• International Area Studies Review
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• v.15 no.2
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• pp.77-100
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• 2011

The Korean economy have experienced the remarkable decreases in factor prices such as bond yields, real wage since the IMF foreign exchange crisis. This paper investigates the effects of the price changes in the factor markets on determining the level and cyclicality of industrial markups in the manufacturing industry. For this purpose, we construct a markup equation in the small open economy based on the production function including foreign intermediate goods and assuming constant returns to scale technology and AR(1) process of technological coefficient. Empirical results are summarized as the followings. The empirical results shows that the increased markups after the IMF crisis can be explained by the price decreases in the factor markets which result in lowering marginal costs. And we also observed counter cyclicality of markup, labor share and interest rates while real wages, technical coefficients, and production price index proved to be pro-cyclical. In conclusion, the price changes in factor market have contributed to the stickiness in markup fluctuation in the manufacturing industry.

• Ocean and Polar Research
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• v.41 no.1
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• pp.35-46
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• 2019

The purpose of this study is to identify factors influencing fish production of shallow-sea aquaculture in South Korea. This study employed the two-way fixed effect and random effect models based on the panel models and also the difference between GMM and system GMM models based on the dynamic panel models using the amount of fish farming production, the number of stocked fry, the number of cultured fish, the amount of inputted feed, the farming area, the number of workers, and the sales price data from 2010 to 2017. First, the two-way fixed effect model of the panel models was selected by panel characteristics, time characteristics and Hausman tests and also the model was statistically significant. As a result of the two-way fixed effect model, the number of stocked fry, the amount of inputted feed, and the number of workers were identified as factors that increase the fish production of shallow-sea aquaculture. However, the number of cultured fish and the sales price were analyzed as factors that reduce the fish production of shallow-sea aquaculture. Second, the system GMM model of the dynamic panel models was selected by Hansen test and Arellano-Bond test in order to identify whether or not the over-discrimination condition is appropriate. Based on the system GMM model, the number of stocked fry, the amount of inputted feed, the number of workers in this year and 1 year ago, the number of cultured fish 2 years ago, and the sale price 3 years ago were analyzed as factors that increase the fish production of shallow-sea aquaculture. However, the amount of fish farming production 1, 2, 3 years ago, the farming area in this year, and the number of cultured fish in this year and 1 year ago were identified as factors that reduce the fish production of shallow-sea aquaculture. In conclusion, this study suggests that it is desirable to control the amount of stocked fry rather than to expand the farming area for fish farming in shallow-sea aquaculture, so as to keep the sale price at a certain level by maintaining the appropriate amount of fish production.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.

• Journal of Venture Innovation
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• v.1 no.1
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• pp.83-98
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• 2018

This paper makes a theoretical approach to the differences between transaction tax and capital gains tax when the financial instruments are traded and imposed taxes in K-OTC market, a newly emerging off-board market. Since it is difficult to reduce risk to the level which investors would like to pursue - depending on the taxation methods of portfolio-composed financial instruments - when it comes to forming a synthetic bond to hedge risk, this paper also seeks for effective taxation methods to make this applicable. First of all, to thoroughly review the taxation balance of synthetic bonds, this paper analyzed the effects of the transaction tax and capital gains tax imposed upon synthetic bonds according to the changes in final stock price and strike price in K-OTC market, and analyzed after-tax profit differences among them depending on whether income tax deduction took place or not. As a result of the research upon the tax gap in transaction tax and capital gains tax according to the changes of final stock prices, it was shown that imposing transaction tax is more likely to be effective for some level of risk hedging with replicating portfolio considering taxation policies and financial markets, since the effect of the transaction tax has a much lower tax gap than that of capital gains tax. In addition, in relation to whether income tax deduction was permitted or not, it was proved that the effect of the transaction tax and the capital gains tax vary depending on the variation in the strike price. Above all, it was shown that if the strike price is lower than the stock price, the transaction tax will be less affected by the existence of income tax deduction than the capital gains tax, while both will be equally affected by the existence of income tax deduction if the strike price is higher than the stock price. Further study would be to demonstrate the validation of this in the K-OTC market with actual financial instruments and, also, to seek for a more systematic hedging method by using a ratio analysis approach to the calculation of the option transaction tax

• Journal of the Korean institute of surface engineering
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• v.48 no.6
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• pp.275-282
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• 2015

The cost for maintenance (replacement cost) of Ni-superalloy components in plant industry is very expensive because of high unit price of INCONEL 718. A development of repairing technology using kinetic spray process can be very helpful for reducing the maintenance cost. However, it is very difficult to produce well-deposited INCONEL 718 layer showing high interfacial bond strength via kinetic spraying. Thus, INCONEL 718 was deposited on SCM 440 substrate and the interfacial properties were investigated, in order to elucidate the cause of hindrance to the bonding between INCONEL 718 layer and SCM 440 substrate. As a result, it was revealed that the dominant obstacle to the interfacial bonding was excessive compressive residual stress accumulated in the coating layer, resulting from low plastic-deformation susceptibility of INCONEL 718. Nevertheless, the bonding state was enhanced by the post heat-treatment through relieving the residual stress and generating a diffusion/metallurgical bonding between the INCONEL 718 deposit and SCM 440 substrate.

• 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.

• Asian Journal of Business Environment
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• v.11 no.4
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• pp.17-29
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• 2021

Purpose: The aim of this study is to explore the dynamic linkage between conditional stock market volatility and macroeconomic uncertainty of Bangladesh. Research design, data, and methodology: This study uses monthly data covering the time period from January 2005 to December 2018. A comprehensive set of macroeconomic variables, namely industrial production index (IP), consumer price index (CPI), broad money supply (M2), 91-day treasury bill rate (TB), treasury bond yield (GB), exchange rate (EX), inflow of foreign remittance (RT) and stock market index of DSEX are used for analysis. Symmetric and asymmetric univariate GARCH family of models and multivariate VAR model, along with block exogeneity and impulse response functions, are implemented on conditional volatility series to discover the possible interactions and causal relations between macroeconomic forces and stock return. Results: The analysis of the study exhibits time-varying volatility and volatility persistence in all the variables of interest. Moreover, the asymmetric effect is found significant in the stock return and most of the growth series of macroeconomic fundamentals. Results from the multivariate VAR model indicate that only short-term interest rate significantly influence the stock market volatility, while conditional stock return volatility is significant in explaining the volatility of industrial production, inflation, and treasury bill rate. Conclusion: The findings suggest an increasing interdependence between the money market and equity market as well as the macroeconomic fundamentals of Bangladesh.

• International Area Studies Review
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• v.20 no.2
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• pp.3-23
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• 2016

In this study, we used actual proof analysis, based on SVAR model according to economy theory, to observe the impact of actual and financial market of Korea, Japan, and China that have adopted quantitative easing export based strategy of growth, an unconventional monetary policy of the U.S. As a result of estimation, it appears that real effective exchange rate rise shock of Korea, Japan, and China against U.S. dollar has a negative influence on current account and index of industrial product, which are real economy. It can be implied that the result is driven from the fact that strong home currency of Korea, Japan, and China decreases price competitiveness of exports, causing negative influence on real economy. The real effective exchange rate shock against U.S. dollar appeared to decrease national bond rate of Korea and Japan, while increasing that of China. In instances of Korea and Japan, it is implied that national bond rate decreases as foreigner investment funds flow in, considering foreign-exchange profit through advanced financial market with high opening extent. On the other hand, because there are strong regulation on opening extent of Chinese financial markets, the influence seems to be greater for domestic policy, rather than a foreign influence. Lastly, Korea showed a more dramatic variable reaction to exchange rate shock compared to Japan or China. It is implied from the result that Korea is relatively more susceptible and fragile in regards of international status of economic size and currency.

• Journal of Cadastre & Land InformatiX
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• v.49 no.1
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• pp.45-63
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• 2019

Until recently, most people have invested in a traditional portfolio consisting of stocks, bonds and real estates based on the three-division method of properties in Korea. However, this study analyzed the impact of the composition of a portfolio combining representative real estate indirect investment products such as Reits and real estate funds on the investment performance. For this purpose, the empirical analysis using the mean variance model, which is the most appropriate method for the portfolio composition, was used. For variables used in this study, mixed asset portfolios were classified into Portfolio A through Portfolio G depending on the composition of assets, and the price indices selected as Kospi, Krx bond, Reits Trus Y7, Hanwha-Lasal fund, and Office (Seoul). The results are as follows; first Portfolio D, which combined bonds, stocks, Reits and Real Estate funds, and Portfolio G, which added the office, the actual real estate, were shown to have the lowest risk. second, Portfolio B composed of bonds, stocks and Reits and Portfolio D with added real estate funds had the lowest risk while Portfolio F composed of bonds, stocks, offices and real estate funds, and Portfolio G with added Reits were the most profitable. As a result, it has been analyzed that it was more effective to compose a portfolio including Reits and real estate funds, which were real estate indirect investment products that eliminated the illiquidity limitation of real estates than real estates, the traditional three-division method of properties. Therefore, it is possible to minimize the risk of investors and reduce the cost of ownership of the real estate by solving the illiquidity problem that is the biggest disadvantage of the direct investment, In addition, it is considered that it is more necessary to reinvigorate the real estate indirect investment market where small amounts can be invested.

• The Journal of the Korea Contents Association
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• v.13 no.3
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• pp.352-361
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• 2013

The purpose of this study is to analyse the impact of macroeconomic and non-macroeconomic forces on the management performance of the air transport firms and offer the useful information to the managers. To conduct the regression analysis, eight macroeconomic and non-macroeconomic variables were selected individually as an independent variable. Macroeconomic variables were the return of corporate bond, West Texas Intermediate, the unemployment rate, the money supply, the trade balance, the won to USD exchange rate, the consumer price index and the index of industrial production. And non-macroeconomic variables were Taiwan earthquake, the Asian economic crisis, the 911 terrorist attacks in the US, the Iraq war, Beijing Olympic, the outbreak of a swine flu epidemic, the 1st presidential election and the 2nd presidential election. And ROA was selected as a dependent variable. As the result of analysis, it was found that the changing rates of won to USD exchange rate and consumer price index affected the changing rate of ROA significantly. And also as the result of analysing the impact of two significant macroeconomic variables and eight non-macroeconomic variables on the changing rate of ROA, it was found that the Asian economic crisis and the outbreak of a swine flu epidemic had a negative impact on it. Therefore managers should take note of a change in macroeconomic and non-macroeconomic variables carefully to improve the management performance.