• Title/Summary/Keyword: Interest Rate

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A Study on the Impact of Macroeconomic Factors in the Health Care Industry Stock Markets (거시경제요인이 보건의료산업 주식시장에 미치는 영향에 관한 연구)

  • Lee, Sang-Goo
    • Management & Information Systems Review
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    • v.34 no.4
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    • pp.67-81
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    • 2015
  • The purpose of this study was to evaluate the effect of this factor on the macroeconomic variables for the healthcare industry market. First, the government bond interest rates and the exchange rate is the cause variable of drug industry index. Drug industry index is a mutual influence between the Call interest rate. Second, the medical equipment index haver mutual cause variable such as call rate index, government bond interest rates, and exchange rate. A current account balance variable is the cause variable of drug industry index. Third, the drug industry index has a negative relationship with a Call interest rate and an exchange rate. but it has a positive relationship with a government bond interest rates. the medical equipment index has a negative relationship with an exchange rate. but it has a positive relationship with a government bond interest rates.

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Using Classification function to integrate Discriminant Analysis, Logistic Regression and Backpropagation Neural Networks for Interest Rates Forecasting

  • Oh, Kyong-Joo;Ingoo Han
    • 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.

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An Empirical Study on the Economic Development Effects on Kazakhstan Focusing on the Macroeconomic Indices: International Oil Price, Interest Rate, Real Exchange Rate (카자흐스탄 경제발전에 대한 실증연구 : 국제유가·이자율·실질환율을 중심으로)

  • Hwang, Yun-Seop;Kim, Kyung-Hee;Kim, Soo-Eun
    • International Area Studies Review
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    • v.14 no.1
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    • pp.77-97
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    • 2010
  • Recently, countries on the Caspian Sea were had heavily interested due to instability of international resource market. These countries having been developed basing on energy exports, especially Kazakhstan have drastically grown during a decades. However economy, heavily relied on the exports of energy, is influenced on fluctuation in the international energy price as well as sometimes exposed at Dutch disease. These days, Kazakhstan, increased trade and investment with Korea, has been on the rise as new supplier for energy. Therefore, economic change in Kazakhstan can be an important issue. In this paper, we analyze relations among oil price, interest rate, and real exchange rate during sample period from January 1999 to December 2008 expanding Balasa-Samuelson model. Empirical results present that oil price, interest rate, and real exchange rate mutually keep their balance. Eventually, we find out Kazakhstan has exposed at Dutch disease since oil price and interest rate have negative impacts on real exchange rate respectively.

Using Structural Changes to support the Neural Networks based on Data Mining Classifiers: Application to the U.S. Treasury bill rates

  • Oh, Kyong-Joo
    • 한국데이터정보과학회:학술대회논문집
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    • 2003.10a
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    • pp.57-72
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    • 2003
  • This article provides integrated neural network models for the interest rate forecasting using change-point detection. The model is composed of three phases. The first phase is to detect successive structural changes in interest rate dataset. The second phase is to forecast change-point group with data mining classifiers. The final phase is to forecast the interest rate 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 network model alone and, in addition, determine which of three classifiers (MDA, CBR and BPN) can perform better. For interest rate forecasting, this study then examines the predictability of integrated neural network models to represent the structural change.

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TWO APPROACHES FOR STOCHASTIC INTEREST RATE OPTION MODEL

  • Hyun, Jung-Soon;Kim, Young-Hee
    • Journal of the Korean Mathematical Society
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    • v.43 no.4
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    • pp.845-858
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    • 2006
  • We present two approaches of the stochastic interest rate European option pricing model. One is a bond numeraire approach which is applicable to a nonzero value asset. In this approach, we assume log-normality of returns of the asset normalized by a bond whose maturity is the same as the expiration date of an option instead that of an asset itself. Another one is the expectation hypothesis approach for value zero asset which has futures-style margining. Bond numeraire approach allows us to calculate volatilities implied in options even though stochastic interest rate is considered.

The prediction of interest rate using artificial neural network models

  • Hong, Taeho;Han, Ingoo
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1996.04a
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    • pp.741-744
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    • 1996
  • Artifical Neural Network(ANN) models were used for forecasting interest rate as a new methodology, which has proven itself successful in financial domain. This research intended to construct ANN models which can maximize the performance of prediction, regarding Corporate Bond Yield (CBY) as interest rate. Synergistic Market Analysis (SMA) was applied to the construction of models [Freedman et al.]. In this aspect, while the models which consist of only time series data for corporate bond yield were devloped, the other models generated through conjunction and reorganization of fundamental variables and market variables were developed. Every model was constructed to predict 1,6, and 12 months after and we obtained 9 ANN models for interest rate forecasting. Multi-layer perceptron networks using backpropagation algorithm showed good performance in the prediction for 1 and 6 months after.

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Impact of Malaysia's Capital Market and Determinants on Economic Growth

  • Ali, Md. Arphan;Fei, Yap Su
    • The Journal of Asian Finance, Economics and Business
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    • v.3 no.2
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    • pp.5-11
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    • 2016
  • This study investigates the impact of Malaysia's capital market and other key determinants on Economic Growth from the period of 1988 to 2012. The key determinants studied are foreign direct investment and real interest rate. This study also examines the long run and short run relationship between the economic growth and capital market, foreign direct investment, and real interest rate by using bound testing cointegration of Autoregressive Distributed Lag (ARDL) and Error Correction Model (ECM) version of ARDL model. The empirical results of the study suggest that there is long- run cointegration among the capital market, foreign direct investment, real Interest rate and economic growth. The result also suggests that capital market and real interest rate have positive impact on economic growth in the short run and long run. Foreign direct investment does not show positive impact on economic growth in the short run but it does in the long run.

A Study on Risk Selection Behavior of Japanese Households: Focusing on the relationship between income level and hyperbolic discount (日本家計のリスク選択行動に関する研究 - 所得水準と双曲性の関係を中心に -)

  • Yeom, Dong-ho
    • Analyses & Alternatives
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    • v.4 no.1
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    • pp.105-123
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    • 2020
  • This study analyzes the risk selection behavior of Japanese households. The study approaches the view of 'the hyperbolic discount' which is used in behavioral economics based on the rise in mortgage lending by low-income households in the late 2000s. The study focuses on how households risk preferences vary by income levels. The study analyzes the relationship of attitude of household interest rate risk using Binomial Logistic and Heckman two-step estimation method assuming that there are only two types of Adjustable-Rate Mortgage and Fixed-Rate Mortgage. As a result of the empirical analysis, low-income households annual income tend to have a higher proportion of housing debt as same as higher interest rate risk preferences households in proportion to income growth and interest rate risk preferences. Those results indicate that there is possibility of a hyperbolic discount on low-income households in Japan, and support the hypothesis that low-income households are relatively higher household debt ratio because of high utility due to home purchase in the near future (short-term).

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A Study on Uncovered Interest Rate Parity : Revisited (커버되지 않은 이자율평가에 대한 실증연구)

  • Lee, Jai Ki
    • 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.