• International Area Studies Review
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• v.13 no.2
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• pp.298-324
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• 2009

The purpose of this paper is to examine the effect of the Korean won exchange rates on the Korean service trade balance. Empirical investigation shows that the USD/KRW and JPY/KRW exchange rates have main effects on the Korean service trade balance. Service balance credit and debit(receipts and payments) are negatively related with the USD/KRW and positively related with the JPY/KRW exchange rate. The depreciation of the USD/KRW and JPY/KRW exchange rates leads to the improvement of the service trade balance. Transportation balance is affected by the USD/KRW, JPY/KRW, and CNY/KRW exchange rates, travel balance by the USD/KRW exchange rate, and other business sevice balance by the USD/KRW and JPY/KRW exchange rates.

• East Asian Economic Review
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• v.18 no.1
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• pp.3-27
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• 2014

This paper examines the effects of financial crises on the long memory volatility dependency of daily exchange returns focusing on the Asian crisis in 97-98 and the Global crisis in 08-09. By using the daily KRW-USD and JPY-USD exchange rates which have different trading regions and volumes, this paper first applies both the parametric FIGARCH model and the semi-parametric Local Whittle method to estimate the long memory volatility dependency of the daily returns and the temporally aggregated returns of the two exchange rates. Then it compares the effects of the two financial crises on the long memory volatility dependency of the daily returns. The estimation results reflect that the long memory volatility dependency of the KRW-USD is generally greater than that of the JPY-USD returns and the long memory dependency of the two returns appears to be invariant to temporal aggregation. And, the two financial crises appear to affect the volatility dynamics of all the returns by inducing greater long memory dependency in the volatility process of the exchange returns, but the degree of the effects of the two crises seems to be different on the exchange rates.

• Proceedings of the KSR Conference
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• 2005.05a
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• pp.957-962
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• 2005

Since the nation's currency crisis in 1997. Korea reioined the USD 10.000 per capita income group after collapse of per capita income to USD 6.000 due to the minus GDP growth and sharp hike of exchange rate. It has also been expected for Korea to achieve per capita income of USD 20.000. provided that it maintains $10\%$ export increase rate. $5\%$ nominal GDP growth rate. $3\%$ consumer price index. $2\%$ increase in KRW/USD exchange rate. and $1\%$ net population increase rate. Yet. it should be noted that the nation needs to fulfill the necessity of various SOC infrastructure investment in order to achieve this goal. This paper will address the prospects for the future direction of the national SOC policies through the historical examination of the industrialized nations. such as U.S.A.. U.K.. France. and Japan. with regard to the relationships between economic growth and SOC provision. Some efforts will be made to forecast the optimal budget allocation of the national SOC, in particular, between highway and railway sectors.

• International Commerce and Information Review
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• v.12 no.1
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• pp.99-121
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• 2010

This paper reviews the categories and properties of risk measures, analyzes the classes and structural equations of volatility forecasting models, and presents the practical methodologies and their expansion methods of estimating and forecasting the volatilities of exchange rates using Excel spreadsheet modeling. We apply the GARCH(1,1) model to the Korean won(KRW) denominated daily and monthly exchange rates of USD, JPY, EUR, GBP, CAD and CNY during the periods from January 4, 1998 to December 31, 2009, make the estimates of long-run variances in the returns of exchange rate calculated as the step-by-step change rate, and test the adequacy of estimated GARCH(1,1) model using the Box-Pierce-Ljung statistics Q and chi-square test-statistics. We demonstrate the adequacy of GARCH(1,1) model in estimating and forecasting the volatility of exchange rates in the monthly series except the semi-variance GARCH(1,1) applied to KRW/JPY100 rate. But we reject the adequacy of GARCH(1,1) model in estimating and forecasting the volatility of exchange rates in the daily series because of the very high Box-Pierce-Ljung statistics in the respective time lags resulting to the self-autocorrelation. In conclusion, the GARCH(1,1) model provides for the easy and helpful tools to forecast the exchange rate volatilities and may become the powerful methodology to overcome the application difficulties with the spreadsheet modeling.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.191-209
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• 2022

This paper is a review of studies that focus on the prediction of a won/dollar exchange rate before and after the covid 19 pandemic. The Korea economy has an unprecedent situation starting from 2021 up till 2022 where the won/dollar exchange rate has exceeded 1,400 KRW, a first time since the global financial crisis in 2008. The US Federal Reserve has raised the interest rate up to 2.5% (2022.7) called a 'Big Step' and the Korea central bank has also raised the interested rate up to 2.5% (2022.8) accordingly. In the unpredictable economic situation, the prediction of the won/dollar exchange rate has become more important than ever. The authors separated the period from 2015.Jan to 2022.Aug into three periods and built a best fitted ARIMA/ARDL prediction model using the period 1. Finally using the best the fitted prediction model, we predicted the won/dollar exchange rate for each period. The conclusions of the study were that during Period 3, when the usual relationship between exchange rates and economic factors appears, the ARDL model reflecting the variable relationship is a better predictive model, and in Period 2 of the transitional period, which deviates from the typical pattern of exchange rate and economic factors, the SARIMA model, which reflects only historical exchange rate trends, was validated as a model with a better predictive performance.

• 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.

• Korea Trade Review
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• v.41 no.5
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• pp.113-138
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• 2016

This study analyzed the impact when Korea expands Chinese Renminbi(RMB) as invoicing currency on the trade to China using Monte-Carlo simulation. Primarily, we analyzed the impact on the balance of Korean Won(KRW) converted from RMB in a case that simulated exchange rate(Korean won to Chinese Renminbi) and realized historically identical probability distribution but in different stochastic process. In addition, we developed the simulation of the case where the volatility of RMB to KRW exchange rate abnormally expanded. The major results found in this study are as follows. First, in the case where RMB exchange rate simulated in identical probability distribution but in the different stochastic process, no matter how much RMB was utilized as invoicing currency, expansion of the RMB exchange rate and exchange rate volatility operated as positive mechanism to increase the KRW converted balance. Secondly, while the expansion of US dollar exchange rate volatility positively influences the balance on average, it caused a polarization of balance, which makes under-average-balance lower and over-average-balance higher. On the contrary, the expansion of RMB exchange rate volatility even shows a similar mechanism but the impact is more moderate than USD exchange rate volatility. Thirdly, as RMB exchange rate volatility expanded, the balance of translated invoicing currency (RMB) declined, whilst the negative impact of RMB exchange rate volatility on balance of translated invoicing currency(RMB) showed diminishing effect. Lastly, the influence of RMB's exchange rate volatility through RMB usage ratio trends similar to bull spread strategy, which is a combination of call option with put option. Therefore, since RMB usage in invoicing currency could spawn a hedging effect, corporations might utilize RMB as a strategic device for maximizing profits.

• Communications for Statistical Applications and Methods
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• v.16 no.5
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• pp.803-812
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• 2009

The application of extreme value theory to financial data is a fairly recent innovation. The classical annual maximum method is to fit the generalized extreme value distribution to the annual maxima of a data series. An alterative modern method, the so-called threshold method, is to fit the generalized Pareto distribution to the excesses over a high threshold from the data series. A more substantial variant is to take the point-process viewpoint of high-level exceedances. That is, the exceedance times and excess values of a high threshold are viewed as a two-dimensional point process whose limiting form is a non-homogeneous Poisson process. In this paper, we apply the two-dimensional non-homogeneous Poisson process model to daily losses, daily negative log-returns, in the data series of KBW/USD exchange rate, collected from January 4th, 1982 until December 31 st, 2008. The main question is how to estimate extreme quantiles of losses such as the 10-year or 50-year return level.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.27 no.4
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• pp.52-64
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• 2019

The purpose of this study is to analyze the impact of macroeconomic variables on air passenger demand and provide useful information to airport managers and policymakers. Therefore, using the quarterly macroeconomic indicators from 2002 to 2017, the relationship with air passenger demand was demonstrated by multiple regression analysis. In the previous studies, they used GDP, Korea Treasury Bond, KOSPI index, USD/KRW Exchange Rate, and WTI Crude Oil Price variables. In this study, we used the Coincident Composite Index, Employment Rate, Consumer Sentiment Index, and Private Consumption Rate used as additional variables. It has confirmed that if the consumption of research results expands or the economic environment is right, it will affect the increase in international passengers. In other words, it confirmed that the overall economic situation acts as the main factor determining air passenger demand. It confirmed that the economic environment at the past has a significant impact on air passenger demand.

• The Korean Journal of Financial Management
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• v.24 no.3
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• pp.153-186
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• 2007

It is well known that the distributional properties of financial asset returns exhibit fatter-tails and skewer-mean than the assumption of normal distribution. The correct assumption of return distribution might improve the estimated performance of the Value-at-Risk(VaR) models in financial markets. In this paper, we estimate and compare the VaR performance using the RiskMetrics, GARCH and FIGARCH models based on the normal and skewed-Student-t distributions in two daily returns of the Korean Composite Stock Index(KOSPI) and Korean Won-US Dollar(KRW-USD) exchange rate. We also perform the expected shortfall to assess the size of expected loss in terms of the estimation of the empirical failure rate. From the results of empirical VaR analysis, it is found that the presence of long memory in the volatility of sample returns is not an important in estimating an accurate VaR performance. However, it is more important to consider a model with skewed-Student-t distribution innovation in determining better VaR. In short, the appropriate assumption of return distribution provides more accurate VaR models for the portfolio managers and investors.