Artificial intelligence technology, which is the core of the 4th industrial revolution, is making intelligent judgments through deep learning techniques and machine learning that it is impossible to predict if it is applied to stock prediction beyond human capabilities. In US fund management companies, artificial intelligence is replacing the role of stock market analyst, and research in this field is actively underway. In this study, we use BLSTM to reduce errors that occur in unidirectional prediction of the existing LSTM method, reduce errors in predictions by predicting in both directions, and macroscopic indicators that affect stock prices, namely, economic growth rate, economic indicators, interest rate, analyze the trade balance, exchange rate, and volume of currency. To help stock investment by accurately predicting the target price of stocks by analyzing the PBR, BPS, and ROE of individual stocks after analyzing macro-indicators, and by analyzing the purchase and sale quantities of foreigners, institutions, pension funds, etc., which have the most influence on stock prices.
Journal of the Korea Society of Computer and Information
/
v.25
no.5
/
pp.47-56
/
2020
The stock index is used not only as an economic indicator for a country, but also as an indicator for investment judgment, which is why research into predicting the stock index is ongoing. The task of predicting the stock price index involves technical, basic, and psychological factors, and it is also necessary to consider complex factors for prediction accuracy. Therefore, it is necessary to study the model for predicting the stock price index by selecting and reflecting technical and auxiliary factors that affect the fluctuation of the stock price according to the stock price. Most of the existing studies related to this are forecasting studies that use news information or macroeconomic indicators that create market fluctuations, or reflect only a few combinations of indicators. In this paper, this we propose to present an effective combination of the news information sentiment analysis and various macroeconomic indicators in order to predict the US Dow Jones Index. After Crawling more than 93,000 business news from the New York Times for two years, the sentiment results analyzed using the latest natural language processing techniques BERT and NLTK, along with five macroeconomic indicators, gold prices, oil prices, and five foreign exchange rates affecting the US economy Combination was applied to the prediction algorithm LSTM, which is known to be the most suitable for combining numeric and text information. As a result of experimenting with various combinations, the combination of DJI, NLTK, BERT, OIL, GOLD, and EURUSD in the DJI index prediction yielded the smallest MSE value.
In this paper, we present empirical testing result to examine the validity of inbound supply and outbound demand risk factors in the sense of early predicting the firm's bankruptcy risk level. The risk factors are drawn from industry uncertainty attributes categorized as uncertainties of input market (inbound supply), and product market (outbound demand). On the basis of input-output table, industry level inbound and outbound sectors are identified to formalize supply chain structures, relevant inbound and outbound uncertainty attributes and corresponding risk factors. Subsequently, publicly available macro-economic indicators are used to appropriately quantify these risk factors. Total 68 industry level bankruptcy risk forecasting results are presented with the average R-square scores of between 53.4% and 37.1% with varying time lag. The findings offers useful insights to incorporate supply chain risk to the body of firm's bankruptcy risk level prediction literature.
Maiboroda, Olha;Bezuhla, Liudmyla S.;Gukaliuk, Andrii F.;Shymanska, Viktoriia;Momont, Tetiana;Ilchenko, Tetiana V.
International Journal of Computer Science & Network Security
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v.21
no.3
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pp.235-244
/
2021
The change of the development of transport and logistics systems occurs with the active change of technology and the advent of the era of Industry 4.0. It requires modernization of approaches to the development of transport and logistics systems at the macro and micro levels. The present study aims to identify perspective directions of development and evolution, find out the existing obstacles in the integration of technological solutions of transport and logistics systems at the macro and micro levels. This study is based on a quantitative and qualitative methodology for assessing the level of integration of technologies into transport and logistics systems to study the prospects for their development at the micro level. Macroeconomic indicators of transport and logistics in the context of different regions of the world were used to quantify the development prospects. For a qualitative assessment of the development of the transport and logistics system, the case study method was used. The object of the study was selected logistics company Sensco Logistics Inc., Austin TX. At the macro level, countries with more innovative logistics sectors have stronger mechanisms for coordinating private sector activities. Simplification of administrative procedures of control and regulation by the public sector in order to facilitate trade between countries is a promising direction for the development of transport and logistics systems. Such reforms are more effective in developing a "rigid" transport infrastructure. The integration of Industry 4.0 technology solutions into the international logistics sector is defined by political and legal barriers, especially in developing countries. In low-income countries, hard and soft infrastructure reforms are hindering the development of logistics companies that provide transport services. This determines the national level of development of transport and logistics systems, and in general the global level of development of transport and logistics. In developed countries, the legal barriers to the development of new technological logistics are environmental requirements for the integration of technologies into the transport system. These trends are slowing down the development of International Logistics, which, compared to other industries, is slower to integrate Industry 4.0 technologies. This study combines macroeconomic factors that determine the prospects for the development of transport and logistics systems at the micro level.
Since the late 2000s, there has been growing preparation in South Korea for a sudden reunification of South and North Korea. Particularly in the power industry field, thorough preparations for the construction of a power infrastructure after reunification are necessary. The first step is to estimate the peak load demand. In this paper, we suggest a new peak demand estimation methodology by integrating existing correlation analysis methods between economic indicators and power generation quantities with a power supply interruption model in consideration of power consumption patterns. Through this, the potential peak demand and actual peak demand of the Nation, which experiences power supply interruption can be estimated. For case studies on North Korea after reunification, the potential peak demand in 2015 was estimated at 5,189 MW, while the actual peak demand within the same year was recorded as 2,461 MW. The estimated potential peak demand can be utilized as an important factor when planning the construction of power system facilities in preparation for reunification.
NGUYEN, Phong Thanh;HUYNH, Vy Dang Bich;NGUYEN, Quyen Le Hoang Thuy To
The Journal of Asian Finance, Economics and Business
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v.8
no.2
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pp.195-200
/
2021
In recent years, Vietnam's economic growth rate has been attributed to the growth of many well-managed industries within Southeast Asia. Among them is the civil construction industry. Construction projects typically take a long time to complete and require a huge budget. Many socio-economic variables and factors affect total construction project costs due to market fluctuations. In recent years, crucial socioeconomic development indicators of construction reached a fairly high growth rate. Also, most infrastructure and construction projects have a high degree of complexity and uncertainty. This makes it challenging to predict the accurate project price. These challenges raise the need to recognize significant factors that influence the construction price index of civil buildings in Vietnam, both micro and macro. Therefore, this paper presents critical factors that affect the construction price index using the fuzzy extent analysis process in an uncertain environment. This proposed quantitative model is expected to reflect the uncertainty in the process of evaluating and ranking the influencing factors of the construction price index in Vietnam. The research results would also allow project stakeholders to be more informed of the factors affecting the construction price index in the context of Vietnam's civil construction industry. They also enable construction contractors to estimate project costs and bid rates better, enhancing their project and risk management performance.
Journal of the Korean Institute of Landscape Architecture
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v.30
no.2
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pp.39-49
/
2002
The purpose of this study is to propose an objective and rational methodology for the selection of proposed sites far the National Trust(NT), which is the new alterative proposal far the conservation of natural environments destroyed by injudicious land development and economic growth. That is to enforce many analysis for the effective estimation of rare ecological and landscape resources and to propose a model based on estimation and united indicators. Using the estimative model, we apply it to the selection of the proposed site in micro scale and simultaneously offer the basic methodology of effective and systematic land conservation in macro scale. The results of this study are as follows: 1) The results of analysis for the reliability of estimative items and indicators, presented no problem in that the coefficient of reliability was over 0.7. 2) The correlation measure of the estimative indicator indicated that 'succession'and 'regenerating restorability' were highly correlative in the item of plants. Another three items showed a tendency to be alike. 3) The results of factor analysis on the characteristics of indicators, classified plants into four categories including a stable factor. The item of animals was classified as a stable and rare factor. The item of landscape was classified as a physical and mental factor and the environment as a pollutional and conditional factor. 4) The model of estimation created through factor analysis was valid for the approval of the regression model because significant probability was 0.00. When we consider the NT proposed site as a complex body that is composed of diverse natural and manmade resources, certainly the synthetic methodology of estimation is needed. If these studies are carried out, NT sites will be selected more rationally and effectively than at present. Consequently, they have the potential to play a core role of natural ecosystem conservation in Korea.
This paper compares two indicators, economic development and social condition, to find a better way to measure the level of social welfare development. The results show that social condition is more adequate indicator than economic development. The social condition has high correlation with the development of social welfare in all the 78 countries as well as in five groups of countries when the economic development is controlled. The comparison of two indicators reveals important findings. Among other things, the higher the level of social condition compared with economic development, the larger the social welfare expenditure. This tendency is particularly strong among the western European countries and former socialist countries. This result implies that the macro-level policy of social redistribution is also important for the development of social welfare in addition to micro-level policy of income redistribution. As we expected, the results show that the level of Korean social welfare development is very low. Considering our levels of economic development and social condition, predicted social welfare expenditure from regression model is at least 17% of GDP, but we are spending only 30% of this predicted expenditure. Another serious problem in Korean social welfare is unbalanced expenditure between social insurance and public assistance. On the basis of these results, this paper suggests three implications for social policy to improve Korean social welfare: First of all, the gap between predicted and actual expenditures should be closed to improve the minimum level of social welfare. Secondly, the level of social condition itself should be improved to increase the public awareness of social welfare. Finally, the wide difference in expenditure between universal and selective social welfare programs should also be removed to decrease the relative deprivation of the poor.
Proceedings of the Korea Water Resources Association Conference
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2009.05a
/
pp.2169-2175
/
2009
This research aims to evaluate the concept of eco-efficient water infrastructure and provides a list of case studies in order to help understand the applicability of eco-efficient water infrastructure to Asia and the Pacific. A set of indicators have been explored to assess eco-efficiency in water infrastructure for the region on a micro and macro scale. The core idea of eco-efficiency, 'more value with less impact (on the environment)', has proven to be applicable in management of water infrastructure. The fundamental elements in eco-efficient water infrastructure should encompass physical infrastructure and non-physical infrastructure, which is more needed particularly in Asian countries. The case studies have demonstrated the applicability of the concept of eco-efficient water infrastructure. The Republic of Korea has provided the case of the eco-friendly approaches to enhance dam management and its innovative solutions how to use water more efficiently through state-of-art technologies. The experiences of Singapore are some of the best evidence to establish eco-efficient water infrastructure, for instance, the NEWater project via application of cutting edge technologies (recycled water) and institutional reform in water tariff systems to conserve water as well as enhance water quality. A list of indicators to assess eco-efficiency in water infrastructure have been discussed, and the research presents a myriad of project cases which are good to represent eco-efficiency in water infrastructure, including multipurpose small dams, customized flood defense systems, eco-efficient ground water use, and eco-efficient desalination plants. The study has presented numerous indicators in five different categories: 1) the status of water availability and infrastructure; 2) production and consumption patterns of freshwater; 3) agricultural products and sources of environmental loads; 4) damages from water-caused natural disaster; and 5) urban water supply and sanitation. There are challenges as well as benefits in such indicators, since the indicators should be applied very carefully in accordance with specific socio-economic, political and policy contexts in different countries in Asia and the Pacific Region. The key to success of establishment of eco-efficient water infrastructure in Asia primarily depends on the extent to which each country is committed to balancing its development of physical as well as non-physical water infrastructure. Particularly, it is imperative for Asian countries to transform its policy focus from physical infrastructure to non-physical infrastructure. Such shift will help lead to implementation of sustainable in Asian countries.
Many studies on port tariff have been done over twenty years using publicly assessed data on tariff. Public data for tariff rates do not reflect, however, the port tariff in a real market, since the cargo handling charge, which is the important fraction of port tariff, is confidentially decided by the negotiations between a shipping company and a container terminal operator. In this paper, we collected the real price data of the port tariff on the world major sixteen container ports from a global shipping company and transformed it into the tariff per TEU(US$/TEU). The comparative analysis of port tariff was performed using the port tariff per TEU, and a panel regression analysis was done to identify the relations between the port tariff and demand variables: throughput, GDP and trade amount.
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