• Journal of Korean Society for Quality Management
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• v.31 no.3
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• pp.160-171
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• 2003

Criteria for the comparison of quality of asset portfolio management are risk and return. In this paper a method to use structural time-series model to determine an optimal portfolio for the improvement of quality of asset portfolio management is suggested. In traditional mean variance analysis expected return is assumed to be time-invariant. However, it is more realistic to assume that expected return is temporally dynamic and structural time-series model can be used to reflect time-varying nature of return. A data set from an insurance company was used to show validity of suggested method.

• Journal of the Korean Operations Research and Management Science Society
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• v.38 no.4
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• pp.11-33
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• 2013

We analyzed the structures and properties of the global financial market networks using social network analysis approach. The Minimum Spanning Tree (MST) lengths and networks of the global financial markets based on the correlation coefficients have been analyzed. Firstly, similar to the previous studies on the global stock indices using MST length, the diversification effects in the global multi-asset portfolio can disappear during the crisis as the correlations among the asset class and within the asset class increase due to the system risks. Second, through the network visualization, we found the clustering of the asset class in the global financial markets network, which confirms the possible diversification effect in the global multi-asset portfolio. Meanwhile, we found the changes in the structure of the network during the crisis. For the last one, in terms of the degree centrality, the stock indices were the most influential to other assets in the global financial markets network, while in terms of the betweenness centrality, Gold, Silver and AUD. In the practical perspective, we propose the methods such as MST length and network visualization to monitor the change of the correlation risk for the risk management of the multi-asset portfolio.

• Journal of Korean Society for Quality Management
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• v.51 no.2
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• pp.171-184
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• 2023

Purpose: First, this paper suggests an alternative approach to find optimal portfolio (stocks, bonds and ESG stocks) under the maximizing utility of investors. Second, we include ESG stocks in our optimal portfolio, and compare improvement of welfares in the case with and without ESG stocks in portfolio. Methods: Our main method of analysis follows Brennan et al(2002), designed under the continuous time framework. We assume that the dynamics of stock price follow the Geometric Brownian Motion (GBM) while the short rate have the Vasicek model. For the utility function of investors, we use the Power Utility Function, which commonly used in financial studies. The optimal portfolio and welfares are derived in the partial equilibrium. The parameters are estimated by using Kalman filter and ordinary least square method. Results: During the overall analysis period, the portfolio including ESG, did not show clear welfare improvement. In 2017, it has slightly exceeded this benchmark 1, showing the possibility of improvement, but the ESG stocks we selected have not strongly shown statistically significant welfare improvement results. This paper showed that the factors affecting optimal asset allocation and welfare improvement were different each other. We also found that the proportion of optimal asset allocation was affected by factors such as asset return, volatility, and inverse correlation between stocks and bonds, similar to traditional financial theory. Conclusion: The portfolio with ESG investment did not show significant results in welfare improvement is due to that 1) the KRX ESG Leaders 150 selected in our study is an index based on ESG integrated scores, which are designed to affect stability rather than profitability. And 2) Korea has a short history of ESG investment. During the limited analysis period, the performance of stock-related assets was inferior to bond assets at the time of the interest rate drop.

• 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.

• Communications for Statistical Applications and Methods
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• v.28 no.1
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• pp.59-79
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• 2021

Value at Risk (VaR) is one of the most common risk management tools in finance. Since a portfolio of several assets, rather than one asset portfolio, is advantageous in the risk diversification for investment, VaR for a portfolio of two or more assets is often used. In such cases, multivariate distributions of asset returns are considered to calculate VaR of the corresponding portfolio. Copulas are one way of generating a multivariate distribution by identifying the dependence structure of asset returns while allowing many different marginal distributions. However, they are used mainly for bivariate distributions and are not widely used in modeling joint distributions for many variables in finance. In this study, we would like to examine the performance of various copulas for high dimensional data and several different dependence structures. This paper compares copulas such as elliptical, vine, and hierarchical copulas in computing the VaR of portfolios to find appropriate copula functions in various dependence structures among asset return distributions. In the simulation studies under various dependence structures and real data analysis, the hierarchical Clayton copula shows the best performance in the VaR calculation using four assets. For marginal distributions of single asset returns, normal inverse Gaussian distribution was used to model asset return distributions, which are generally high-peaked and heavy-tailed.

• Industrial Engineering and Management Systems
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• v.13 no.4
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• pp.442-448
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• 2014

Portfolio optimization in the presence of estimation error can be stabilized by incorporating norm-constraints; this result was shown by DeMiguel et al. (A generalized approach to portfolio optimization: improving performance by constraining portfolio norms, Management Science, 5, 798-812, 2009), who reported empirical performance better than numerous competing approaches. We extend the idea of norm-constraints by introducing a powerful enhancement, grouped selection for portfolio optimization. Here, instead of merely penalizing norms of the assets being selected, we penalize groups, where within a group assets are treated alike, but across groups, the penalization may differ. The idea of groupwise selection is grounded in statistics, but to our knowledge, it is novel in the context of portfolio optimization. Novelty aside, the real benefits of groupwise selection are substantiated by experiments; our results show that groupwise asset selection leads to strategies with lower variance, higher Sharpe ratios, and even higher expected returns than the ordinary norm-constrained formulations.

• Journal of the Korean Home Economics Association
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• v.41 no.9
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• pp.105-120
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• 2003

This study has conducted to develop the computer program for households portfolio management to enhance their financial well-being. The study has divided into two parts. First, descriptive statistics has used to analyze as a basis of computer program and it includes the comparison of household asset allocations between households in Korea and U. S. A., Second, it shows the components of the portfolio program developed to manage households efficiently. For both two countries, recent four years data has been used and in part two, total sample size of households in Korea is 2155. From the statistical analysis, households in U. S. A. tend to invest more on the stock & bonds as their net-asset is increased. However households in Korea tend to have less financial assets and it might be found the fact that they prefer to own real-estate because of the inflation. In the part of computer program, it is included the average financial asset responding to the demographic variables and households could refer those average amount as a reference planning their asset portfolio.

• Industrial Engineering and Management Systems
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• v.16 no.1
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• pp.118-128
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• 2017

Uncertain factors in finical markets make the prediction of future returns and risk of asset much difficult. In this paper, a model,assuming the admissible errors on expected returns and risks of assets, assisted in the multiperiod mean variance portfolio selection problem is built. The model considers transaction costs, upper bound on borrowing risk-free asset constraints, cardinality constraints and threshold constraints. Cardinality constraints limit the number of assets to be held in an efficient portfolio. At the same time, threshold constraints limit the amount of capital to be invested in each stock and prevent very small investments in any stock. Because of these limitations, the proposed model is a mix integer dynamic optimization problem with path dependence. The forward dynamic programming method is designed to obtain the optimal portfolio strategy. Finally, to evaluate the model, our result of a meaning example is compared to the terminal wealth under different constraints.

• Knowledge Management Research
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• v.19 no.1
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• pp.97-118
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• 2018

The finance-investment industry is currently focusing on research related to artificial intelligence and big data, moving beyond conventional theories of financial engineering. However, the case of equity optimization portfolio by using an artificial intelligence, big data, and its performance is rarely realized in practice. Thus, the purpose of this study is to propose process improvements in equity selection, information analysis, and portfolio composition, and lastly an improvement in portfolio returns, with the case of an equity optimization model based on quantitative research by an artificial intelligence. This paper is an empirical study of the portfolio based on an artificial intelligence technology of "D" asset management, which is the largest domestic active-quant-fiduciary management in accordance with the purpose of this paper. This study will apply artificial intelligence to finance, analyzing financial and demand-supply information and automating factor-selection and weight of equity through machine learning based on the artificial neural network. Also, the learning the process for the composition of portfolio optimization and its performance by applying genetic algorithms to models will be documented. This study posits a model that the asset management industry can achieve, with continuous and stable excess performance, low costs and high efficiency in the process of investment.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.2
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• pp.49-66
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• 2014

This paper studies optimal consumption and investment behaviors of an individual when risky asset returns and her income are affected by the business cycle. The investor considers the incomplete information risk of unobservable macroeconomic conditions and updates her belief of expected risky asset returns through Bayesian learning. We find that the optimal investment strategy, certainty equivalent wealth, and portfolio hedging demand significantly depend on the belief about the macroeconomic conditions.