• 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.

• The Journal of the Korea Contents Association
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• v.20 no.6
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• pp.279-292
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• 2020

The purpose of this study is to suggest what the effect of channel brand equity is in the environment of multi-platform and to raise how channel brand equity is important by investigating how terrestrial TV's channel brand equity influences viewers' choice and use of the terrestrial TV contents on the multi-platform. The findings showed that the terrestrial TV's channel brand equity partially had a significant effect on the degree of use of Terrestrial TV contents on multi-platforms, but it did not on the diversity of media for viewing the terrestrial TV contents. In addition, it partially had an influence on the use of platform and service for viewing terrestrial TV contents by type. Finally, it also partially had impacts on the diversity of genre and the genre use by type. The findings suggest that the channel brand equity can have effects on the viewers' choice and use of broadcasting contents on the multi-platforms, and thus this study provides significant insights on what strategies are required for the competitiveness of broadcasting channels.

• Korean Journal of Social Welfare
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• v.68 no.4
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• pp.53-74
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• 2016

In this study, to verify influence that economic situations of a household unit have on donation behavior, after economic situations of a household unit were measured with income and assets by type and income to assets, effect which each variable has on secular giving was verified. This study used 3-year panel data of a total of 4,938 households based on the fifth to seventh year data as investigation data from 2012 to 2014 among data of financial panel investigation of Korea Institute of Public Finance of National Survey of Tax and Benefit. As an analysis method, a random effect tobit model was used. At the analysis result, it appeared that as scales of financial assets, earned income, property income, and transfer income become larger, the amount of donation increased. Also, it was represented that rates of income to assets had negative influence on secular giving. In case of demographic variables, education levels of householders and sizes of houses had relation of a positive direction. In case of ages, it appeared that they had inverted U-type relation. This study has meanings in that understanding of donation behavior of a household unit can be increased and expanded more and also implications related to intervention strategies of a household unit to expand sharing culture can be extracted by verifying influence which economic factors of a household unit have on donation behavior based on panel data.

• Journal of Advanced Navigation Technology
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• v.13 no.6
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• pp.971-976
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• 2009

This paper demonstrates the design and development of asset management systems suitable for the universities full of very various kind of assets. Universities consists of many departments, which have a multiplicity of many experimental. It is very difficult to record and manage assets with hands. In addition, the equipments are moving freely from one lab to another inside the school, which means it is tough to find the location of the assets and so some stuffs that are given lack attention are likely to disappear. So, these things occurring frequently in the university asset management environment should be considered in the design and embodiment of the asset management system. In the proposed system, location recognition of the assets is realized based on a route tracking method, so it is possible to detect the loss of the high priced assets and entrance, export, and lending of them are controlled efficiently. The system is likely to reduce the load of a manager responsible for asset management, because configured to decrease interventions of the manager in overall asset management process. Especially, the proposed system and implementation method will be suitable for small and medium-scale asset management, path tracking, history management.

• Journal of Platform Technology
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• v.11 no.3
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• pp.32-44
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• 2023

A blockchain bridge (hereinafter referred to as "bridge") is a service that enables the transfer of assets between blockchains. A bridge accepts virtual assets from users and delivers the same virtual assets to users on other blockchains. Users use bridges because they cannot transfer assets to other blockchains in the usual way because each blockchain environment is independent. Therefore, the movement of assets through bridges is not traceable in the usual way. If a malicious actor moves funds through a bridge, existing asset tracking tools are limited in their ability to trace it. Therefore, this paper proposes a method to obtain information on bridge usage by identifying the structure of the bridge and analyzing the event logs of bridge requests. First, to understand the structure of bridges, we analyzed bridges operating on Ethereum Virtual Machine(EVM) based blockchains. Based on the analysis, we applied the method to arbitrary bridge events. Furthermore, we created an automated tool that continuously collects and stores bridge usage information so that it can be used for actual tracking. We also validated the automated tool and tracking method based on an asset transfer scenario. By extracting the usage information through the tool after using the bridge, we were able to check important information for tracking, such as the sending blockchain, the receiving blockchain, the receiving wallet address, and the type and quantity of tokens transferred. This showed that it is possible to overcome the limitations of tracking asset movements using blockchain bridges.

• Knowledge Management Research
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• v.24 no.3
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• pp.73-94
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• 2023

With the virtual asset market's rapid growth, government regulations on listing and trading procedures are expected. However, specific measures are currently lacking. To ensure stable inclusion in the institutional framework, precise regulations are needed for market development and investor protection. This study compares self-regulatory guidelines of the top domestic virtual asset exchanges with Korea Exchange's Preliminary Listing Examination Standards (2022) to enhance timeliness and relevance. It defines IEO, IPO, and ICO concepts and addresses conflicts of interest in IEO. Analyzing delisted virtual assets, it categorizes issues and classifies listing examination guidelines into formal and qualitative requirements. The study examines self-regulatory guidelines based on continuity, transparency, stability, corporate characteristics, and investor protection criteria, along with five special requirements for virtual assets. Improvement measures include regular disclosures of governance structure, circulation volume, and the establishment of independent audit institutions. This research further analyzes delisting cases, classifies issues, and proposes solutions. Considering stock market similarities, it offers measures based on the institutional framework.

• IT SoC Magazine
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• s.19
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• pp.31-36
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• 2007

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.9
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• pp.75-82
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• 2009

In this paper, the method to apply the RFID technology to schools will be presented in order to effectively integrate and manage various assets in school. The proposed system may be seemed to be very useful of individual school to grasp the status of their assets and also the central government to control and manage the assets scattered far and wide around the country. We also propose the OSN/PMS server based on EPC global standard could be appropriate especially in schools. In addition, the proposed system can acquire simultaneously the information from several RFID readers at real time so that it is possible and easy to track the position, the path of moving and the status of assets in the school. To show the usefulness of the proposed system, the prototype of the system has been implemented and conducted. The proposed system seems to be applicable to various fields such as factories, farms, or homes as well as school. Especially, it would become the very good integrated management system in the case that assets lie scattered widely.

• 한국IT서비스학회:학술대회논문집
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• 2006.11a
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• pp.185-189
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• 2006

기존의 레거시 시스템은 개발과정에 있어서 이미 많은 시간과 경험과 지식을 갖고 있기 때문에 조직의 핵심 가치를 지닌 재사용 자산으로 활용할 수 있는 의미있는 자산이다. 그러므로 레거시 시스템에서 사용해 왔던 가치있는 자산들을 웹을 기반으로 한 e-비즈니스 환경에 적용시키고, 다양한 플랫폼에서 사용하기 위한 필요성이 증대되었다. 변화하는 환경에 따라 레거시 시스템을 현대화(Modernization)하는 방법중의 하나로 현재 시스템에서 운용되고 있는 것을 OMG에서 제안한 모델기반아키텍처(MDA)를 사용하여 여러 플랫폼을 쉽게 지원하고 모델기반의 통합을 하고자 한다. MDA 환경을 기반으로 기존의 레거시 시스템을 활용하기 위하여 기존의 소프트웨어를 직접 수정 없이 재사용하거나 PSM에서 PIM 변환을 하기 위하여 래퍼(wrapper를 사용한다. 본 논문에서는 이러한 래퍼의 사용에 따른 문제점을 분석하고, 요구에 따라 모델에 대한 접근방식을 다르게 사용하여 시스템의 개선상황에 유연하게 대처할 수 있도록 래퍼를 상황에 따라 적절하게 사용하는 혼합(hybrid) 방식을 적용한 개선전략을 제안하고자 한다.

• KDI Journal of Economic Policy
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• v.29 no.1
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• pp.113-136
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• 2007

Korean house prices have risen rapidly since year 2001 and there have been some worries that the recent house price hikes are too excessive. This paper empirically analyzes the movement of Korean house prices and derives some implications from it, based on three different theoretical asset pricing models; long-run supply demand model, present value model and general asset pricing model. The results from the analyses show that recent house prices are overall higher than the theoretical prices, thus requiring measures to stabilize house prices hikes.