• Asian Journal of Business Environment
• /
• v.9 no.4
• /
• pp.5-13
• /
• 2019

Purpose - This research is aimed to investigate the impact of the Information and Communication Technology (hereinafter ICT) development index and ICT investment on Indonesian economic growth. Research design, data and methodology - The data used consist of ICT development index, government expenditure on ICT sector, and economic growth from 33 provinces in Indonesia from 2012 to 2015. Based on the Networked Readiness Index published by the World Economic Forum (WEF), Indonesia was ranked 80^th among 142 countries in 2012 and had climbed 64^th in 2014. This indicates that the businesses in Indonesia have adopted ICTs to increase productivity and expand their activities. Panel data regression analysis is performed to reveal the change of the impact over time in each of the provinces. Result - The ICT development index and government expenditure for ICT have a positive effect on the economic growth of all provinces, although the impact is different in each of the provinces. There is a digital gap between the provinces, especially the large digital gap occurring with DKI Jakarta. The provinces of Eastern Indonesia such as NTT and Papua are still relatively slow in development of ICT. Conclusions - ICT development index and allocation of local government expenditure for ICT have significant effect on economic growth. ICT development index has a bigger role in increasing economic growth.

• The Journal of Asian Finance, Economics and Business
• /
• v.7 no.8
• /
• pp.197-204
• /
• 2020

Nowadays, many construction engineering and technology enterprises are evolving to find that prosperity is driven and inspired by an open economy with dynamic markets and fierce multifaceted competition. Besides brand and product uniqueness, the ability to quickly provide customers with quotes are matters of concern. Such a requirement for prompt cost estimation of construction investment projects with the use of a construction price index poses a significant challenge to contractors. This is because the nature of the construction industry is shaped by changes in domestic and foreign economic factors, socio-financial issues, and is under the influence of various micro and macro factors. This paper presents a fuzzy decision-making approach for calculating critical factors that affect the construction price index. A qualitative approach was implemented based on in-depth interviews of experts in the construction industry in Vietnam. A synthetic comparison matrix was calculated using Buckley approach. The CoA approach was applied to defuzzified the fuzzy weights of factors that affect the construction price index. The research results show that the top five critical factors affecting the construction price index in Vietnam are (1) consumer price index, (2) gross domestic product, (3) basic interest rate, (4) foreign exchange rate, and (5) total export and import.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2008.10a
• /
• pp.76-94
• /
• 2008

This paper investigates performance of the Markowitz's portfolio selection model with applications to Korean stock market. We choose Samsung-Group-Funds and KOSPI index for performance comparison with the Markowitz's portfolio selection model. For the most recent one and a half year period between March 2007 and September 2008, KOSPI index almost remains the same with only 0.1% change, Samsung-Group-Funds shows 20.54% return, and Markowitz's model, which is composed of the same 17 Samsung group stocks, reaches 52% return. We perform sensitivity analysis on the duration of financial data and the period of portfolio change in order to maximize the return of portfolio. In conclusion, according to our empirical research results with Samsung-Group-Funds, investment by Markowitz's model, which periodically changes portfolio by using nonlinear programming with only financial data, outperforms investment by the fund manager who possesses rich experiences on stock trading and actively changes portfolio based on minute-by-minute market news and business information.

• Journal of Convergence for Information Technology
• /
• v.11 no.2
• /
• pp.82-89
• /
• 2021

The objective of this study is to propose a new Glide Path that dynamically adjusts the risky asset inclusion ratio of the Target Date Fund by simultaneously considering the market's forecast volatility as well as the time of investor retirement, and to compare the investment performance with the traditional Target Date Fund. Forecasts of market volatility utilize historical volatility, time series model GARCH volatility, and the volatility index VKOSPI. The investment performance of the new dynamic Glide Path, which considers stock market volatility has been shown to be excellent during the analysis period from 2003 to 2020. In all three volatility prediction models, Sharpe Ratio, an investment performance indicator, is improved with higher returns and lower risks than traditional static Glide Path, which considers only retirement date. The empirical results of this study present the potential for the utilization of the suggested Glide Path in the Target Date Fund management industry as well as retirees.

• Journal of Intelligence and Information Systems
• /
• v.23 no.4
• /
• pp.127-146
• /
• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.

• Industry Promotion Research
• /
• v.6 no.4
• /
• pp.69-81
• /
• 2021

Pakistan is a South Asian auspicious developing country. Based on the corruption perception index report 2020 by transparency international, Pakistan has ranked 124 with total scores of 31 globally and 188 ranks with a score of -2.25 in terms of political stability ranging from 0 (lowest) to 100 (highest). More crucially, the inflow of foreign direct investment toward Pakistan has declined between 2008 and 2019. Though political instability and government corruption have both positive and negative linear relationships with foreign direct investment, we tested the moderating impact of government corruption between political instability and inward foreign direct investment over time. We also tested the relationship between political instability and inward foreign direct investment in different phases of political regimes in the same country. Our results suggested that authoritarian regimes attracted more inward foreign direct investment than that during democratic periods of government. Furthermore, we found that there was low inward foreign direct investment when government corruption was high in the country. However, government corruption weakened the positive relationship between political instability and inward foreign direct investment (FDI).

• Journal of the Korea Society of Computer and Information
• /
• v.13 no.4
• /
• pp.231-240
• /
• 2008

In respect complication, group and period, the foreign direct investment of korea is composed of various factors. This paper studies focus on estimating the determinants of foreign direct investment of korea. The region of analysis consist of 7 groups, that is, Asia, Europe, Central and South America, Oceania, Africa, Middle East. Analyzing period be formed over a 67 point(2002. 6${\sim}$2007. 12). In this paper dependent variable setting up an amount of foreign direct investment, explanatory(independent) variables composed of gross domestic product, a balance of current accounts, the foreign exchange rate, employment to population ratio, an average of the rate of operation(the manufacturing industry), consumer price index, the amount of export, wages(a service industry). For an actual proof analysis, LIMDEP 8.0 software, analysis model is random effect in TWECR The result of estimating the determinants of foreign direct investment of korea provides empirical evidences of significance positive relationships between employment to population ratio and wages(a service industry). However this study provides empirical evidences of significance negative relationships between the foreign exchange rate, censurer price index and the amount of export. The explanatory variables, that is, an average of the rate of operation(the manufacturing industry), gross domestic product and a balance of current accounts, are non-significance variables.

• Proceedings of the Safety Management and Science Conference
• /
• 2002.11a
• /
• pp.321-339
• /
• 2002

The result of variance decomposition through yield of Treasury of 30 year maturity of USA, S&P 500 index, stock price of KEPCO has 76.12% of impulse of KEPCO stock price at short-term horizon, but they have 51.40% at long-term horizon. After one year, they occupy 13.65%, and 33.25%. So their effects are increased. By the way, S&P 500 index and yield of Treasury of 30 year maturity of USA have relatively more effect for forecast of stock price oi KEPCO at short-term & long-term. The yield of Treasury of 30 year maturity of USA more than S&P 500 index have more effect for stock price of KEPCO. It is why. That foreign investors through fall of stock price of USA invest for emerging market is less than movement for emerging market of hedge funds through effect of fall of yield of Treasury of 30 year maturity of USA, according to relative effects for stock price of Korea companies. The result of variance decomposition through won/dollar foreign exchange rate, yield of corporate bond of 3 year maturity, Korea Stock Price index(KOSPI), stock price of KEPCO has 81.33% of impulse of KEPCO stock price at short-term horizon, but they have 41.73% at long-term horizon. After one year, they occupy 23.57% and 34.70%. So their effects are increased. By the way, KOSPI and won/dollar foreign exchange rate have relatively more effect for forecast of stock price of KEPCO at short-term & long-term. The won/dollar foreign exchange rate more than KOSPI have more effect for stock price of KEPCO. It is why. The recovery of economic condition through improvement of company revenue causes of rising of KOSPI. But, if persistence of low interest rate continues, fall of won/dollar foreign exchange rate will be more aggravated. And it will give positive effect for stock price of KEPCO. This gives more positive effect at two main reason. Firstly, through fall of won/dollar foreign exchange rate and rising of credit rating of Korea will be followed. Therefore, foreign investors will invest more funds to Korea. Secondly, inflow of foreign investment funds through profit of won/dollar foreign exchange rate and stock investment will be occurred. If appreciation of won against dollar is forecasted, foreign investors will buy won. Through this won, investors will do investment. Won/dollar foreign exchange rate is affected through external factors of yen/dollar foreign exchange rate, etc. Therefore, the exclusion of instable factors for foreign investors through rising of credit rating of Korea is necessary things.

• Journal of Digital Convergence
• /
• v.16 no.5
• /
• pp.185-197
• /
• 2018

The purpose of this study is to analyze the Korean ETF market, which is experiencing a rapid increase in the number of stocks, to identify the degree of investment efficiency and to present investment directions. The methodology and procedure are ETF yield, change trends, correlation and regression analysis of the ETFs traded between 2010 and 2018. As a result, the total return of domestic ETFs was 3.51%, which was lower than the KOSPI growth rate and the return on equity ETFs was 4.03%, which was low. Leverage ETF yields were below 3%, which was low. The return on bond and currency ETFs was less than 1%. The most profitable ETFs were index ETFs, followed by domestic and leveraged ETFs. This study has contributed to establishing considerations when purchasing ETFs from the viewpoint of investors. Future research will present the direction of ETF investment more precisely.

• The Korean Journal of Applied Statistics
• /
• v.23 no.5
• /
• pp.783-797
• /
• 2010

Based on the importance of asset allocation in the return of an investment portfolio, this article attempts to verify the appropriateness of mutual funds as means of investment to obtain optimal asset allocation. The return-based style analysis is applied to determine a mutual fund's allocation(or a style) among a set of specified asset classes. Assuming a particular investor who defines a range allowed a fund's style to differ from its original one, it is examined whether or not the fund style is continued over an investment time horizon. After verifying the fact that the original style of the investment fails to remain unchanged from the empirical analysis limited to domestic equity mutual funds, we further investigated the reasons for the style drift. Despite several limitations of the analysis, it yields the conclusion that domestic equity mutual funds do not seem to be an appropriate investment tool to achieve a target asset allocation.