• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.31-38
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• 2021

The study investigates the diversification behavior of Islamic stocks against US financial uncertainty. Considering limitations found in the literature, a comprehensive index of financial uncertainty (FU) is used, developed by Jurado, Ludvigson, and Ng (2015). The empirical analysis uses monthly data from four Islamic markets - Saudi Arabia, Malaysia, Indonesia, and Turkey - for the period from January 2010 to September 2019. Results of the bivariate EGARCH models show that Islamic stocks can be used for diversification purpose against the financial uncertainty of the US because the volatility of US uncertainty does not propagate in the Islamic stock markets. Moreover, findings show that the spillover effect of financial uncertainty varies with the FU forecast horizon. The spillover effect of FU increases with an increase in the FU forecast horizon and becomes significant over 3-month and 12-month periods in the case of Saudi Arabia. The current volatility of Islamic stock returns is independent of the size of shocks in past volatility. The leverage effect and asymmetry have been found in Saudi Arabia and Malaysia. The findings validate the arguments of the literature that Islamic markets are resilient facing uncertainties and perform well during crisis periods. The findings are important for investors in making better portfolio decisions.

• Asia-Pacific Journal of Business
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• v.11 no.1
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• pp.61-75
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• 2020

Purpose - The purpose of this study was to examine the efficiency of the foreign exchange markets in Korea, Japan and China. Design/methodology/approach - This study collected 1327 observations each of the daily closing exchange rates of the three currencies against the US dollar for the sample period from January 1, 2015 to January 31, 2020, based on the tests for autocorrelation, unit root tests and GARCH-M(1,1) model estimation. Findings - We have found that the autocorrelation test indicates the lack of autocorrelation and unit root test confirms the existence of unit roots in all times series of the three currencies, respectively. The GARCH-M(1,1) test results, however, suggest that the exchange rates do not follow a random walk process. In conclusion, the recent spot foreign exchange markets in Korea, Japan and China are believed to be informationally inefficient. Research implications or Originality - These findings have practical implications for both individual and institutional investors to be able to obtain excess returns on their investments in the foreign exchange markets in three countries by using appropriate risk management, portfolio strategy, technical analysis, etc. This study provides the first empirical examination on the foreign exchange market efficiency in the three biggest economies in Asia including China, which has been excluded from research due to its exchange rate regime.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.759-770
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• 2021

Using a DCC - GARCH model analysis, this paper examines the existence of financial contagion from the U.S. stock market to the Vietnamese and the Philippine stock markets during the global financial crisis and the COVID-19 pandemic crisis. We use daily data from the S&P 500 (U.S.), VN-Index (Vietnam), and the PSEi (the Philippines). As a result, there is no evidence of contagion from the U.S stock market to the Philippine stock market that can be found during global financial crisis, while the Vietnamese market is influenced by this effect. Besides, both these developing stock markets (the Vietnamese and Philippine stock markets) are influenced by the contagion effect in COVID-19 pandemic crisis. Another finding is that the contagion effect during the coronavirus pandemic crisis in Vietnam is smaller than that during the global financial crisis, however, the opposite is the case for the Philippines. It is noticed that the Philippines seems to be more affected by the contagion effect from the COVID-19 pandemic than Vietnam at the time of this study. Because financial contagion is important for monetary policy, asset pricing, risk measurement, and portfolio allocation, the findings in this paper may give some useful information for policymakers and investors.

• Journal of Distribution Science
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• v.20 no.7
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• pp.23-33
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• 2022

Purpose: Although foreign capital flows have played a vital role in fostering the economic growth in recipient countries, there are some concerns about the adverse impact of international capital flows on the banking stability. Hence, the study revisits this issue to explore the relationship between the different types of foreign investments and banking stability in ASEAN region. Research design, data and methodology: Based on the bank-level data of 96 commercial banks and country-level in six ASEAN countries from 2008 to 2019, we perform the multivariate regression analysis and provide a variety of robustness tests. Results: Our empirical evidence shows the volatility of foreign portfolio investments has significantly negative effect on the banking stability, besides that of foreign other investments has the similar influence but the result is relatively less pronounced in some robustness tests. Additionally, increasing trade cooperation and international distribution may lead countries to face higher risk of banking instability driven from these international investments. Meanwhile, the impact of foreign direct investments is positive, but the evidence is the least obvious. Conclusions: Our findings suggest policy-makers in ASEAN and emerging nations as a whole should carefully consider when building policies-related to mitigate the adverse impact of foreign capital flows.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.5
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• pp.1-9
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• 2022

The study examines stock prices (LOGKSE) and exchange rate (LOGPK)-Pakistani Rupee vis-à-vis US Dollar- interactions in Pakistan. This study employs a multivariate VAR-GARCH model using monthly data from January 2012 to October 2020. The results of the Johansen cointegration test show that there is no relationship between Foreign Exchange Market and Stock Market in the long run. In the short-run, stock exchange returns are affected slightly negatively by the changes in the foreign exchange market, but the foreign exchange market does not seem to be affected by the ups and downs of the stock exchange. The VAR model and Granger Causality show that both markets are strongly influenced by their own lagged values rather than by the lagged values of one another and show weak or no correlation between the two markets. Volatility persistence is observed in both the stock and foreign exchange markets, implying that shocks and past period volatility are major drivers of future volatility in both markets. Thus greater uncertainties today will induce panic and consequently generate higher volatility in the future period. This phenomenon has been observed many times on Pakistan Stock Exchange especially. The results have important implications for local international investors in portfolio diversification decisions and risk hedging strategies.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.635-647
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• 2006

Korean construction companies first advanced to the international markets in 1960's and so far have brought more than 4,900 projects which account for 193 billion dollars approximately. With the large increase of national employment and income being followed by the achievement, Korea's construction industry has made an enormous contribution to the improvement of domestic economy for the last 40 years. However, recently the increased risk in international markets as well as the sharpening competition with foreign companies promising in terms of advanced technologies and low labor cost have been driving Korean construction away from the market shares. According to ENR (Engineering News Record, 1994~2003), it is revealed that 15.1% of top 225 global contractors are suffering from loss in international construction markets. This phenomenon is largely due to the highly uncertain characteristics of international projects, which are inherently exposed to various and complicated risky situations. Furthermore, especially for Korean construction companies, it is often the case that the failure in an international construction project cannot be offset by even a sufficient number of successful domestic achievements. Therefore, not only the selective screening among the nominated projects which have strong possibility of collapse but the systematic strategies for controlling potential risk factors are also considered indispensable in international construction portfolio management. The purpose of this study is to first analyze the causal relationships of the profit-influencing variables and the project success, and develop the profitability forecasting model in international construction projects.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.63-83
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• 2019

Investors prefer to look for trading points based on the graph shown in the chart rather than complex analysis, such as corporate intrinsic value analysis and technical auxiliary index analysis. However, the pattern analysis technique is difficult and computerized less than the needs of users. In recent years, there have been many cases of studying stock price patterns using various machine learning techniques including neural networks in the field of artificial intelligence(AI). In particular, the development of IT technology has made it easier to analyze a huge number of chart data to find patterns that can predict stock prices. Although short-term forecasting power of prices has increased in terms of performance so far, long-term forecasting power is limited and is used in short-term trading rather than long-term investment. Other studies have focused on mechanically and accurately identifying patterns that were not recognized by past technology, but it can be vulnerable in practical areas because it is a separate matter whether the patterns found are suitable for trading. When they find a meaningful pattern, they find a point that matches the pattern. They then measure their performance after n days, assuming that they have bought at that point in time. Since this approach is to calculate virtual revenues, there can be many disparities with reality. The existing research method tries to find a pattern with stock price prediction power, but this study proposes to define the patterns first and to trade when the pattern with high success probability appears. The M & W wave pattern published by Merrill(1980) is simple because we can distinguish it by five turning points. Despite the report that some patterns have price predictability, there were no performance reports used in the actual market. The simplicity of a pattern consisting of five turning points has the advantage of reducing the cost of increasing pattern recognition accuracy. In this study, 16 patterns of up conversion and 16 patterns of down conversion are reclassified into ten groups so that they can be easily implemented by the system. Only one pattern with high success rate per group is selected for trading. Patterns that had a high probability of success in the past are likely to succeed in the future. So we trade when such a pattern occurs. It is a real situation because it is measured assuming that both the buy and sell have been executed. We tested three ways to calculate the turning point. The first method, the minimum change rate zig-zag method, removes price movements below a certain percentage and calculates the vertex. In the second method, high-low line zig-zag, the high price that meets the n-day high price line is calculated at the peak price, and the low price that meets the n-day low price line is calculated at the valley price. In the third method, the swing wave method, the high price in the center higher than n high prices on the left and right is calculated as the peak price. If the central low price is lower than the n low price on the left and right, it is calculated as valley price. The swing wave method was superior to the other methods in the test results. It is interpreted that the transaction after checking the completion of the pattern is more effective than the transaction in the unfinished state of the pattern. Genetic algorithms(GA) were the most suitable solution, although it was virtually impossible to find patterns with high success rates because the number of cases was too large in this simulation. We also performed the simulation using the Walk-forward Analysis(WFA) method, which tests the test section and the application section separately. So we were able to respond appropriately to market changes. In this study, we optimize the stock portfolio because there is a risk of over-optimized if we implement the variable optimality for each individual stock. Therefore, we selected the number of constituent stocks as 20 to increase the effect of diversified investment while avoiding optimization. We tested the KOSPI market by dividing it into six categories. In the results, the portfolio of small cap stock was the most successful and the high vol stock portfolio was the second best. This shows that patterns need to have some price volatility in order for patterns to be shaped, but volatility is not the best.

• Korean Journal of Construction Engineering and Management
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• v.16 no.6
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• pp.144-155
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• 2015

This paper is to understand investment's efficiency and performance of commercial real estate assets diversified by use and district. To do so, this paper divides two different commercial real estate markets(office build market and retail real estate market) in Seoul city by district into "GBD(Gangnam Business District), YBD(Yeouido Business District), and CBD(Central Business District)" and "GBD(Gangnam Business District), SBD(Shinchon Business District), and CBD(Central Business District)" respectively, configures these districts each other to structure portfolios as its portion varies based on Markowitz's Mean-Variance principle, and looks at risk-return relationship of portfolios to find out efficiency, performance, and optimal investment chosen based upon Sharpe's Performance Index. As a result, the portfolio configured by "10 to 30% of office building asset at CBD" and "70 to 90% of retail real estate asset at CBD" is shown to be the most optimal, suggesting the highest quarterly Sharpe's performance index of 2.7118~2.7776 with quarterly rate of return of 1.826%~1.838% and quarterly standard deviation of 0.573~0.589. Furthermore, it is obvious that diversified portfolio configured by use(office-retail) shows better investment performance than that by district with same type of asset(office-office or retail-retail). Finally, results driven from this research will play an important role to stimulate real estate and construction markets through enlarging ideas as to diversified investment by use and district on real estate indirect investment products.

• Journal of Industrial Convergence
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• v.20 no.11
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• pp.75-83
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• 2022

This study analyzes whether investor sentiment and liquidity explain the momentum phenomenon in the Korean stock market and whether it is a risk factor for the asset pricing model. The empirical analysis used the monthly returns of non-financial companies listed on the stock market during the period 2000-2021. As a result of the analysis, first, it was found that there is a momentum effect in Korea. This is the same result as the previous study, and since 2000, the momentum effect has been accepted as a general phenomenon in the Korean stock market. Second, if we look at the portfolio based on investor sentiment, investor sentiment is influencing momentum. In particular, when investor sentiment is negative, the return on the winner portfolio is high. Third, as a result of the analysis based on liquidity, the momentum effect disappears and a reversal effect appears. Fourth, it was found that investor sentiment and liquidity influence the momentum effect. This is a result of the strong momentum effect in the illiquid stock group with negative investor sentiment. Fifth, as a result of analyzing the effect of each factor on stock returns, it was found that both investor psychology and liquidity factors have a significant impact on returns. The estimated results provide evidence that the inclusion of these two factors in the Carhart four-factor model significantly increases the predictive power of the model. Therefore, it can be said that investor sentiment factors and liquidity factors are important factors in determining stock returns.

• The Korean Journal of Financial Management
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• v.24 no.4
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• pp.75-106
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• 2007

In this study, it is analyzed whether oil price plays a major role in the pricing return on Koran stock market and examined why the covariance risk between oil and return on stock is different in each industry. Firstly, this study explores whether the expected rate of return on stock is pricing due to global oil price factors as a function of risk premium by using a two-factor APT. Also, it is examined whether spill-over effects of oil price volatility affect the beta risk to oil price. Considering the asymmetry of oil price volatility, we use the GJR model. As a result, it shows that oil price is an independent pricing factor and oil price volatility transmits to stock return in only electricity and electrical equipment. Secondly, the two step-analyzing process is introduced to find why the covariance between oil price factor and stock return is different in each industry. The first step is to study whether beta risk exists in each industry by using two proxy variables like size and liquidity as control variables. The second step is to grasp the systematic relationship between the difference of liquidity and size and beta to oil price factor by using the panel-data model which can be analyzed efficiently using the cross-sectional data formed with time series. Through the analysis, we can argue that oil price factor is an independent pricing factor in only electricity and electrical equipment having the greatest market capitalization, and know that beta risk to oil price factor is a proxy of size in the other industries. According to the result of panel-data model, it is argued that the beta to oil price factor augments when market capitalization increases and this fact supports the first assertion. In conclusion, the expected rate of return of electricity and electrical equipment works as a function of risk premium to market portfolio and oil price, and the reason to make beta risk power differentiated in each industry attributes to the size.