• 수산경영론집
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• 제44권2호
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• pp.1-17
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• 2013

We investigate the appropriateness of the fixed 12% discount rate to be used in estimating the amount of compensation for revoking a license for fishery business by the Enforcement Decree of Fisheries Act in Korea. We also suggest the appropriate discount rate fully reflecting the change of market interest rate in the Korean financial market. The capital asset pricing model, or, CAPM is the best known model of risk and return, and is widely used to estimate the expected rate of return for the risky projects. Even though the CAPM implies that the discount rate or the expected rate of return should change as the related market factors do, the discount rate used to estimate compensation for revoking a license for fishery business remains to be the same 12% rate for the last 15 years by law. During this period, however, the yield to maturity for the 5-year government bonds in Korea has dramatically changed from about 12% to less than 3%. In order to provide the fair compensation for the damages against the coastal fisheries and evaluate the intrinsic value of fishery resources in the coastal areas, we suggest that the appropriate discount rate should be determined by the yield to maturity of the government bonds with 5-year maturity, instead of the current fixed 12% interest rate.

• East Asian Economic Review
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• 제21권2호
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• pp.147-165
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• 2017

This study quantifies the dynamic interrelationship between the KOSPI index return and search query data derived from the Naver DataLab. The empirical estimation using a bivariate GARCH model reveals that negative contemporaneous correlations between the stock return and the search frequency prevail during the sample period. Meanwhile, the search frequency has a negative association with the one-week- ahead stock return but not vice versa. In addition to identifying dynamic correlations, the paper also aims to serve as a test bed in which the existence of profitable trading strategies based on big data is explored. Specifically, the strategy interpreting the heightened investor attention as a negative signal for future returns appears to have been superior to the benchmark strategy in terms of the expected utility over wealth. This paper also demonstrates that the big data-based option trading strategy might be able to beat the market under certain conditions. These results highlight the possibility of big data as a potential source-which has been left largely untapped-for establishing profitable trading strategies as well as developing insights on stock market dynamics.

• The Journal of Asian Finance, Economics and Business
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• 제8권2호
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• pp.697-710
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• 2021

The purpose of this study is to explore the reaction of sharia stock in the Indonesian capital market to the global Covid-19 pandemic. The method used in this study is an event study with a Market Adjusted Model (MAM) approach. The population of this study is shares listed on the Indonesian Stock Exchange (IDX), with the sample chosen from the Jakarta Sharia (Islamic) Index. The result of this study found that the global Covid-19 pandemic is bad news, with the indicators as follows: a) the average expected return is negative; b) the average actual return is negative; c) the average abnormal return is negative, and d) the increase selling action of stock as a cut loss strategy. There is a negative abnormal return and significant Trading Volume Activity (TVA) before, during, and after the announcement of the global Covid-19 pandemic. However, this study found no difference in abnormal return and TVA before and after the announcement of the global Covid-19 pandemic. From these results, this study indicates that the sharia stocks in the capital market in Indonesia can respond quickly to the information that existed. Therefore, the capital market of Indonesia is a capital market with a semi-strong efficient form.

• 산경연구논집
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• 제11권3호
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• pp.7-17
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• 2020

Purpose: This study reexamines the test on the pricing of accruals quality. Theory suggests that information risk is a priced risk factor. Using accruals quality as the proxy for information risk, researchers have tested the pricing of information risk. The results are inconsistent potentially because of the information shock in the realized returns that are used as the proxy for expected returns. Based on this argument, this study revisits this issue excluding information-shock-free measure of expected returns. Research design, data and methodology: This study estimates expected returns using the vector autoregression model. This method extracts information shocks more thoroughly than the methods in prior studies; therefore, the concern regarding information shock is minimized. As risk premiums are larger in recession periods than in expansion periods, recession and expansion subsamples were used to confirm the robustness of the main findings. For the pricing test, this study uses two-stage cross-sectional regression. Results: Empirical results find evidence that accruals quality is a priced risk factor. Furthermore, this study finds that the pricing of accruals quality is observed only in recession periods. Conclusions: This study supports the argument that accruals quality, as well as the pricing of information risk, is a priced risk factor.

• 한국경영과학회지
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• 제32권3호
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• pp.1-15
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• 2007

In this paper, the return link of interactive GEO satellite network providing multimedia services is considered. First, we classify data by delay characteristics, and analyze the numbers of expected lost packets and expected delay packets for each data class of each terminal. Next we mathematically formulate optimal rate scheduling model to minimize the weighted sum of the numbers of expected lost packets and expected delay packets considering priority of each data class. We also suggest a dynamic rate scheduling scheme based on Lagrangean relaxation technique and subgradient technique to solve the proposed model in a fast time. Extensive experiments show that the proposed scheme provides encouraging results.

• 한국경영과학회지
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• 제38권4호
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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 Journal of Asian Finance, Economics and Business
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• 제5권3호
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• pp.19-29
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• 2018

This research examined the alternatives of Jensen's alpha (α) estimation models in the Capital Asset Pricing Model, discussed by Treynor (1961), Sharpe (1964), and Lintner (1965), using the robust maximum likelihood type m-estimator (MM estimator) and Bayes estimator with conjugate prior. According to finance literature and practices, alpha has often been estimated using ordinary least square (OLS) regression method and monthly return data set. A sample of 50 securities is randomly selected from the list of the S&P 500 index. Their daily and monthly returns were collected over a period of the last five years. This research showed that the robust MM estimator performed well better than the OLS and Bayes estimators in terms of efficiency. The Bayes estimator did not perform better than the OLS estimator as expected. Interestingly, we also found that daily return data set would give more accurate alpha estimation than monthly return data set in all three MM, OLS, and Bayes estimators. We also proposed an alternative market efficiency test with the hypothesis testing Ho: α = 0 and was able to prove the S&P 500 index is efficient, but not perfect. More important, those findings above are checked with and validated by Jackknife resampling results.

• 한국기계가공학회지
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• 제5권2호
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• pp.49-55
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• 2006

In the consideration of the problem occurred by certain return bender brazing welding works that depend only on handworks, the automatization of the whole production line is impossible due to the high dependency of skillful workers. In addition, it is difficult to establish a standardization due to the various heat exchanger model and irregular amount of orders, and the fault reduction is also impossible due to the severe difference in brazing conditions. It is necessary to develop a method, which quantitively analyzes the problem existed in this manual brazing welding of return benders and technically solves that problem, and to lead the improvement of the productivity and cost reduction in order to increase the business competitive power. Then, this will contribute the technical development of automatic welding for Korea's heat exchanger businesses. Thus, this study develops an automatic technology, which automatically controls the flame strength using digital control methods, for various models and produces a sample model. It is possible to increase the productivity and produce uniformed and qualified products by solving the problem existed in manual processes using the developed automatic return bender brazing system. In addition, the brazing condition can be automatically controlled according to the model and line speed, and such an economical operation can reduce the production cost. The developed system is expected to future applications not only heat exchangers in the field of refrigeration and air conditioning, but also other various industrial fields that apply heat exchangers, such as car and boiler industries.

• 재무관리연구
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• 제24권3호
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• pp.153-186
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• 2007

It is well known that the distributional properties of financial asset returns exhibit fatter-tails and skewer-mean than the assumption of normal distribution. The correct assumption of return distribution might improve the estimated performance of the Value-at-Risk(VaR) models in financial markets. In this paper, we estimate and compare the VaR performance using the RiskMetrics, GARCH and FIGARCH models based on the normal and skewed-Student-t distributions in two daily returns of the Korean Composite Stock Index(KOSPI) and Korean Won-US Dollar(KRW-USD) exchange rate. We also perform the expected shortfall to assess the size of expected loss in terms of the estimation of the empirical failure rate. From the results of empirical VaR analysis, it is found that the presence of long memory in the volatility of sample returns is not an important in estimating an accurate VaR performance. However, it is more important to consider a model with skewed-Student-t distribution innovation in determining better VaR. In short, the appropriate assumption of return distribution provides more accurate VaR models for the portfolio managers and investors.

• Management Science and Financial Engineering
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• 제10권1호
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• pp.25-41
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• 2004

There have been many studies to build a model that can help investors construct optimal portfolio. Most of the previous models, however, are based upon the path-breaking Markowitz model (1959) which is a quantitative model. One of the most important problems with that kind of quantitative model is that, in reality, most of the investors use not only quantitative, but also qualitative information when they select their optimal portfolio. Since collecting both types of information from the markets are time consuming and expensive, making a set of target assets smaller, without suffering heavy loss in the rate of return, would attract investors. To extract only desired assets among all available assets, we need knowledge that identifies investors' preference for the risk of the assets. This study suggests two-layer decision-making rules capable of identifying an investor's risk preference and an architecture applying them to a quantitative portfolio model based on risk and expected return. Our knowledge-based portfolio system is to build an investor's preference-oriented portfolio. The empirical tests using the data from Korean capital markets show the results that our model contributes significantly to the construction of a better portfolio in the perspective of an investor's benefit/cost ratio than that produced by the existing portfolio models.