• 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 Journal of Engineering Geology
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• v.15 no.2 s.42
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• pp.213-227
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• 2005

This study aims to assess the problems with investigation method and to suggest the complementary solutions by comparing the predicted data from surface investigation with the outcome data from underground cavern. In the study area, one(NE-1) of 6 fracture zones predicted during the surface investigation was only confirmed in underground caverns. Therefore, it is necessary to improve the confidence level for prediction. In this study, the fracture classification criteria was quantitatively suggested on the basis of the BHTV images of NE-1 fracture zone. The major orientation of background fractures in rock mass was changed at the depth of the storage cavern, the length and intensity were decreased. These characteristics result in the deviation of predieted predicted fracture properties and generate the investigation bias depending on the bore hole directions and investigated scales. The evaluation of hydraulic connectivity in the surface investigation stage needs to be analyze by the groundwater pressures and hydrochemical properties from the monitoring bore hole(s) equipped with a double completion or multi-packer system during the test bore hole is pumping or injecting. The hydraulic conductivities in geometric mean measured in the underground caverns are 2-3 times lower than those from the surface and furthermore the horizontal hydraulic conductivity in geometric mean is six times lower than the vertical one. To improve confidence level of the hydraulic conductivity, the orientation of test hole should be considered during the analysis of the hydraulic conductivity and the methodology of hydro-testing and interpretation should be based on the characteristics of rock mass and investigation purposes.