• Title/Summary/Keyword: 기대인플레이션

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A Study on the Impact of International Prices on Domestic Prices and Export Prices in Korea (국제물가 변동 충격이 국내물가와 수출물가에 미치는 영향 분석)

  • Kim, Jung Ryol
    • International Commerce and Information Review
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    • v.15 no.4
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    • pp.195-216
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    • 2013
  • In this paper, I investigate how international prices affect domestic prices and export prices in Korea by using vector error correction model(VECM) and estimate its impact on international trade. According to the empirical results, international prices, such as world raw material prices and oil prices, make stronger effects on domestic prices, in order of import, export, producer, and consumer prices. And recent years the effect of international raw material prices on domestic prices becomes larger. It implies importers, exporters and producers are more affected by international prices than consumers are. Therefore, the international trade, import and export, is affected by changes in international prices. Firms, especially importing and exporting companies, should do much efforts on risk managing about raw material prices variation, diversification of raw material suppliers, and oversea resources development. The government is needed to support on firms those efforts while doing its economic policies to cope with economic conditions and the price policy.

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Study on Economic and Financial Education for the North Koreans after Unification: from the Perspective of Behavioral Economics (통일 후 북한 주민 대상 경제금융 교육에 관한 연구: 행태경제학 관점을 중심으로)

  • Son, Jeong-Kook;Kim, Young-Min
    • The Journal of the Convergence on Culture Technology
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    • v.7 no.2
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    • pp.239-246
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    • 2021
  • Unification means the change of the economic system from 'Planned Economy' of the North Korea to 'Market Economy' of the South Korea. Therefore, it may cause confusions and difficulties for North Koreans who have been under planned economy for ages. So, we need to take the perspective of behavioral economics for the effective education. First of all, it is about overall finance, which contains the record of financial transactions, effect of inflation, investors' bounded rationality, and choice difficulty of financial products. Second, it is about borrowings, which includes the credit management, interest rate of difference among financial institutions. Third, it is about investment on financial products, which includes the effect of cost on returns, difference between compound interest and simple interest, trade-off between expected return and risk, market and non-market risks, the importance of diversification, and passive & aggressive investments.

A Study on Foreign Exchange Rate Prediction Based on KTB, IRS and CCS Rates: Empirical Evidence from the Use of Artificial Intelligence (국고채, 금리 스왑 그리고 통화 스왑 가격에 기반한 외환시장 환율예측 연구: 인공지능 활용의 실증적 증거)

  • Lim, Hyun Wook;Jeong, Seung Hwan;Lee, Hee Soo;Oh, Kyong Joo
    • 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.