• Journal of Korea Technology Innovation Society
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• v.12 no.2
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• pp.360-387
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• 2009

In this paper, we analyse empirically the effects of internal financing on investment of innovative small and medium sized enterprises listed on Kosdaq Market of Korea Exchange. The main results of this study can be summarized as follows. Free cash flows by proxy variables of internal financing have the significant effects on R&D investment as well as fixed asset investment. Internal financing has much more effects on R&D investment of general enterprises listed on Kosdaq Market than that of venture enterprises listed on Kosdaq Market, and on R&D investment of innovative enterprises than that of non-innovative enterprises. Internal financing has more effects on asset-counted R&D investment than cost-counted R&D investment. Asset-counted R&D investment is counted in intangible assets on Balance Sheet, and cost-counted R&D investment is counted in cost on Income Statement. Internal financing has more effects on R&D investment of financial constrained enterprises than that of financial unconstrained enterprises. Financial constraints is measured by credit ratings. Faulkender and Smith (2007) emphasize that low credit ratings enterprises are more likely to face financial constraints, and they rely largely on internal financing.

• Journal of Information Technology Services
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• v.15 no.2
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• pp.51-63
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• 2016

In this study, we conducted a comparative analysis of R&D investment efficiency and operational efficiency of IT firms using Data Envelopment Analysis (DEA). We categorized thirteen sample firms into two groups-IT manufacturing and IT service-after an extensive literature review on IT industry classification. We adopted an output-oriented two-stage DEA model suggested by Banker et al. (1984) with total asset and R&D investment as input variables. Then, we constructed investment efficiency and operational efficiency by using Return on Equity (ROE) and Return on Asset (ROA) as intervening variables and operating income and Earnings Per Share (EPS) as output variables. The outcome of the analysis is summarized as follows. First of all, IT manufacturing firms were more efficient (57% on average) than IT service firms. To be specific, IT service firms showed decreasing returns to scale (DRS) with diseconomy of scale. In contrast, IT service firms showed higher operational efficiency (81.5% on average) than IT manufacturing firms. Also, we conducted a Mann-Whitney U test to compare the output of IT service firms and IT manufacturing firms. Lastly, we found a negative correlation ($R^2$ = -.754) between R&D investment efficiency and operational efficiency which infers the trade-off between two constructs

• Journal of Korean Institute of Industrial Engineers
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• v.38 no.4
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• pp.258-261
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• 2012

In this paper, I propose a new asset allocation framework to cope with the dynamic nature of the financial market. The investment performance can be much improved by protecting the capital from the market crashes, and such crashes can be pre-identified with high probabilities by regime detection analysis via a specialized unsupervised machine learning technique.

• Industry Promotion Research
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• v.8 no.2
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• pp.11-19
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• 2023

The purpose of this study is to analyze the effect of economic uncertainty on business innovation. To this end, Ahir et al. (2018) World Uncertainty Index (WUI) is selected as a proxy for economic uncertainty, while total R&D investment (RD), capitalized R&D investment (RD_A), expensed R&D investment (RD_E), and the proportion of capitalized R&D investment to total R&D investment (RD_R) are selected as variables representing business innovation. The research findings showed that economic uncertainty (WUI) had a statistically significant positive (+) relationship with total research and development investment (RD), asset-based research and development investment (RD_A), and the proportion of asset-based research and development investment (RD_R). This relationship remained the same even after controlling for managerial opportunistic accounting behavior (DACC; discretionary accruals). These findings suggest that companies focus on research and development investment as an opportunity for management innovation even in the face of economic uncertainty. The results of this study are significant in demonstrating the validity and effectiveness of government support for industrial promotion under economic uncertainty.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.135-149
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• 2020

Artificial intelligences are changing world. Financial market is also not an exception. Robo-Advisor is actively being developed, making up the weakness of traditional asset allocation methods and replacing the parts that are difficult for the traditional methods. It makes automated investment decisions with artificial intelligence algorithms and is used with various asset allocation models such as mean-variance model, Black-Litterman model and risk parity model. Risk parity model is a typical risk-based asset allocation model which is focused on the volatility of assets. It avoids investment risk structurally. So it has stability in the management of large size fund and it has been widely used in financial field. XGBoost model is a parallel tree-boosting method. It is an optimized gradient boosting model designed to be highly efficient and flexible. It not only makes billions of examples in limited memory environments but is also very fast to learn compared to traditional boosting methods. It is frequently used in various fields of data analysis and has a lot of advantages. So in this study, we propose a new asset allocation model that combines risk parity model and XGBoost machine learning model. This model uses XGBoost to predict the risk of assets and applies the predictive risk to the process of covariance estimation. There are estimated errors between the estimation period and the actual investment period because the optimized asset allocation model estimates the proportion of investments based on historical data. these estimated errors adversely affect the optimized portfolio performance. This study aims to improve the stability and portfolio performance of the model by predicting the volatility of the next investment period and reducing estimated errors of optimized asset allocation model. As a result, it narrows the gap between theory and practice and proposes a more advanced asset allocation model. In this study, we used the Korean stock market price data for a total of 17 years from 2003 to 2019 for the empirical test of the suggested model. The data sets are specifically composed of energy, finance, IT, industrial, material, telecommunication, utility, consumer, health care and staple sectors. We accumulated the value of prediction using moving-window method by 1,000 in-sample and 20 out-of-sample, so we produced a total of 154 rebalancing back-testing results. We analyzed portfolio performance in terms of cumulative rate of return and got a lot of sample data because of long period results. Comparing with traditional risk parity model, this experiment recorded improvements in both cumulative yield and reduction of estimated errors. The total cumulative return is 45.748%, about 5% higher than that of risk parity model and also the estimated errors are reduced in 9 out of 10 industry sectors. The reduction of estimated errors increases stability of the model and makes it easy to apply in practical investment. The results of the experiment showed improvement of portfolio performance by reducing the estimated errors of the optimized asset allocation model. Many financial models and asset allocation models are limited in practical investment because of the most fundamental question of whether the past characteristics of assets will continue into the future in the changing financial market. However, this study not only takes advantage of traditional asset allocation models, but also supplements the limitations of traditional methods and increases stability by predicting the risks of assets with the latest algorithm. There are various studies on parametric estimation methods to reduce the estimated errors in the portfolio optimization. We also suggested a new method to reduce estimated errors in optimized asset allocation model using machine learning. So this study is meaningful in that it proposes an advanced artificial intelligence asset allocation model for the fast-developing financial markets.

• Journal of Korea Technology Innovation Society
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• v.12 no.2
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• pp.291-311
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• 2009

Intellectual Property(IP) investment and its management are an key driver to create corporate value and intangible asset value through corporate's competitiveness. The purposes of this study are to survey capability of IP management and assess the effects of IP investment and its management on the separation into groups of intangible asset value. In order to attain those purposes of this study, sample companies were taken and categorized into three groups by the level of intangible asset value ratio, and data for IP investment such as R&D expenditure and advertising expenditure were collected from 90 manufacturing companies, and data for IP management capability about patent, design and brand were taken through survey. The final results showed as followed: First, IP management capability were generally not sufficient in the results of survey. Second, mean vector for the four variables were significantly different among three groups in multivariate analysis variance. Third, the order of their contribution to separating the groups were R&D expenditure, advertising expenditure, patent management, management of design and brand in canonical variate analysis. Fourth, R&D and patent management capability were significantly related to the separation of three groups, while advertising expenditure were not significant and management of design and brand were not sure of Significance in multinomial logit discriminant analysis. Fifth, exploratory power of the discriminant model were estimated by 53% in classification analysis. Finally, strategic policy for IP investment and its management should be taken urgently to create intangible asset value and to improve the capability of its management.

• Journal of Satellite, Information and Communications
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• v.12 no.4
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• pp.125-130
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• 2017

In recent, a rapid growth of the air tourism and leisure industry and the massive amount of investing plan by the national government, the local authorities have drawn new investment of new market entrance companies and increasing investment of current companies which have been diversified their business area. Whereas, few research literature on the asset structure formation which is the base of investment activity has been studied. In this study, we suggest the results of the impact of the asset structure to the managerial outcomes by the analysis of the asset structure of air transport industry, the sea transport industry, and the ground passenger transport industry that have been representing of the air tourism and leisure industry. As results of this study, we suggest the reference point of future invest direction and the way of improving effectiveness of air tourism and leisure industry.

• International Journal of Human Ecology
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• v.7 no.2
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• pp.53-62
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• 2006

The purpose of this study is to examine the changes in financial structure of the self-employed brought on the economic crisis in Korea.. We use financial ratio analysis, such as income to expenditure ratio, liquidity ratio, debt ratio, and capital accumulation ratio to analyze financial well-being of self-employed households. This study used a 1997 and 1998 Korean Household Panel Study collected by Daewoo Economic Research Institute. The average amount of holding of each type of asset showed that the investment of self-employed households decreased in the banking industry and the stock market in 1998 compared to 1997. On the other hand, asset allocation in bond and real estate increased, which implied preference for a stable type of asset with the increase in uncertainty of the future and economic instability. Devaluation of real estate allowed households to easily obtain real estate and increase preference for asset allocation in real estate after the crisis. The changes in financial ratio for the year 1998 shows that such ratios as income to expenditure, liquidity, and capital accumulation, decreased compared to the year 1997. Among those ratios, the income to expenditure ratio showed the biggest decline because of reduced income of self employed households. The results implied that the income structure of the self-employed is unstable, thus the self-employed were likely to be greatly affected during the economic downturn. Earners have more average income and net assets than the self-employed. However, using financial ratios, it was found that self-employed households were more stable than employees. The results shows that the financial ratio analysis is better tool to estimate households financial status. Implications for financial educators, counselors, and planners are offered. The results will provide implications for policy makers to establish appropriate policies for the self-employed and help them financially survive.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.4
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• pp.177-187
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• 2015

Although actual business environment is getting difficult and hard, IT companies tend to shy away from of annual investment. Many firms have already reached the 25 percent level. However, the profit and the result of their annual investment needs to be evaluated objectively. IT investment analysis usually proceeds by comparing benefits and costs of an IT investment. Much of the problem derives from the historical treatment of IT as an overhead expense rather than a capital asset. What is most worrying about the current situation is the pressure to take a very short-term view of IT. Therefore, this research aims to analyses and justify the necessity of Visionary IT Investment. For this, it is crucial to identify the factors, which affect positively Visionary IT Investment and understand the role of CIO and explain the result of Visionary IT Investment, which is differed to related business and by different business environment. As a result of this study, the legitimacy of IT Investment is proved through analyzing the business value of not investing and cost-avoidance strategies.

• Proceedings of KHEA Conference
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• 1997.07a
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• pp.50-50
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• 1997