• 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.

• The Journal of Industrial Distribution & Business
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• v.12 no.2
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• pp.41-52
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• 2021

Purpose: This study aims to provide implications for the government's housing supply policy by analyzing the factors that determine the type of real estate holding and household debt. This study started from the awareness that the determinants of household debt differ depending on the type of real estate holding. Research design, data and methodology: Real estate ownership type was classified and analyzed into 4 models: model 1 (1 household 1 house and self-resident), model 2 (1 household multiple real estate ownership and self-resident), model 3 (1 household 1 house and rent residence), model 4 (1 household holds a large number of real estate and rent residence). The analysis method used multiple regression analysis. The dependent variable was household total debt. As independent variables, household debt, annual gross household income, financial assets, real estate net assets, annual repayment, demographic & residential characteristics were used. Results: 1) Model 4 has the highest household debt and the highest gross income, Model 2 has the most real estate mortgage loans and real estate net asset, and Model 1 has the highest real estate mortgage payments. 2) The positive factor of common household debt determinants is real estate net assets, and the negative factor is financial assets. 3) It was the net assets of real estate that acted as a positive factor in common for the four models. In other words, the more financial assets, the less household debt. It was analyzed that the more net assets of real estate, the more household debt. The annual repayment of financial liabilities had no influence on household debt, while the annual repayment of loan liabilities and household debt had a positive relationship. Conclusions: 1) It is necessary to introduce benefits and systems that can increase the proportion of household financial asset. Specific alternatives include tax benefits and reduced fees for financial asset investment. 2) In the case where a homeless person prepares one house for one household, it is necessary to prepare various support measures according to the income level. The specific alternative is to give additional points for pre-sale or apply an interest rate cut incentive for mortgage loans.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.3-10
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• 2022

An estimated investment gap of $176 billion needs to be filled over the next ten years to improve America's inland waterway transportation systems. Many of these infrastructure systems are now beyond their original 50-year design life and are often behind in maintenance due to funding constraints. Therefore, long-term maintenance strategies (i.e., asset management (AM) strategies) are needed to optimize investments across these waterway systems to improve their condition. Two common AM strategies include policy-driven maintenance and performance-driven maintenance. Currently, limited research exists on selecting the optimal AM approach for managing inland waterway transportation assets. Therefore, the goal of this study is to provide a decision model that can be used to select the optimal alternative between the two AM approaches by considering key uncertainties such as asset condition, asset test results, and asset failure. We achieve this goal by addressing the decision problem as a single-criterion problem, which calculates each alternative's expected value and certain equivalence using allocated monetary values to determine the recommended alternative for optimally maintaining navigable waterways. The decision model considers estimated and predicted values based on the current state of the infrastructure. This research concludes that the performance-based approach is the optimal alternative based on the expected value obtained from the analysis. This research sets the stage for further studies on fiscal constraints that will effectively optimize these assets condition.

• Korean Journal of Construction Engineering and Management
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• v.13 no.5
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• pp.3-11
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• 2012

The most of domestic bridge has an used life under 30 years, Future maintenance budgets can be expected to increase. However, because of bridge maintenance budgets are limited, demand for asset management being performed to achieve required performance within available budget is increasing. To perform effective asset management of bridges should be made the best use of information to occur in all phase of construction project. Therefore, the development of system and DB is required to support asset management by effective information management. The objective of this study is the development of the BIM-based bridge asset management model. Through previous research survey, BIM capabilities and asset management components were established and mutual linkages were examined. Bridge asset management model was composed of alternate assessment model. In addition, BIM-based asset management model was performed case studies to verify feasibility and applicability. The proposed model can be applied to a current bridge maintenance procedures and supported to perform effective bridge maintenance tasks within a limited budget.

• 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 the Korean Society for Industrial and Applied Mathematics
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• v.15 no.4
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• pp.277-290
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• 2011

We define some multi-type asset models derved from L$\acute{e}$vy proceses which emphasize coefficients of stochastic differential equations. Also these asset models can be represented by Doleance-Dade linear equations derived from jump-type semimartingales which are decomposed by various terms of time basically. For these asset models, we can construct optimal portfolio strategy by using filtered various information at each check time.

• Journal of Families and Better Life
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• v.17 no.4
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• pp.193-206
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• 1999

This study analyzed the household portfolio according to wealth levels using a survey data of 1997 Korea Household Panel Study. The major findings of this study are as follows: (1) A household in high wealth level has invested relatively large proportion of his asset into real estate (2) A household in middle wealth level has invested relatively large proportion of his asset into risky financial asset(3) A household in low wealth level has invested relatively large proportion of his asset into secure financial asset. These findings accorded with risky pyramid model.

• Korean Journal of Mathematics
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• v.22 no.3
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• pp.529-552
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• 2014

As we know, some indices and data are strong influence to the price movement of some assets now, but not to another assets and in future. Thus we define some asset models for several time intervals; intraday, weekly, monthly, and yearly asset models. We define these asset models by using Brownian motion with volatility and Poisson process, and several deterministic functions(index function, twitter data function and big-jump simple function etc). In our asset models, these deterministic functions are the positive or negative levels of auxiliary indices, of analyzed data, and for imminent and extreme state(for example, financial shock or the highest popularity in the market). These functions determined by indices, twitter data and shocking news are a kind of one of speciality of our asset models. For reasonableness of our asset models, we introduce several real data, figurers and tables, and simulations. Perhaps from our asset models, for short-term or long-term investment, we can classify and reference many kinds of usual auxiliary indices, information and data.

• Journal of the Korean Association of Geographic Information Studies
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• v.5 no.3
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• pp.55-67
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• 2002

Various researches and practices on asset management and asset-based mapping have been done with regard to engineering, industry, business and stocks marketing areas. Their notions and concepts are differently interpreted in response to different requirements. There are considerable research outcomes of management, operation and maintenance for physical, natural and digital assets. However, existing concept of asset management might have limitations to deal with diverse tangible or intangible assets at the individual/household/community level. In this paper, a conceptual framework of Hexad asset model is designed to explicate increase, decrease and other changes of assets flows as a geometric pathway. Particularly, consideration of lands and housing as important physical and natural assets to escape poverty not only leads to creation of an excellent 3D digital asset management, but also reaches to a new approach to asset-based mapping for a poverty information management and system.

• 한국디지털정책학회:학술대회논문집
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• 2004.05a
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• pp.491-512
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• 2004

The purpose of this paper is to analyze and compare the existing digital media asset management systems and develop a prospective implementation model. As a result of conducting this research, it is recommended that the prospective system consist of archiving server, processing server, and interface program. This result suggests important starting point for development a resonable and reliable implementation model for digital media asset management system.