• The Journal of Asian Finance, Economics and Business
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• 제7권8호
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• pp.681-693
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• 2020

This study sees a critical gap in the previous body of research, which it seeks to fill; the disclosure of the unemployment ratio correlation has only been measured by the level of economic growth. This study is to add investment variables and government expenditure variables that objectively aim to measure the level of effectiveness in handling the unemployment ratio, which is then a measurement of the effectiveness of unemployment. Economic growth is measured by its impact on income inequality through empirical, conceptual relationships as a critical review and economic strategy for the future. The research uses secondary data on Indonesian macro and microeconomics since 2003-2018, then testing uses a quantitative approach to correlation, regression, and scatterplot. The results of this study show correlations between variables, and volatiles on the graphs show a similar trend. In other words, variables are bound together and support each other. The strategy of prioritizing the scale of government expenditure and investment to reach the target is the primary concern, so that the economic cycle can be optimal and equipped to face the possibility of an economic recession in the future. Many factors cause complex income inequality, though investment does not show a correlation to income inequality.

• 산업경영시스템학회지
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• 제46권4호
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• pp.63-73
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• 2023

This study explores modern portfolio theory by integrating the Black-Litterman portfolio with time-series clustering, specificially emphasizing K-shape clustering methodology. K-shape clustering enables grouping time-series data effectively, enhancing the ability to plan and manage investments in stock markets when combined with the Black-Litterman portfolio. Based on the patterns of stock markets, the objective is to understand the relationship between past market data and planning future investment strategies through backtesting. Additionally, by examining diverse learning and investment periods, it is identified optimal strategies to boost portfolio returns while efficiently managing associated risks. For comparative analysis, traditional Markowitz portfolio is also assessed in conjunction with clustering techniques utilizing K-Means and K-Means with Dynamic Time Warping. It is suggested that the combination of K-shape and the Black-Litterman model significantly enhances portfolio optimization in the stock market, providing valuable insights for making stable portfolio investment decisions. The achieved sharpe ratio of 0.722 indicates a significantly higher performance when compared to other benchmarks, underlining the effectiveness of the K-shape and Black-Litterman integration in portfolio optimization.

• 기술혁신연구
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• 제27권1호
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• pp.1-43
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• 2019

본격적인 뉴노멀(New Normal) 시대에 접어들면서 중소기업의 중요성은 더욱 강조되는 추세이다. 우리나라도 경제성장과 일자리 창출을 위하여 중소기업 지원을 강화하고 있으며, 특히 R&D투자와 기술혁신을 촉진하기 위하여 국가연구개발사업과 조세지원제도를 확충하는 등 다양한 정책수단을 강구하고 있다. 하지만 중소기업의 R&D투자를 유인하기 위한 직 간접지원의 효용성에 대해서는 연구자마다 의견이 엇갈리고 있으며, 두 정책수단 간 최적의 조합을 모색하려는 논의는 거의 이루어지지 않고 있는 실정이다. 중소기업 정책의 주무부처가 격상되었고, 중소기업을 지원하는 정부 R&D투자의 규모가 지속적으로 증가하고 있는 현 시점이 직 간접지원의 정책조합을 비롯한 중장기적 방향성에 대하여 논의할 적기로 판단된다. 본 연구에서는 그간 국내 학계에서 발표되었던 유관 연구 32건을 취합하여 체계적 문헌고찰과 메타분석을 시도하였다. 이러한 작업은 단순히 정부의 정책지원이 중소기업의 자체 R&D투자를 유인하는지 검증하는 수준을 넘어, 그간의 관련 논쟁을 종합하고 실증적으로 정리한다는 의의도 있다. 본 연구의 메타분석 결과, 대기업은 조세지원 위주로, 중소기업은 보조금 위주로 지원하는 것이 효과적이었다. 하지만 현재 우리나라의 중소기업 R&D지원은 직접지원에 대한 비중이 과도하게 높아서 간접지원 비중을 점진적으로 늘릴 필요성이 제기된다.

• 경영정보학연구
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• 제25권4호
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• pp.27-45
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• 2023

정보통신기술의 발달로 정보보호의 중요성이 커졌지만, 기업은 제한된 예산 내에서 적절한 대책을 선택하는 데 어려움을 겪고 있다. Sönmez and Kılıç(2021)는 정보 보안 침해를 완화하기 위한 최적의 투자 조합을 결정하기 위해 AHP 및 혼합 정수 계획을 사용하는 모델을 제안했다. 그러나 1) 보안 위협에 대한 보안 대책의 효과를 객관적으로 측정하지 못하고, 2) 투자로 인한 위험 감소가 투자 이전에 측정한 위험 수준을 초과하는 비현실적인 현상이 발생하고, 3) 여러 위협에 대해 단일 대응책을 사용할 때 중복된 투자가 이루어진다는 한계가 있었다. 본 연구에서는 베타 확률 분포를 사용하여 대책의 효과를 객관적으로 정량화하고, 위험 감소 수준이 투자 이전에 측정된 위험 수준을 초과하지 않고 보안 대책이 중복 투자되지 않도록 최적화 모델을 개선했다. 개선된 모델을 국내 중소기업을 대상으로 실증분석한 결과, Sönmez and Kılıç(2021)의 최적화 모델보다 더 나은 결과를 도출했다. 개선된 최적화 모델을 사용하면 정보보호 비용, 수량, 대책 효율성을 고려하여 고정된 예산 내에서 최적의 대책별 투자 포트폴리오를 도출할 수 있고, 정보 보안 예산을 확보하고 정보 보안 위협을 효과적으로 해결하는데 도움이 될 것이다.

• 기술혁신연구
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• 제25권3호
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• pp.51-82
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• 2017

본 연구는 내생적 성장모형을 통해 경제성장과 사회적 효용 관점에서 기초연구 예산의 적정 비중 및 그 규모를 다룬다. 이에 본 연구는 지식스톡을 고려한 내생적 성장모형을 구축하고, 이를 토대로 기초연구예산의 적정 여부를 판단하는 하나의 기준을 제시한다. 아울러 정부의 투자 비중과 기초연구 투자 비중 간의 이론적 적정 비율은 정부자본에 대한 산출 탄력성과 지식스톡에 대한 산출 탄력성 간의 비율과 같다는 사실도 도출하였다. 이러한 사실에 기대어 기존 선행연구들의 결과에 따라 필요 파라미터 값들을 특정한 후 적정 규모를 산정하고, 실제 투자 규모와 비교함으로써 유의미한 시사점을 도출해보았다. 이상 본 연구의 결과는 적정 투자 규모 수준에 대한 새로운 기준과 그 규모에 대한 대략적인 수치를 제시하고 있기 때문에, 향후 기초연구정책 수립과 관련하여 합리적인 예산배분 조정을 위한 기초자료로서 크게 기여할 수 있을 것으로 기대된다. 다만, 본 연구에서 제시한 최적의 해는 경제적 관점에서 도출한 것이므로 해석함에 있어 주의할 필요가 있다.

• 산업경영시스템학회지
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• 제46권4호
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• pp.152-159
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• 2023

This study endeavors to enrich investment prospects in cryptocurrency by establishing a rationale for investment decisions. The primary objective involves evaluating the predictability of four prominent cryptocurrencies - Bitcoin, Ethereum, Litecoin, and EOS - and scrutinizing the efficacy of trading strategies developed based on the prediction model. To identify the most effective prediction model for each cryptocurrency annually, we employed three methodologies - AutoRegressive Integrated Moving Average (ARIMA), Long Short-Term Memory (LSTM), and Prophet - representing traditional statistics and artificial intelligence. These methods were applied across diverse periods and time intervals. The result suggested that Prophet trained on the previous 28 days' price history at 15-minute intervals generally yielded the highest performance. The results were validated through a random selection of 100 days (20 target dates per year) spanning from January 1st, 2018, to December 31st, 2022. The trading strategies were formulated based on the optimal-performing prediction model, grounded in the simple principle of assigning greater weight to more predictable assets. When the forecasting model indicates an upward trend, it is recommended to acquire the cryptocurrency with the investment amount determined by its performance. Experimental results consistently demonstrated that the proposed trading strategy yields higher returns compared to an equal portfolio employing a buy-and-hold strategy. The cryptocurrency trading model introduced in this paper carries two significant implications. Firstly, it facilitates the evolution of cryptocurrencies from speculative assets to investment instruments. Secondly, it plays a crucial role in advancing deep learning-based investment strategies by providing sound evidence for portfolio allocation. This addresses the black box issue, a notable weakness in deep learning, offering increased transparency to the model.

• 상하수도학회지
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• 제18권2호
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• pp.145-154
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• 2004

A long-term sewer rehabilitation project consuming an enormous budget needs to be conducted systematically using an optimization skill. The optimal budgeting and ordering of priority for sewer rehabilitation projects are very important with respect to the effectiveness of investment. In this study, the sewer rehabilitation optimization model using fast-messy genetic algorithm is developed to suggest a schedule for optimal sewer rehabilitation in a subcatchment area by modifying the existing GOOSER$^{(R)}$ model having been developed using simple genetic algorithm. The sewer rehabilitation optimization model using fast-messy genetic algorithm can improve the speed converging to the optimal solution relative to GOOSER$^{(R)}$, suggesting that it is more advantageous to the sewer rehabilitation in a larger-scale subcatchment area than GOOSER.

• East Asian mathematical journal
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• 제38권3호
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• pp.277-292
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• 2022

This study investigates the convergence of the optimal consumption and investment policies in a binomial-tree model to those in the continuous-time model of Merton (1969). We provide the convergence in explicit form and show that the convergence rate is of order ∆t, which is the length of time between consecutive time points. We also show by numerical solutions with realistic parameter values that the optimal policies in the binomial-tree model do not differ significantly from those in the continuous-time model for long-term portfolio management with a horizon over 30 years if rebalancing is done every 6 months.

• KEPCO Journal on Electric Power and Energy
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• 제3권1호
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• pp.23-28
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• 2017

The life management technology becomes important as the failure risk of the aged power transformers increases. Asset management technology, therefore, has been developed to evaluate the remaining life and build replacement strategies of power transformers, which enables an optimal investment decisions based on reliability and economic feasibility. The remaining life assessment technology uses data related to such as installation, operation, maintenance, refurbishment, and disposed history of power transformers. The optimal investment decision additionally uses data related to failure and social costs. To develop the asset management technology in power transformers, it is important to find deterioration parameters directly indicating degradation of power transformers. In this study, 110,000 DGA data during the past 35 years have been analyzed in order to find the deterioration parameters related to the degradation of power transformers. The alarm rates of combustible gases ($H_2$, $C_2H_2$, $C_2H_4$, $CH_4$, $C_2H_6$), TCG CO, and $CO_2$ were analyzed as deterioration parameters. The origin of the gas was discussed in connection with discharge, overheating and insulation aging.

• 전기학회논문지
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• 제67권8호
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• pp.1009-1018
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• 2018

As the generation of renewable energy increases rapidly, the stability of the grid due to its intermittency becomes a problem. The most appropriate way to solve this problem is to combine and operate the renewable generators with the ESS(Energy Storage System). However, since the revenues of operating the ESS are less than the investment cost, many countries are implementing various incentive policies for encouraging investment of the ESS. In this paper we estimated optimal capacity of the ESS to maximize profits of renewable energy generation businesses under the incentive policy of Korea and analyzed the impact of the incentive policy on the future electric power system of Jeju island. The simulation results show that the incentive policy has significantly improved the profitability of the renewable energy businesses generation business. But the volatility of the net demand has increased as the energy stored in the ESS is discharged intensively at the time of the incentive application.