• International Journal of Quality Innovation
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• v.8 no.1
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• pp.40-75
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• 2007

In the early industrial age which with high intensity of machine and labor, using financial measurement index was good enough to tie in company's mechanization and philosophy of management and been in efficiency. But being comply with "New Economic age," a new economic environment is full of knowledge and information, the enterprise competition had changed from tangible assets, plants to intangible innovation ability of knowledge. As recognizing the new tendency by enterprise, they value gradually the growth and influence from learning. Practice of organization learning not only needs firm structure and be in coordination with both hardware and software, but also needs an affect measurement model to offer enterprise to estimate learning performance. It's a good instrument of financial performance measure mold in the past years, But it's for measuring the past, couldn't formulate enterprise trend to future, hard to estimate investment for future, such as development of products, organization learning, knowledge management etc, as which intangible assets and knowledge ability just the key factors of being win around competition environment in the future. In 1992, Kaplan and Norton brought up Balance Scorecard (BSC) on Harvard Business Review, as an instrument helping enterprise to measure performance, which is being considered to be a most influence management instrument. It added non-financial index such as customer, internal process and learning growth besides traditional financial index, as offering enterprise an index to measure and manage intangible assets and intellectual property. As being aware of organization learning is hard to be ignored in the new economic age, this research is based on learning and growth of BSC, and citing one national material company try to let the most difficult measurement performance of organization learning, to be estimate through BSC, analyze of factor and individual case, to discuss the company how to make the related strategy and vision of organization learning to develop learning and growth of the structure of BSC, subject the matter of out put factors to be discussed, and measure the outcomes as a result of research. The research affect offers (1) the base implement procedure of carrying out BSC; (2) the reference of formulating measurement index while enterprise using BSC to estimate performance of organization learning; (3) the possibility bottleneck maybe forcing while carrying out BSC, to be an improvement or preventive for enterprise.

• Journal of the Korea Society of Computer and Information
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• v.8 no.3
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• pp.113-123
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• 2003

Many researches on the application of neural networks for making financial index prediction have proven their advantages over statistical and other methods. In this paper, a neural network model is proposed for the Buying, Holding or Selling timing prediction in stocks by the price index of stocks by inputting the closing price and volume of dealing in stocks and the technical indexes(MACD, Psychological Line). This model has an equalized multi-layer arithmetic function as well as the time series prediction function of backpropagation neural network algorithm. In the case that the numbers of learning data are unbalanced among the three categories (Buying, Holding or Selling), the neural network with conventional method has the problem that it tries to improve only the prediction accuracy of the most dominant category. Therefore, this paper, after describing the structure, working and learning algorithm of the neural network, shows the equalized multi-layer arithmetic method controlling the numbers of learning data by using information about the importance of each category for improving prediction accuracy of other category. Experimental results show that the financial index prediction using the equalized multi-layer arithmetic neural network has much higher correctness rate than the other conventional models.

• Journal of Information Technology Services
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• v.19 no.6
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• pp.145-159
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• 2020

Because of the recent development of information and communication technology, companies are exposed to various media such as blogs, social media, and YouTube. In particular, exposed news affects the company's reputation. So, while positive news can improve corporate value, negative news can lead to financial losses for the company. In this study, we redefine corporate reputation as social responsibility, vision and leadership, financial performance, products and services through existing literature, and conducted an AHP survey with a total of four components to calculate the weight of each factor. As a result of the calculation, the proportion of financial performance was the highest at 0.41, and products and services, vision and leadership, and social responsibility were the lowest. In addition, in order to measure the reputation of a company, it is classified as a component that defines online news using the LDA technique. In addition, through sentiment analysis, an index for each corporate reputation factor was derived, and the reputation index was calculated by combining it with the AHP analysis result, and Spearman ranking correlation analysis was performed to secure the validity of the research results. Therefore, the significance of this study is that the definition and importance of the constituent factors can contribute to the future planning and development direction of the company, and also contribute to the derivation of the corporate reputation index. This study is significant in that a new analysis methodology that applied AHP analysis results to sentiment analysis was suggested.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.3
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• pp.499-506
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• 2017

Consideration of influential factors through division of capital market sector and interest rate sector to find and resolve the problems in current housing market and leasing market will become an important index to prepare measures for stabilization of housing sales market and housing lease market. Furthermore, a guideline will be provide you with preliminary data using Big Data to prepare for sudden price fluctuation because expected economic crisis, stock market situation, and uncertain future financial crisis can be predicted which may help anticipate real estate price index such as housing sales price index and housing lease price index.

• The Journal of Industrial Distribution & Business
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• v.9 no.4
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• pp.19-26
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• 2018

Purpose - This study measures how competitive securities broker-dealers are in the Korean financial markets. It aims to test whether the markets are perfectly competitive or monopolistic since the global financial crisis of 2008. Research design, data, and methodology - We apply the method developed by Panzar and Rosse (1987), H-statistics, which offers an index for the competitiveness as well as statistical tests. The dataset in use is retrieved mainly from the quarterly statements of the financial services companies by the Financial Statistics Information System of the Financial Supervisory Service. General information on officers and employees is utilized in addition to balance sheets and income statements of securities companies. Results - H-statistics for 2009-2015 is about 0.7 that is a robust estimate regardless of model specifications such as full trans-log, partial trans-log, and Cobb-Douglas regression equations. H-statistics for each year is also computed in similar ways in that it varies between 0.3 and 0.9. Conclusions - Since the global financial crisis, H-statistics concludes that securities broker-dealer markets in Korea is neither perfectly competitive nor monopolistic. It evidences that the markets are rather monopolistically competitive. The trend in annual H-statistics leads to the same conclusion but the result is not such stable that overall H-statistics implies.

• Economic Analysis
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• v.25 no.3
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• pp.70-99
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• 2019

Using a stochastic volatility-in-mean VAR model consisting of the KOSPI index, the foreign exchange rate, the government bond rate, and the credit spread, this study investigates the effects of financial market uncertainty on financial markets. We find that higher uncertainty has recessionary effects on financial markets. The effects are especially stronger in equity markets and in won-dollar exchange markets. We also find that the effects of uncertainty become stronger during times of financial market stress compared to normal times. Finally, the results imply that financial market uncertainty may potentially affect the real sector, too.

• Asia-Pacific Journal of Business
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• v.15 no.1
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• pp.209-223
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• 2024

Purpose - This article analyzes the impact of macroeconomic variables of the United States, China, and Korea on KOSPI and VKOSPI, in that United States and China have a great influence on Korea, having an export-driven economy. Design/methodology/approach - The influence of US, China, and Korea interest rates, industrial production index, consumer price index, US employment index, Chinese real estate index, and Korea's foreign exchange reserves on KOSPI and VKOSPI is analyzed on monthly basis from Jan 2012 to Aug 2023, using multifactor model. Findings - The KOSPI showed a positive relationship with the U.S. industrial production index and Korea's foreign exchange reserves, and a negative relationship with the U.S. employment index and Chinese real estate index. The VKOSPI showed a positive relationship with the Chinese consumer price index, and a negative relationship with the U.S. interest rates, and Korean foreign exchange reserves. Next, dividing the analysis into two periods with the Covid crisis and the analysis by country, the impact of US macroeconomic variables on KOSPI was greater than Chinese ones and the impact of Chinese macroeconomic variables on VKOSPI was greater than US ones. The result of the forward predictive failure test confirmed that it was appropriate to divide the period into two periods with economic event, the Covid Crisis. After the Covid crisis, the impact of macroeconomic variables on KOSPI and VKOSPI increased. This reflects the financial market co-movements due to governments' policy coordination and central bank liquidity supply to overcome the crisis in the pandemic situation. Research implications or Originality - This study is meaningful in that it analyzed the effects of macroeconomic variables on KOSPI and VKOSPI simultaneously. In addition, the leverage effect can also be confirmed through the relationship between macroeconomic variables and KOSPI and VKOSPI. This article examined the fundamental changes in the Korean and global financial markets following the shock of Corona by applying this research model before and after Covid crisis.

• Land and Housing Review
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• v.14 no.3
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• pp.55-75
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• 2023

Based on prior studies on real estate policy, tax policy, and financial policy, this study examined how tax policy and financial policy affected real estate prices using monthly data from January 2014 to December 2021. We performed a VAR model using unit root tests, cointegration tests, as well as conducted impulse response analysis and variance decomposition analysis. The results are as follows. First, the tax regulation index and the financial regulation index had no discernible impact on housing prices. Specifically, a one-sided stabilizing regulatory policy was ineffective and, instead, led to unintended side effects, such as price increases resulting from reduced transaction volume. Secondly, mortgage rates had a negative impact on the housing sale price index. In other words, an increase in interest rates might led to a decrease in housing prices. Thirdly, an increase in the transfer difference, which involves capital gains tax, has a positive effect on housing prices. This led to rising housing prices because the transfer taxes were shifted to buyers, causing them to hesitate to make purchases due to the increased tax burden. Fourthly, both acquisition taxes and mortgage loans had relatively little impact on housing prices.

• The Journal of the Korea Contents Association
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• v.9 no.1
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• pp.407-416
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• 2009

It is evident that a financial feasibility study based on the economic analysis has been theoretically and practically accepted in the aspect of its adequacy. However, it is not easy to apply in the practical business affairs since there exist some difficulties on the economic analysis and the interpretation of the result because of the difficulty of the estimation of the discount rate. This study aims to suggest a method of the financial feasibility study based on the economic analysis. The results of this study are as follows. First, this study can increase the reliance and adequacy of the economic analysis result by suggesting a method of estimating the discount rate by means of the proxy ${\beta}$ method in the practical way. Second, this study can provide the overall frame of the financial feasibility study based on the economic analysis method (namely, Net Present Value Method internal rate of return, profit index method and payback period method)which use discount rate and cash flow. Third, this study can suggest an practical analysis skill required in each step of the financial feasibility study.

• Journal of Family Resource Management and Policy Review
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• v.16 no.3
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• pp.153-176
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• 2012

This study gives an account of the state of baby-boomer households in regard to assets and liabilities utilizing the 2006 Household Asset Survey and the 2011 Survey of Household Finances. Using the data gathered from each year, this study examined the proportion of households who had each type of asset and liability, and the amount of them. This study also compared the amount of assets and liabilities of baby-boomer households with those of non baby-boomer households in 2006 and 2011 respectively. Finally, this study examined the amount of change and composition ratio of assets and liabilities of baby-boomer households between 2006 and 2011. Selected financial ratios were also presented for both years. Major findings are as follows. The average asset amount for baby-boomer households was approximately 296 million in 2006 and 392 million in 2011. Of total assets, 78% and 76.5% were real assets in 2006 and 2011 respectively. The average financial assets of 2006 baby-boomer households were approximately 66 thousand and the average amount of debt was 42 thousand. For 2011 baby-boomer households, the average amount of financial assets was 92 thousand and the average amount of debt was 73 thousand. Results from the 2011 survey showed that baby-boomer households had a significantly higher proportion of total assets, total debt, and net worth than non baby-boomer households. The proportion of savings, saving insurance, stocks, and mutual funds were significantly higher for baby-boomer households than non baby-boomer households in 2011. In regard to financial ratios, the emergency fund index and debt burden index were appropriate to the guidelines of asset quality, although the propensity to investment indexes were not.