• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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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.

• Korean System Dynamics Review
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• v.12 no.1
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• pp.75-87
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• 2011

Congestion problems can be approached from the viewpoint of system dynamics theory. The relationship between road capacity and congestion can be explained by the 'relative control' archetype among four system archetypes suggested by Wolstenholme. There is a balancing feedback loop between road capacity and road congestion. However, there is another balancing loop between road congestion and car traffic volume, which keeps disrupting the equilibrium of the former loop. A system dynamics model, which is based on a partial adjustment model of induced traffic in the literature, is built to simulate three road building scenarios: 'Expanding investment', 'Balancing investment' and 'Frozen road investment' scenarios. The 'Expanding investment' scenario manages to drop congestion levels by 9% over 30 years, however, causing much higher emissions of $CO_2$ than other scenarios. The trade-off relationship between congestion levels and environmental costs must be taken into consideration for road investment policies.

• Journal of Korea Port Economic Association
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• v.19 no.2
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• pp.33-53
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• 2003

The purpose of this paper is to investigate the effectiveness of port investemnt which is one of the important elements for measuring the port efficiency by using congestion approach of DEA(Data Envelopment Analysis). Congestion is said to be present when increases in inputs result in input reductions. Congestion approach takes the forms of weak input disposability and strong input disposability. Empirical analysis by using congestion approach in this paper identified inefficiencies in the inputs including port investment, and indicated inefficient ports like the ports of Sokcho, Gunsan, Pohang, and Seoguipo which shows the large amount of slacks with congestion especially in terms of port investment. Therefore these ports should examine the reason about the inefficiency of port investment. The main policy implication based on the findings of this study is that The Ministry of Maritime Affairs & fisheries in Korea should introduce congestion approach when the amount of port investment to each port is decided.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.41
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• pp.33-40
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• 1997

The main objective of this study is to analysis the relationship between productivity measurement model which describe and explain R&D(Research & Development) productivity based on production function of Cobb-Douglas and the structure of the R&D investment. The model focuses on the variables related to R&D investment in order to measure the efficiency of R&D largely. So, the proposed model describe the relationship between output(or / input) and factors of production such as capital cost, labor cost and R&D expense, etc. These factors are associated with a signigicant positive correlation between productivity and R&D investment.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.377-396
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• 2023

As the cryptocurrency market continues to grow, it has developed into a new financial market. The need for investment strategy research on the cryptocurrency market is also emerging. This study aims to conduct an empirical analysis on an investment methodology of cryptocurrency that combines short-term trading strategy and deep learning. Daily price data of the Ethereum was collected through the API of Upbit, the Korean cryptocurrency exchange. The investment performance of the experimental model was analyzed by finding the optimal parameters based on past data. The experimental model is a volatility breakout strategy(VBS), a Long Short Term Memory(LSTM) model, moving average cross strategy and a combined model. VBS is a short-term trading strategy that buys when volatility rises significantly on a daily basis and sells at the closing price of the day. LSTM is suitable for time series data among deep learning models, and the predicted closing price obtained through the prediction model was applied to the simple trading rule. The moving average cross strategy determines whether to buy or sell when the moving average crosses. The combined model is a trading rule made by using derived variables of the VBS and LSTM model using AND/OR for the buy conditions. The result shows that combined model is better investment performance than the single model. This study has academic significance in that it goes beyond simple deep learning-based cryptocurrency price prediction and improves investment performance by combining deep learning and short-term trading strategies, and has practical significance in that it shows the applicability in actual investment.

• Journal of Distribution Science
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• v.11 no.12
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• pp.13-23
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• 2013

Purpose - There is a dominant opinion that medium and small enterprises in the Korean economy have not developed qualitatively but only towards quantitative growth and, therefore, the unbalanced structure between large enterprises and those that are medium and small has worsened. In particular, this rapid industrialization causes after-effects such as polarization as well as anti-business sentiment, the collapse of the middle class, and hostility against the establishment. The consensus contends that it is difficult for Korea to be an advanced nation without resolving these problems. This paper attempts to suggest a co-prosperity model by limiting the focus to business relations with medium and small manufacturers (with regard to investment among the various co-prosperity institutions of POSCO). These co-prosperity institutions have been established in POSCO; however, it is thought that the development of a co-prosperity model regarding investment in medium and small manufacturers will help many needy investment manufacturers. Research design, data, and methodology - This study analyzes research on the co-prosperity model, using it to examine Korean cases and foreign cases. The co-prosperity model has been continuously extended but is determined to be seriously insufficient. The purpose of this study is to develop the Korean co-prosperity model by reinterpreting it in various aspects. In order to develop the Korean co-prosperity model, this study suggests the case of the establishment of the co-prosperity model by POSCO with medium and small manufacturers with regard to investment. This model is expected to be presented to many enterprises as the future co-prosperity model. Results - To date, analysis of the co-prosperity model itself and the co-prosperity model through the case of POSCO have been suggested. As empirical studies on co-prosperity in Korea are not sufficient, successful models of co-prosperity should be developed in various aspects in future. It is expected that through this study, medium and small manufacturers would have an opportunity to find various growth engines by actively using the cooperation platform and establishing optimized competitiveness of steel material through a steel business model. The ecosystem of enterprises may evolve and be healthier by making more joint products through productive business relationships between large enterprises and those that are medium and small. From the enterprises' ecosystem viewpoint, cooperation between such businesses rather than one-way support is identified as an essential element for the security of inter-competitiveness. Conclusions - Infrastructure should be established to form a dynamic industry ecosystem not by transient efforts in co-prosperity, but by an entire culture of co-prosperity across industries. In this respect, the leading role of public institutions needs to be intensified initially. In addition, the effects of co-prosperity should be extended to blind spots of policies such as third party companies and regions. A precise co-prosperity monitoring system should be established to continuously conduct and extend these efforts.

• Journal of Korea Trade
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• v.27 no.3
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• pp.161-178
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• 2023

Purpose - purpose of this paper is to analyze the effects of the investment facilitation levels of 11 RCEP countries (excluding Myanmar, Brunei, and Laos due to lack of data) on China's outward foreign direct investments(OFDI) using balanced panel data from 2010 to 2019. Design/methodology - First, four investment facilitation measurement indicators (regulatory environment, infrastructure, financial market, ease of doing business) were selected,investment facilitation scores of the 11 countries were obtained using the principal component analysis, an investment gravity model was established with nine explanatory variables (investment facilitation level, market size, population, geographic distance, degree of opening, tax level, natural resources, whether the country is an APEC member or not, and whether a valid bilateral investment treaty with China has been concluded) were used to establish an investment gravity model, and regression analyses were conducted with OLS and system GMM. Findings - The results of the regression analyses showed that investment facilitation levels had the greatest effect on China's OFDI, all four first-level indicators had positive effects on China's OFDI, and among them, the institutional environment had the greatest effect. In addition, it was shown that explanatory variables such as market size, population, geographical distance, degree of openness, natural resources, and whether or not a valid bilateral investment treaty has been concluded would have positive effects on China's OFDI, while tax levels and APEC membership would impede China's OFDI to some extent. Originality/value - Since the Regional Comprehensive Economic Partnership (RCEPT) came into effect not long ago, there are not so many studies on the effects of investment facilitation levels of RCEP member states on China's OFDI, and the investment facilitation measurement index constructed in this paper is relatively systematic and scientific because it includes all the contents of investment facilitation related to the life cycle of company's foreign direct investments.

• Korea Trade Review
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• v.41 no.3
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• pp.177-198
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• 2016

China has retained economic growth rate of average 9% for more than ten years recently after China introduced capitalistic market economy system in 1979 by Deng Xiaoping. China has attracted foreign direct investment for a long time because it has retained very high economic growth rate, low labor cost, and various policies for foreign investors. This paper tries to analyse the determinants of foreign direct investment inflow after reform-opening of China with empirical analysis methods utilizing each province·city's specific characteristics by using the panel data from 1985 to 2013. For the empirical analysis we use random effect model, fixed effect model, pooled OLS, and random coefficient model. The results by pooled OLS and random coefficient model are presented for the comparison with the main results in the process of research. The research shows the results by fixed effect model are better than those by random effect model after doing Hausman's test. The results shows that GRDP, capital stock, and telecommunication exert a positive relationship with foreign direct investment, while express way variable exerts a negative one. China's education level surprisingly does not attract foreign direct investment even though it is not at a critical level. Therefore, the Chinese government should try to increase national income level as it symbolizes market size; encourage domestic investment; and construct high quality telecommunication infrastructure.

• The Journal of Asian Finance, Economics and Business
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• v.2 no.2
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• pp.5-12
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• 2015

The authors calculate the long-term predictability of GDP, domestic demand, investment, and net exports for Guangdong province, P.R. China from 2000 to 2013. A vector autoregressive (VAR) model with quarterly data for this period is first co-integrated then the Granger causality test is applied to empirically assess the relationships among gross domestic product (GDP), consumption, investment, and net exports. There is a strong causality effect between investment and net exports in Guangdong province. However, the variance decomposition results indicate that exports respond to foreign shocks rather than domestic ones, making their impact on the Guangdong economy to predict. Results show the stimulating effect of domestic demand on GDP is larger than the stimulating effect of net exports and much larger than even the stimulating effect of investment. The analysis suggests that there are dynamic influences with various levels of persistence between GDP, consumption, investment, and net exports. Macroeconomic policy adjustments are urgently required to expand domestic demand and thereby stimulate economic growth in Guangdong province.

• Korea Trade Review
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• v.44 no.1
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• pp.115-127
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• 2019

In recent years, the Indian market has gained worldwide attention in the global trading business environment. Korean companies are also seeking to enter the indian market, and their foreign trade investment strategy is based on the Global Value Chain(GVC). In this study, we examine difference from traditional investment strategy to GVC investment strategy in the age of 4IR(fourth industrial revolution) through using POLS model(pooled least square), FEM(fixed effect model), and REM(randomized effect model). Based on the analysis of 84 monthly data related to the FDI and international trade effects between Korea and India, the following results were found. As Korean companies increased their share of export to the Indian market and export to the Indian market, the number of new companies directly invested in overseas market increased. However, the amount of import into the Indian market was relatively low in relation to the number of new companies directly in overseas markets. As a result of analyzing the investment strategy of the GVC in India, the GVC has shifted from manufacturing to process upgrading to enter the GVC on Smile Curve.