• Journal of Digital Convergence
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• v.19 no.3
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• pp.161-166
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• 2021

The macroeconomic concept represents the movement of a country's economy, and it affects the overall economic activities of business, government, and households. In the macroeconomy, by looking at changes in national income, inflation, unemployment, currency, interest rates, and raw materials, it is possible to understand the effects of economic actors' actions and interactions on the prices of products and services. The US Federal Reserve System (FED) is leading the world economy by offering various stimulus measures to overcome the corona economic recession. Although the stock price continued to decline on March 20, 2020 due to the current economic recession caused by the corona, the US S&P 500 index began rebounding after March 23 and to 3,694.62 as of December 15 due to quantitative easing, a powerful stimulus for the FED. Therefore, the FED's economic stimulus measures based on macroeconomic indicators are more influencing, rather than judging the stock price forecast from the corporate financial statements. Therefore, this study was conducted to reduce losses in stock investment and establish sound investment by analyzing the FED's economic stimulus measures and its effect on stock prices.

• The Korean Journal of Applied Statistics
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• v.33 no.3
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• pp.321-334
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• 2020

The US Federal Reserve (Fed) has decided to cut interest rates. When we look at the expression of the FOMC statements at the time of policy change period we can understand that Fed has been communicating with markets through a change of word selection. However, there is a criticism that the method of analyzing the expression of the decision sentence through the context can be subjective and limited in qualitative analysis. In this paper, we evaluate the signaling effect of FOMC statements based on previous research. We analyze decision making characteristics from the viewpoint of text mining and try to predict future policy trend changes by capturing changes in expressions between statements. For this purpose, a decision tree and neural network models are used. As a result of the analysis, it can be judged that the discrepancy indicators between statements could be used to predict the policy change in the future and that the US Federal Reserve has systematically implemented policy signaling through the policy statements.

• Economic Analysis
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• v.26 no.3
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• pp.71-133
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• 2020

The Bank of Korea began its operation on June 12, 1950, with the Bank of Korea Act established a month or so earlier. Thus was first introduced to Korea modern central banking in the real sense of the word. The Bloomfield Mission, consisting of A. Bloomfield and J. Jensen of the Federal Reserve Bank of New York, spent about six months drafting a bill, which finally became the Bank of Korea Act. Little has been known yet about the process leading to the creation of the Mission and the historical context surrounding it, except that F. Tamagna of the Federal Reserve Board made in his capacity of the ECA's representative the offer of technical assistance to the Korean government. This paper attempts to dig deeper into relevant historical records and literature to fill these gaps. As it happened, the confrontation between the US and the USSR was accelerating towards the end of 1940s. The paper's new findings include that the Bloomfield Mission was, together with the ECA Mission to Korea, a product of the then US foreign policy (Cold War policy) and that the former Mission's technical assistance was conceived and provided all along as part of the inflation stabilization program pursued by the latter Mission. The Bloomfield Mission was after all a historical necessity. Next, the paper examines the changes added to the bill during its journey to becoming the Bank of Korea Act enacted in May 1950, presenting a review of the Act. The paper further evaluates the Act in terms of legal persistence, finding that the revised Act currently in force still substantially resembles the Act enacted 70 years ago from now. Finally in order is a brief discussion on those factors which seem to have contributed much to such persistence and thus apparent excellence of the Act enacted.

• Asia-Pacific Journal of Business
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• v.14 no.1
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• pp.365-379
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• 2023

Purpose - Our previous study (Chang & Lee, 2023) presented observations on the recent changes in the year-on-year (YoY) Consumer Price Index (CPI) of the Republic of Korea (ROK) after the COVID-19 pandemic. The purpose of this article is to present an integrated analysis and interpretation of the recent changes in CPI and the Aggregate Import Price Index (IPI) by incorporating recent data, specifically data from September 2022 to December 2022. Design/methodology/approach - This study collected CPI (YoY) data in the ROK from January 2019 to December 2022 using e-National Indicator System provided by the ROK. Statistical analysis was employed to analyze the data. Findings - First, we confirm the extended results of the existing study by Chang and Lee (2023). Second, we demonstrate that the Aggregate IPI in ROK increased significantly in 2022 compared to 2021. We then provide an integrated interpretation on the significant increase in CPI and aggregate IPI in ROK, which complements Chang and Lee (2023) that limits their discussion to YoY CPI. Moreover, we show that the IPI of the semiconductor in ROK decreased significantly in 2022 compared to 2021. Research implications or Originality - Our results provide important insights into the recent changes in the CPI in the ROK. The results suggest that these changes can be partially attributed to various factors, such as the global supply chain disruptions resulting from the spread of the COVID-19 pandemic and the prolonged war between Russia and Ukraine, the side effect of quantitative easing by the US Federal Reserve, heat waves and droughts caused by climate change in ROK, a surge in demand following a gradual daily recovery, US-China trade conflict, etc. Our study shows statistically comprehensive results compared to the studies that limit their discussion to YoY average growth rate.

• Journal of the Korea Convergence Society
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• v.12 no.7
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• pp.31-36
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• 2021

As the global economy stagnated due to the Corona 19 virus from Wuhan, China, most countries, including the US Federal Reserve System, introduced policies to boost the economy by increasing the amount of money. Most of the stock investors tend to invest only by listening to the recommendations of famous YouTubers or acquaintances without analyzing the financial statements of the company, so there is a high possibility of the loss of stock investments. Therefore, in this research, I have used artificial intelligence deep learning techniques developed under the existing automatic trading conditions to analyze and predict macro-indicators that affect stock prices, giving weights on individual stock price predictions through correlations that affect stock prices. In addition, since stock prices react sensitively to real-time stock market news, a more accurate stock price prediction is made by reflecting the weight to the stock price predicted by artificial intelligence through stock market news text mining, providing stock investors with the basis for deciding to make a proper stock investment.

• 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.