• 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.

• Industrial Engineering and Management Systems
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• v.15 no.1
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• pp.63-76
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• 2016

Multiperiod portfolio selection problem attracts more and more attentions because it is in accordance with the practical investment decision-making problem. However, the existing literature on this field is almost undertaken by regarding security returns as random variables in the framework of probability theory. Different from these works, we assume that security returns are uncertain variables which may be given by the experts, and take absolute deviation as a risk measure in the framework of uncertainty theory. In this paper, a new multiperiod mean absolute deviation uncertain portfolio selection models is presented by taking transaction costs, borrowing constraints and threshold constraints into account, which an optimal investment policy can be generated to help investors not only achieve an optimal return, but also have a good risk control. Threshold constraints limit the amount of capital to be invested in each stock and prevent very small investments in any stock. Based on uncertain theories, the model is converted to a dynamic optimization problem. Because of the transaction costs, the model is a dynamic optimization problem with path dependence. To solve the new model in general cases, the forward dynamic programming method is presented. In addition, a numerical example is also presented to illustrate the modeling idea and the effectiveness of the designed algorithm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.3
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• pp.123-130
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• 2022

Pair trading is a statistical arbitrage investment strategy. Traditionally, cointegration has been utilized in the pair exploring step to discover a pair with a similar price movement. Recently, the clustering analysis has attracted many researchers' attention, replacing the cointegration method. This study tests a clustering-driven pair trading investment strategy in the Korean stock market. If a pair detected through clustering has a large spread during the spread exploring period, the pair is included in the portfolio for backtesting. The profitability of the clustering-driven pair trading strategies is investigated based on various profitability measures such as the distribution of returns, cumulative returns, profitability by period, and sensitivity analysis on different parameters. The backtesting results show that the pair trading investment strategy is valid in the Korean stock market. More interestingly, the clustering-driven portfolio investments show higher performance compared to benchmarks. Note that the hierarchical clustering shows the best portfolio performance.

• 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.

• The Korean Journal of Financial Management
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• v.27 no.2
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• pp.35-62
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• 2010

This paper examines the existence of the fund performance persistence and the smart money effect in Korean stock market and tests the flow-induced price pressure (FIPP) hypothesis, that is, fund flows affect individual stock returns and mutual fund performance. This paper also tests whether the FIPP effect can cause the performance persistence using the monthly returns and stock holdings data of 2,702 Korean mutual funds from January 2002 to June 2008. The empirical results indicate that the performance persistence exists significantly for a long time but the smart money effect does not. The hedge portfolio constructed by buying funds with the highest past 12 months performance and selling funds with the lowest past 12 months performance earns 0.11%~1.05% monthly abnormal returns, on average, in 3 years from portfolio formation month, but the hedge portfolio constructed by buying funds with the highest past net fund inflows and selling funds with the lowest past net fund inflows cannot earn positive monthly abnormal returns and the size of negative abnormal returns of the portfolio increase as time goes on. We find the evidence that the FIPP hypothesis is significantly supported. We first estimate the FIPP measure for each individual stock using the trading volume resulting from past fund flows and then construct the hedge portfolio by buying stocks with the highest FIPP measure and selling stocks with the lowest FIPP measure. That portfolio earns significantly positive abnormal return, 1.01% at only portfolio formation month and cannot earn significant abnormal returns after formation month. But, the FIPP effect cannot cause the performance persistence because, within the same FIPP measure group, funds with higher past performance still earn higher monthly abnormal returns than those with lower past performance by 0.08%~0.77%, on average, in 2 years. These results imply that the main cause of the performance persistence in Korean stock market is the difference of fund managers' ability rather than the FIPP effect.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.63-73
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• 2023

This study explores modern portfolio theory by integrating the Black-Litterman portfolio with time-series clustering, specificially emphasizing K-shape clustering methodology. K-shape clustering enables grouping time-series data effectively, enhancing the ability to plan and manage investments in stock markets when combined with the Black-Litterman portfolio. Based on the patterns of stock markets, the objective is to understand the relationship between past market data and planning future investment strategies through backtesting. Additionally, by examining diverse learning and investment periods, it is identified optimal strategies to boost portfolio returns while efficiently managing associated risks. For comparative analysis, traditional Markowitz portfolio is also assessed in conjunction with clustering techniques utilizing K-Means and K-Means with Dynamic Time Warping. It is suggested that the combination of K-shape and the Black-Litterman model significantly enhances portfolio optimization in the stock market, providing valuable insights for making stable portfolio investment decisions. The achieved sharpe ratio of 0.722 indicates a significantly higher performance when compared to other benchmarks, underlining the effectiveness of the K-shape and Black-Litterman integration in portfolio optimization.

• The Korean Journal of Applied Statistics
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• v.34 no.1
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• pp.39-56
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• 2021

Many researches have been done on portfolio optimization since Markowitz (1952) published a diversified investment model. Markowitz's mean-variance portfolio optimization problem is established under the assumption that the distribution of returns follows a normal distribution. However, in real life, the distribution of returns does not follow a normal distribution, and variance is not a robust statistic as it is heavily influenced by outliers. To overcome these potential issues, mean-shortfall portfolio model was proposed that utilized downside risk, shortfall, as a risk index. In this paper, we propose a perturbation method that uses the shortfall as a risk index of the portfolio. The proposed portfolio utilizes an adaptive Lasso to obtain a sparse and stable asset selection because it can reduce management and transaction costs. The proposed optimization is easily applicable as it can be computed using an efficient linear programming. In our real data analysis, we show the validity of the proposed perturbation method.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.1
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• pp.29-43
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• 2022

This study measures the realized rate of return of venture capital(VC) fund at the level of investment agreement(as opposed to fund level returns reported by most of the relevant studies). It also measures the stock price return of the VC's portfolio firms (unlisted start-ups) at firm level(as opposed to fund returns) and its variance for the first time using unique data of the VC funds held by the Korean Venture Capital Association. Results of the analysis confirm that VC fund returns exceed individual stock price returns. Additionally, it is confirmed that VC portfolio firms exhibit a positive relationship between risk and return measured by total risk. Finally, we find that stock price returns at firm level are lower than that implied by the associated levels of risk. Consequently, this may make individual investors hesitate to directly buy unlisted startups' stocks even when investment in individual startup companies guarantees high risk-high returns relationship.

• The Journal of Fisheries Business Administration
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• v.45 no.1
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• pp.109-119
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• 2014

This study aimed to examine the applicability of a portfolio approach to the ecosystem-based fisheries management targeting the large purse seine fishery. Most fisheries are targeting multispecies and species are biologically and technically interacted each other. It enables a portfolio approach to be applied to find optimal production of each species through expected returns and risk analyses. Under specific assumptions on the harvest quota by species, efficient risk-return frontiers were generated and they showed a combination of optimal production level. Comparisons between portfolio and actual production provided a useful information for targeting strategy and management. Results also showed the possibility of effective multispecies fisheries management by imposing constraints on each species such as total allowable catch quotas.

• Asia-Pacific Journal of Business
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• v.10 no.3
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• pp.37-51
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• 2019

In this paper, we investigate the performance of anomaly factors in Asia-Pacific Stock market and show the higher Sharpe ratio of the volatility managed smart beta portfolio. The smart beta portfolio combines the benefit of passive strategy and active strategy. However, the smart beta portfolios are seems to be exposed to the risk of anomaly factors from the perspective of traditional financial equilibrium model. Therefore, the smart beta strategy may generate negatively skewed returns unappealing to investors having lower risk tolerance. Our empirical investigations find that the return of the Asia-Pacific region stock market is more volatile than other regions with the lower efficiency ratio. However, the value factor and the momentum factor of Asia-Pacific region both show good performances. More interestingly, we also find that managing the volatility of the momentum factor in Asia-Pacific stock market almost doubles the efficiency ratio.