (EN) shocks on Indonesia's economic growth (EG). The focus on Indonesia is unique due to the abundant resources available in the nation, but they are unsuccessful in boosting economic growth. This study applied a quantitative method to comprehensively analyze the correlation between variables by employing Vector Autoregression Model (VAR) combined with Vector Error Correction Model (VECM). Various procedures are preformed: Augmented Dickey-Fuller test (ADF), Optimum Lag Test, Johansen Cointegration Test, Granger Causality Test, as well as Impulse Response Function (IRF) and Error Variance Decomposition Analysis (FEVD). The data were collected from the World Bank and the Asian Development Bank from 1986 to 2017. The findings of the study indicated that economic growth responded positively to real interest rate shocks, which implies that when the real interest rate experiences a shock (increase), the economy will be inclined to growth. While, economic growth responded negatively to gross domestic savings and net export shocks. Policymakers are expected to consider several matters, particularly the economic conditions at the time of formulating policy, so that the prediction effectiveness of a policy can be appropriately assessed.

• 아태비즈니스연구
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• 제13권3호
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• pp.343-359
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• 2022

We analyze the regional ripple effects of both the sale prices and cheonsei prices using the global VAR(GVAR) model. The interest rate shock causes the regional sale prices to fall. Moreover, the greatest responses to the shock are those of Gangnam-gu, etc. because of there were many transactions for investment purpose. When interest rate rose, the cheonsei price in Gangnam-gu reacted greatly. Conversely, if interest rates fall, the cheonsei demand to live in Gangnam-gu increases. Furthermore, the response of sale price to the interest rate shock are greater than those of the cheonsei prices. Whereas, a positive shock on the sale price in Gangnam-gu increases the sale price there. It also raises the sale prices of the surrounding area in a similar pattern. The shock on the sale price in Gangnam-gu also increases the cheonsei price in Gangnam-gu. In addition, an increase in the sale price in Gangnam-gu leads to increases of cheonsei prices in other regions. Therefore, the recent rise of the base rate can negatively affect the sale prices, and thus a decrease in the sale price spreads to the surrounding areas. Accordingly, it is time for policy alternatives to make a soft landing in sale prices.

• 대한산업공학회지
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• 제13권2호
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• pp.1-8
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• 1987

In this paper, a deterministic EOQ model with interest rate in which a proportion (${\beta}$) of the demand is backlogged and the rest (1-${\beta}$) is lost. The optimal order quantity is derived and the corresponding average cost is obtained, Sensitivity analysis is performed to sec the influence of interest rate on the optimal order quantity and the average cost. Finally a numerical example is given in which optimum quantities of the model developed in this study and those of the conventional EOQ model are compared.