• The Journal of Asian Finance, Economics and Business
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• v.9 no.3
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• pp.203-215
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• 2022

Bayesian Networks are multivariate probabilistic factor graphs that are used to assess underlying factor relationships. From January 2005 to December 2018, the study examines how Dynamic Bayesian Networks can be utilized to estimate portfolio risk and return as well as determine inter-factor relationships among reversal profit-generating components in Pakistan's emerging market (PSX). The goal of this article is to uncover the factors that cause reversal profits in the Pakistani stock market. In visual form, Bayesian networks can generate causal and inferential probabilistic relationships. Investors might update their stock return values in the network simultaneously with fresh market information, resulting in a dynamic shift in portfolio risk distribution across the networks. The findings show that investments in low net profit margin, low investment, and high volatility-based designed portfolios yield the biggest dynamical reversal profits. The main triggering aspects related to generation reversal profits in the Pakistan market, in the long run, are net profit margin, market risk premium, investment, size, and volatility factor. Investors should invest in and build portfolios with small companies that have a low price-to-earnings ratio, small earnings per share, and minimal volatility, according to the most likely explanation.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2000.11a
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• pp.346-356
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• 2000

This paper aims to analyse the relationship between R＆D investment and economic growth in Korea. The analysis result shows 38 percent of average economic growth rate(7.1%) of Korea between 1976 and 1998 was achieved by the growth of Total Factor Productivity (TFP), and the R&D investment during the period contributed in achieving the economic growth rate by as much as 9.86 percent. In the process of the estimate, the rate of return of the R&D investment from both government and private was calculated as 47 percent. The relationship between private R&D investment, government R&D investment and the GDP was also investigated, and it was estimated that the private sector invested 2.0 percent of the GDP in R&D during the period, and was found that 1 won of government R&D investment induced 0.202 won of private sector's R&D investment. However, the time-lag effect, which is naturally believed to exist between the R&D investment and the economic growth, could not be analysed in a mathematical form, because of the lack of the data to establish this relationship. However, this paper believe that the time-lag effect in this relationship was included implicitly by using the data of 23 years.

• IE interfaces
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• v.24 no.1
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• pp.24-39
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• 2011

In this paper, we study the methodology for the measurement and integration of market risk and credit risk using Copula. We apply the methodology of Rosenberg, and Schuermann(2006) to the assets of pension system. Firstly we estimate dynamics of risk factors and their effects on investment returns, then use the estimated result to simulate future movement of risk factors and distribution of investment returns. Finally we measure integrated risk using integrated return distribution by Copula and simulated future investment return distributions. We found the integrated risk changing with the correlation of risks and investment weights of risks and confirmed the diversification effect of risks. This result is consistent when we use normal Copula and normal marginals, t-Copula and t(3) marginals, and normal Copula and non-parametric marginals. And in the case of non-parametric maginals, larger integrated risk is calculated. It means that use of non-parametric marginals is more conservative.

• The Journal of Industrial Distribution & Business
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• v.13 no.1
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• pp.23-32
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• 2022

Purpose: This study used ESG grade, but defined AESG, adjusted to the size of a company and examines whether it can be used as an investment strategy. Research design, data and methodology: The analysis sample in this study is a company that has given an ESG rating among companies listed on the Korea Stock Exchange. We examine the results through portfolio analysis and Fama-macbeth regression analysis. Results: As result of examining the long-only performance and the long-short performance by constructing quintile portfolios, it was observed that a significant positive return was shown. It was observed that there was an alpha that could not be explained in asset pricing models. Also, AESG had a return prediction effect in the result of a Fama-Macbeth regression that controlled corporate characteristic variables in individual stocks. Next, we confirmed AESG's usage through various portfolio composition. In the portfolio optimization, the Risk Efficient method was the most superior in terms of sharpe ratio and the construct multi-factor model with Value, Momentum and Low Vol showed statistically significant performance improvement. Conclusions: The results of this study suggest that it can be helpful in ESG investment to reflect the ESG rating of relatively small companies more through the scale adjustment of the ESG rating (i.e.AESG).

• Journal of the Korean Operations Research and Management Science Society
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• v.38 no.4
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• pp.35-52
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• 2013

Markowitz's portfolio selection model is used to construct an optimal portfolio which has minimum variance, while satisfying a minimum required expected return. The model uses estimators based on analysis of historical data to estimate the returns, standard deviations, and correlation coefficients of individual stocks being considered for investment. However, due to the inaccuracies involved in estimations, the true optimality of a portfolio constructed using the model is questionable. To investigate the effect of estimation inaccuracy on actual portfolio performance, we study the changes in a portfolio's realized return and standard deviation as the accuracy of the estimations for each stock's return, standard deviation, and correlation coefficient is increased. Furthermore, we empirically analyze the portfolio's performance by comparing it with the performance of active mutual funds that are being traded in the Korean stock market and the KOSPI benchmark index, in terms of portfolio returns, standard deviations of returns, and Sharpe ratios. Our results suggest that, among the three input parameters, the accuracy of the estimated returns of individual stocks has the largest effect on performance, while the accuracy of the estimates of the standard deviation of each stock's returns and the correlation coefficient between different stocks have smaller effects. In addition, it is shown that even a small increase in the accuracy of the estimated return of individual stocks improves the portfolio's performance substantially, suggesting that Markowitz's model can be more effectively applied in real-life investments with just an incremental effort to increase estimation accuracy.

• The Korean Journal of Financial Management
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• v.22 no.2
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• pp.135-164
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• 2005

We analyze trade and balance records of 10,000 stock investment accounts of individual investors for the period of 1998 to 2003. Individual investors em an annual gross return of 12.3% while the KOSPI and the value weighted composite including KOSDAQ stocks yield 13.6% and 9.7% respectively during the same period. Net return performance is 8.3%, a drop of 5.3% mainly due to heavy trading. Individual investors' annual turnover amounts to over 270 percent. In an analysis of groups formed on the month's end position value, the performance of the top quintile is found comparable to the market while the rest yield significantly lower risk-adjusted returns than the market. We also find evidence rejecting the rational expectation model while supporting the overconfidence hypothesis which states overconfidence leads to a higher level of trading, resulting in poor performance. Individuals tilt their stock investment toward high-beta, small, and value stocks.

• Knowledge Management Research
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• v.22 no.1
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• pp.21-37
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• 2021

The purpose of this study is to explore financial investment knowledge related to multi-strategy, which is not generally shared. Through case studies, we will share it with the domestic hedge fund market. Since the era of full-fledged private equity hedge funds in Korea opens, many funds are created; however, reality is that there is a lack of diversity in strategies. Initially, it started with a simple stock long/short strategy, and various strategies such as mezzanine and alternative investments are in use but funds using multi-strategy are limited. This study aims to present an empirical application plan for hedge fund management strategies using a case study. It will specifically focus on process of achieving Absolute Return using the Multi Strategy technique actively used in securities firms' Prop Trading. With the results of this study, we intend to contribute to those fund managers and desired researchers who are utilizing multiple strategies in the hedge fund management to pursue Absolute Return and to help them strengthening their financial knowledge and competitiveness.

• Korean Management Science Review
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• v.30 no.1
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• pp.73-89
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• 2013

This paper develops an investment algorithm based on Markowitz's Portfolio Selection Theory, using historical stock return data, and empirically evaluates the performance of the proposed algorithm in the U.S. and the Hong Kong stock markets. The proposed investment algorithm is empirically tested with the 30 constituents of Dow Jones Industrial Average in the U.S. stock market, and the 30 constituents of Hang Seng Index in the Hong Kong stock market. During the 6-year investment period, starting on the first trading day of 2006 and ending on the last trading day of 2011, growth rates of 12.63% and 23.25% were observed for Dow Jones Industrial Average and Hang Seng Index, respectively, while the proposed investment algorithm achieved substantially higher cumulative returns of 35.7% in the U.S. stock market, and 150.62% in the Hong Kong stock market. When compared in terms of Sharpe ratio, Dow Jones Industrial Average and Hang Seng Index achieved 0.075 and 0.155 each, while the proposed investment algorithm showed superior performance, achieving 0.363 and 1.074 in the U.S. and Hong Kong stock markets, respectively. Further, performance in the U.S. stock market is shown to be less sensitive to an investor's risk preference, while aggressive performance goals are shown to achieve relatively higher performance in the Hong Kong stock market. In conclusion, this paper empirically demonstrates that an investment based on a mathematical model using objective historical stock return data for constructing optimal portfolios achieves outstanding performance, in terms of both cumulative returns and Sharpe ratios.

• Proceedings of the Korea Association of Information Systems Conference
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• 2005.12a
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• pp.275-280
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• 2005

Net present value (NPV) and return on investment (ROI) are commonly used to evaluate investment in new technologies. Sometimes, however, measuring the value of investment in new IT becomes very difficult due to its wide scope of application coupled with embedded options in its adoption. Therefore, comprehensive but easily understandable methodologies are needed to solve the complicated problems resulting from the complexity of new technologies. This paper employs a real option analysis to evaluate RFID adoption in the supply chain. Real options analysis should be a better way to evaluate a disruptive technology like RFID.

• The Journal of Information Systems
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• v.27 no.3
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• pp.43-62
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• 2018

Purpose Since the Bitcoin, which was the first virtual currency, was made at 2009, almost 1,000 virtual currencies appeared onstage in the world. Even though virtual currencies have the function of money as a medium of exchange or contract, any of those has not yet entered the commercialization stage. Instead, some of the virtual currencies show the nature of investment assets. In the case of virtual money investment, users tend to use all the information of the world because information transfer is very easy and capital movement is almost free between different countries. In addition, as the transaction sizes of virtual currencies increase, a virtual currency price is no longer independent and is likely to be affected by the prices of other virtual currencies. Therefore, it is necessary to understand the influence among virtual currency markets, which helps successful implementation of investment strategies. Design/methodology/approach This study focuses on the investment product function of virtual money and conducts the analysis using the time series model used in the financial and economic areas. In this paper, we try to analyze the return and volatility transfer effect of virtual money markets through GJR-GARCH model. Findings This study is expected to find out whether we can make market forecasts through reflecting changes in other markets. In addition, we can reduce the trial and error of user decision making by using the information on the yield and volatility transition effect derived from the research results, and it is expected to reduce the opportunity cost of users.