• Korean Management Science Review
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• v.25 no.3
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• pp.59-72
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• 2008

This paper proposes an R&D opportunity scan framework for information and telecommunications company in aging society. The framework consists of trend analysis, market-oriented search, technology-oriented search, and R&D Portfolio development. We identify technology themes in the market-oriented search by developing market scenarios and analyzing a new business model framework. And then we search prospective technologies in the technology-oriented recess by technology scanning and patent analysis. By matching technology themes with prospective technologies, generate an R&D portfolio. Finally, we evaluate the risk of the proposed R&D portfolio.

• Asia-Pacific Journal of Business
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• v.12 no.1
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• pp.121-134
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• 2021

Purpose - This study examines whether flight-to-liquidity (FTL) explains the dynamic liquidity risk on stock returns, and whether it has a significant influence on determinants the cross-section of stock returns. Design/methodology/approach - This study suggests a new risk factor, dynamic liquidity hedge portfolio (DLP), to reflect the dynamic impact of liquidity risk on stock returns and the Fama-MacBeth 2 stage regression analysis is employed in order to analyze the data. Findings - First, the DLP factor shows more positive and significant beta for the small or illiquidity stocks. Second, the DLP shows a different influence than SMB (size risk factor), HML (value risk factor), NMP (liquidity risk factor), FTVOL (total volatility factor) in determining the cross-section of stock returns. In addition, the DLP has a statistically significant risk premium of around 5%, which is relatively larger than other risk factors. Research implications or Originality - This study has academic value in terms of newly confirming that the DLP factor has a more significant impact on cross-sectional determination of stock returns than other risk factors by proposing a conditional liquidity factor that can explain the FTL phenomenon.

• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.541-559
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• 2015

VaR is now widely used as an important tool to evaluate and manage financial risks. In particular, it is important to select an appropriate volatility model for the rate of return of financial assets. In this study, both univariate and multivariate models are considered to evaluate VaR of the portfolio composed of KOSPI, Hang-Seng, Nikkei indexes, and their performances are compared through back testing techniques. Overall, multivariate models are shown to be more appropriate than univariate models to estimate the portfolio VaR, in particular DCC and ADCC models are shown to be more superior than others.

• The Korean Journal of Applied Statistics
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• v.24 no.4
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• pp.597-607
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• 2011

Value at Risk(VaR) is being widely used as a simple tool for measuring financial risk. Although VaR has a few weak points, it is used as a basic risk measure due to its simplicity and easiness of understanding. However, it becomes very difficult to estimate the volatility of the portfolio (essential to compute its VaR) when the number of assets in the portfolio is large. In this case, we can consider the application of a dimension reduction technique; however, the ordinary factor analysis cannot be applied directly to financial data due to autocorrelation. In this paper, we suggest a dimension reduction method that uses the time-series factor analysis and DCC(Dynamic Conditional Correlation) GARCH model. We also compare the method using time-series factor analysis with the existing method using ordinary factor analysis by backtesting the VaR of real data from the Korean stock market.

• Korean Journal of Construction Engineering and Management
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• v.14 no.1
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• pp.23-31
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• 2013

Following the U.S sub-prime mortgage crisis and a slump in properties market, the probability is rising that housing investment would not yield high profit as it used to do until early 2000s. For this reason, the nature of properties market is undergoing a change from a source of lucrative investment to a source of a relatively low but stable profit, such as profit-oriented real estate. This trend is likely to promote REITs market, which is a leading product for indirect investment. Until now, the REITs market has been growing slowly compared to a general housing market or financial markets. However, as the importance of risk management based on portfolio theories increases, stable profit generation of REITs can be effective in risk management. This study conducts an empirical analysis on how investment risks can be diversified by including REITs-a source of relatively stable profit in the equity market-in investment portfolio. The analysis results showed that, similar to food and beverage stocks of highly defensive nature, REITs has a relatively weak correlation with KOSPI that reflects the overall market performance. It also showed very low standard deviation in case of minimum variance portfolio. This suggests that including REITs in investment portfolio can be as effective as including food and beverage stocks for risk diversification. Due to uncertainties, investment always accompanies risks, and balancing potential profits and risks is essential.

• Environmental and Resource Economics Review
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• v.17 no.1
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• pp.51-81
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• 2008

In this paper, economic performance was measured through portfolio analysis for environmentally friendly companies from September 2004 to September 2005. By using portfolio analysis, rate of revenue for environmentally friendly company is twelve to seven teen percent higher than the KOSPI, and KOSPI200 based companies. Except medical and pharmatical industry, environmentally friendly companies had shown low risk and high returns of revenue for banking and financing, chemical and electronic industry. As SRI fund is emerging as a important guideline in recent years, valuation of a cooperate will be very important tool for the financing business area in the future.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.1113-1122
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• 2020

The purpose of this study is to examine how the Indian banks have adjusted their risk-based capital ratios during 2009-2018 to meet the regulatory requirements. Banks can, in principle, increase their risk-based regulatory capital ratio, either by increasing their levels of regulatory capital or by shrinking their risk-weighted assets by adjusting asset growth or risk in the portfolio. We investigate banks' capital behavior by decomposing the change in the capital ratio into the contribution of its components and analyzing their variance across regulatory regimes and banks' ownerships. We further investigate how each component of the capital ratio is adjusted by the banks by breaking down them into balance sheet items. We find that the banks' capital behavior significantly differed between public and private sector banks and between the two regulatory regimes. During Basel II, banks, in general, followed a strategy of aggressive asset growth with increased risk-taking. The decline in the CRAR because of such an expansionary strategy was adjusted by augmenting additional capital. However, during Basel III, due to higher capital requirements, both in terms of quantity and quality, banks followed a strategy of cutting back their asset growth and reducing the risk in their portfolio to maintain their CRAR.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.49
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• pp.43-57
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• 1999

The recent trend is that risk management has more and more its importance. Neverthless, Korea's risk management is not developed. Even most banks does gap, duration in ALM for risk management, development and operation of VaR stressed at BIS have elementary level. In the case of Fallon and Pritsker, Marshall, gamma model is superior to delta model and Monte Carlo Simulation is improved at its result, as sample number is increased. And, nonparametric model is superior to parametric model. In the case of Korea's stock portfolio, VaR of Monte Carlo Simulation and Full Variance Covariance Model is less than that of Diagonal Model. The reason is that VaR of Full Variance Covariance Model is more precise than that of Diagonal Model. By the way, in the case of interest rate, result of monte carlo simulation is less than that of delta-gamma analysis on 95% confidence level. But, result of 99% is reversed. Therefore, result of which method is not dominated. It means two fact at forecast on volatility of stock and interest rate portfolio. First, in Delta-gamma method and Monte Carlo Simulation, assumption of distribution affects Value at Risk. Second, Value at Risk depends on test method. And, if option price is included, test results will have difference between the two. Therefore, If interest rate futures and option market is open, Korea's findings is supposed to like results of other advanced countries. And, every banks try to develop its internal model.

• Asia-Pacific Journal of Business
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• v.13 no.4
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• pp.163-175
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• 2022

Purpose - This study introduces a methodology for finding the optimal tracking error of active stock funds. Tracking error is commonly used in risk budgeting techniques as a concept of cost for alpha creation. Design/methodology/approach - This study uses a post-optimal smart beta portfolio that maximizes alpha under the given tracking error constraint. Findings - As a result of the analysis, the smart beta strategy that maximized alpha under the constraint of 0.15% daily tracking error shows the highest IR. This means the maximum theoretically achievable efficiency. In this regard, a fixed-effect panel regression analysis is conducted to evaluate the active efficiency of domestic stock funds. In addition to control variables based on previous studies, the effect of tracking error on alpha is analyzed. The alpha used in this model is calculated using the smart beta portfolio according to the size of the constraint of the tracking error as a benchmark. Contrary to theoretical estimates, in Korea, the alpha performance is maximized under a daily tracking error of 0.1%. This indicates that the active efficiency of domestic equity funds is lower than the theoretical maximum. Research implications or Originality - Based on this study, it is expected that it can be used for active risk management of pension funds and performance evaluation of active strategies.

• 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.