Academic literature on the topic 'Asset allocation – Korea'

This study examines whether the management style of a fund differs depending on the type of fund being managed for tax purposes, given the rules of temporary tax relief for fund investments. The study considers a change in the ratio of tax-favored assets to the net asset value of a tax relief qualified fund around the effective date of tax relief laws in South Korea in 2007 and 2016. A regression model is used to test sample data from domestic and overseas equity funds available in the three months before and after the 2007 and 2016 Restriction of Special Taxation Act came into effect. It was found that the ratio of the value of tax-favored assets to the net asset value in the tax relief qualified fund increased significantly since the enactment of tax relief laws in both 2007 and 2016. These findings suggest that fund managers may try to change the asset allocation in a managed fund to increase the after-tax return of the fund investor, which means that fund managers do take into account the potential tax burden on fund investors and try to minimize it. AcknowledgmentThis work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF- 2019S1A5A8035027).

Foreign institutional investors are one of the major groups of investors in the financial sector. Because of their particular characteristics and limitations, 'conventional assets,' such as equities, bonds, and cash, dominate institutional investors' asset allocation. To attain higher and more consistent return profiles, major Korean institutional investors have been rearranging their asset allocation strategies to include more exposure to the real estate industry. Real estate prices grow more efficient and closer to their long-term equilibrium as a result of rules. Any foreigner intending to purchase property in Korea must notify the government, according to the Real Estate Transaction Report, Etc. Act. If a foreign buyer chooses not to file an acquisition report, they must comply with the same legislation (the Act on Real Estate Transaction Report, etc.) that requires the submission of all real estate purchase reports. International investors that invest in designated zones for foreign investment or in firms with foreign ownership that provide certain recognized high-level technology services can additionally benefit from other tax incentives. This study aims to find out, because of these rules and policies, investing in the real estate industry in Korea might seem to be complicated but the after effects of these investments looks much brighter in the future.

Purpose The purpose of this paper is to investigate US noncombatant evacuation operations (NEO) in South Korea and devise planning and management procedures that improve the efficiency of those missions. Design/methodology/approach It formulates a time-staged network model of the South Korean noncombatant evacuation system as a mixed integer linear program to determine an optimal flow configuration that minimizes the time required to complete an evacuation. This solution considers the capacity and resource constraints of multiple transportation modes and effectively allocates the limited assets across a time-staged network to create a feasible evacuation plan. That solution is post-processed and a vehicle routing procedure then produces a high resolution schedule for each individual asset throughout the entire duration of the NEO. Findings This work makes a clear improvement in the decision-making and resource allocation methodology currently used in a NEO on the Korea peninsula. It immediately provides previously unidentifiable information regarding the scope and requirements of a particular evacuation scenario and then produces an executable schedule for assets to facilitate mission accomplishment. Originality/value The significance of this work is not relegated only to evacuation operations on the Korean peninsula; there are numerous other NEO and natural disaster related scenarios that can benefit from this approach.

Financial sustainability for individuals has become more important due to the increase in life expectancy. In personalized lifetime financial planning, human capital is critical for incorporating the life-cycle of individuals. This study focuses on human capital modeling based on features such as education level and working industry, and presents how difference in human capital can affect the optimal asset allocation. By analyzing the Korean labor and income panel survey data, fixed effects regression was performed to model human capital and a portfolio model that maximizes utility of total wealth is solved to optimize the lifetime financial plan. The empirical results show that individuals with human capital that are more correlated with stocks are advised to reduce allocation in stocks.

Unconditional and conditional correlations have played a central role in portfolio analysis, optimization, and performance measurement. However, recent studies show these two correlation measures are inappropriate for measuring both financial integration and, therefore, diversification benefits. We use an alternative correlation measure that we refer to by factor model-implied correlation estimated from the systematic (predictable) portion of returns of a multi-factor model with several global risk factors. Estimated implied correlations, covariances, variances, and in-sample (predicted) mean returns are used to calculate optimal US and Asian equities’ asset allocation weights in alternative Global equity portfolios varying by Asian equity market combined with US equities, as well as by whether: (i) implied or unconditional statistics are used; and (ii) portfolios are optimized by Sharpe’s ratio-maximization or variance-minimization. Risk-adjusted returns of alternative actively-managed Global equity portfolios are compared to US equities’ risk-adjusted returns. We find Global equity portfolios with asset allocation weights calculated using factor model-implied statistics uniformly yield higher risk-adjusted returns than US equities and Global equity portfolios with asset allocation weights calculated using unconditional portfolio statistics. In actively-managed Global equity portfolios with asset allocation weights calculated using implied statistics, India and Taiwan consistently rank as top contributors, while South Korea, Singapore, and Hong Kong consistently rank as bottom contributors to enhancing US equities’ risk-adjusted returns. While our analyses are dynamic, they use implied portfolio statistics estimated from historical returns’ distributions. Future studies can extend this research using conditional(out-of-sample) ex-ante estimates of systematic returns, covariances, variances, and correlations in examining emerging markets’ contributions to developed markets’ equities.

Purpose – The purpose of this paper is to examine the regime shifts and stock market volatility in the stock market returns of seven emerging economies popularly called as “BRIICKS” which stands for Brazil, Russia, India, Indonesia, China, South Korea and South Africa, over the period from February 1996 to January 2012 by applying Markov regime switching (MS) in mean-variance model. Design/methodology/approach – The authors apply MS model developed by Hamilton (1989) using its mean-variance switching framework on the monthly returns data of BRIICKS stock markets. Further, the estimated probabilities along with variances have been used to calculate the time-varying volatility. The authors also examine market synchronization and portfolio diversification possibilities in sample markets by calculating the Logit transformation based cross-market correlations and Sharpe ratios. Findings – The applied model finds two regimes in each of these markets. The estimated results also helped in formulating the asset allocation strategies based on market synchronization and Sharpe ratio. The results suggest that BRIICKS is not a homogeneous asset class and each market should be independently evaluated in terms of its regime-switching behavior, volatility persistence and level of synchronization with other emerging markets. The study finally concludes that Russia, India and China as the best assets to invest within this emerging market basket which can be pooled with a mature market portfolio to achieve further benefits of risk diversification. Research limitations/implications – The study does not provide macroeconomic and financial explanations of the observed differences in dynamics among sample emerging stock markets. The study does not examine these markets under multivariate framework. Practical implications – The results highlight the role of regime shifts and stock market volatility in the asset allocation and risk management. This study has important implications for international asset allocation and stock market regulation by way of identifying and recognizing the differences on regimes and on the dynamics of the swings which can be very useful in the field of portfolio and public financial management. Originality/value – The paper is novel in employing tests of MS under mean-variance framework to examine the regime shifts and volatility switching behavior in seven promising BRIICKS stock market. Further, using MS model, the authors analyze the duration (persistence) of each identified regime across sample markets. The empirical results of MS model have been used for making portfolio allocation strategies and also examine the synchronization across markets. All these aspects of stock market regime have been largely ignored by the existing studies in emerging market context particularly the BRIICKS markets.

This study analyzes whether a value averaging (VA) strategy, which adjusts the amount of investment each period to achieve the target amount of investment in risk assets, as a modified form of a dollar cost averaging (DCA) strategy, improves investment performance. Using 18.5 years of fund market data in Korea from 2001 to June 2019, we compare the investment performance of VA strategy relative to two alternatives: DCA strategy, which invests a certain amount in each period, and Buy-and-Hold (BH) strategy, which refers to half-and-half asset allocation between risky and risk-free assets and has an expected return which is the same as that of DCA in the ex-ante sense. Our historical performance analysis reveals that the VA strategy has lower average return and higher standard deviation compared to the BH strategy and has lower average return and lower standard deviation compared to the DCA strategy. These findings are in stark contrast to the claims made by advocates of VA strategy that the strategy improves investment performance.

<abstract><p>The traditional mean-variance portfolio optimization models in practice have suffered from complexity and heavy computation loads in the process of selecting the best assets for constructing a portfolio. If not, they are considerably departed from the theoretically optimized values. In this work, we develop the optimized portfolio investment strategy in which only one asset substitution occurs when re-balancing a portfolio. To do this, we briefly look into a quadratically constrained quadratic programming (QCQP), which has been well-studied for the non-negative solution. Based on the quadratic programming, an efficient scheme is presented for solving the large-scale inverse problem. We more precisely update the rank of an inverse matrix, so that the optimal solution can be easily and quickly obtained by our proposed scheme.</p> <p>Various numerical and practical experiments are presented to demonstrate the validity and reliability of our scheme. Our empirical application to the U.S. and South Korea stock markets is tested and highlighted. Moreover, comparisons of a random allocation strategy and our proposed scheme reveal the better performance in the lower risks and higher expected returns obtained by our scheme.</p></abstract>

Executive Summary Cross-sectional volatility measures dispersion of security returns at a particular point of time. It has received very little focus in research. This article studies the cross-section of volatility in the context of economies of Brazil, Russia, India, Indonesia, China, South Korea, and South Africa (BRIICKS). The analysis is done in two parts. The first part deals with systematic volatility (SV), that is, cross-sectional variation of stock returns owing to their exposure to market volatility measure ( French, Schwert, & Stambaugh, 1987 ). The second part deals with unsystematic volatility (UV), measured by the residual variance of stocks in a given period by using error terms obtained from Fama–French model. The study finds that high SV portfolios exhibit low returns in case of Brazil, South Korea, and Russia. The risk premium is found to be statistically significantly negative for these countries. This finding is consistent with Ang et al. and is indicative of hedging motive of investors in these markets. Results for other sample countries are somewhat puzzling. No significant risk premiums are reported for India and China. Significantly positive risk premiums are observed for South Africa and Indonesia. Further, capital asset pricing model (CAPM) seems to be a poor descriptor of returns on systematic risk loading sorted portfolios while FF is able to explain returns on all portfolios except high SV loading portfolio (i.e., P1) in case of South Africa which seems to be an asset pricing anomaly. It is further observed that high UV portfolios exhibit high returns in all the sample countries except China. In the Chinese market, the estimated risk premium is statistically significantly negative. This negative risk premium is inconsistent with the theory that predicts that investors demand risk compensation for imperfect diversification. The remaining sample countries show significantly positive risk premium. CAPM does not seem to be a suitable descriptor for returns on UV sorted portfolios. The FF model does a better job but still fails to explain the returns on high UV sorted portfolio in case of Brazil and China and low UV sorted portfolio in South Africa. The findings are relevant for global fund managers who plan to develop emerging market strategies for asset allocation. The study contributes to portfolio management as well as market efficiency literature for emerging economies.

The budget for disaster and safety management can be characterized as a large-scale public asset in which the government has a significant role. However, this budget has been managed in a somewhat scattered and inconsistent manner by different government ministries, until the Sewol ferry incident in Korea 2014. After the Sewol incident, the Ministry of Public Safety and Security has introduced a prior consultation system for budget allocation in the field of disaster and safety management, so that the budget can be reviewed in a holistic manner, effectively managed, and invested according to agreeable priorities. This study introduces the prior consultation system for the budget in disaster and safety management, which has been implemented since 2015, analyzes budget allocation procedures, and provides possible solutions to improve the current status of the prior consultation system for classification and prioritization. (1) The issues that were found in the budget plans for the fiscal years of 2016 to 2017 are, firstly, unclear classification criteria that made it hard to differentiate much more disaster-related programs and projects from less-related ones. Secondly, investment priorities of projects and programs for disaster and safety management are controversial, due to the lack of objective standards and procedures. To firmly settle down the prior consultation system, several possible solutions to these two main issues are suggested. (2) To improve actual budget classification, the current classification system needs to be reviewed at first, and social issues will be analyzed to be included as a criterion and, finally, authors will propose additional criteria and items based on the Disaster and Safety Management Framework Act. In order to improve prioritization procedures for budget allocation, disaster damage and loss are compiled to find implications and other related prioritization practices, such as prioritization in natural disaster-prone area improvement programs, which need to be analyzed to provide suggestions on improvement in prioritization. Through the proposed improvement of the classification system, projects that are not related to disaster safety are not included in the disaster safety project. Projects that are deeply related to disaster safety can be further explored. It is also recommended that an investment direction be established in consideration of damage characteristics through the investment priority improvement plan, and that qualitative assessment criteria should be considered in the criteria for similar projects, and weights should be required. The improvement measures derived can be used as follows: the scale can be clearly identified by clarifying the subject of the disaster safety budget. This gives a sense of where investment is lacking, and where it is sufficient. Investment priority is reviewed in a variety of ways, preventing budgetary bias in advance. As a result, these two improvements enable efficient operation of the disaster safety budget.