• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.311-324
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• 2021

Investors have increasingly become interested in macroeconomic antecedents in order to better understand the investment environment and estimate the scope of profitable investment in equity markets. This study endeavors to examine the interdependency between the macroeconomic antecedents (international oil price (COP), Domestic gold price (GP), Rupee-dollar exchange rates (ER), Real interest rates (RIR), consumer price indices (CPI)), and the BSE Sensex and Nifty 50 index return. The data is converted into a natural logarithm for keeping it normal as well as for reducing the problem of heteroscedasticity. Monthly time series data from January 1992 to July 2019 is extracted from the Reserve Bank of India database with the application of financial Econometrics. Breusch-Godfrey serial correlation LM test for removal of autocorrelation, Breusch-Pagan-Godfrey test for removal of heteroscedasticity, Cointegration test and VECM test for testing cointegration between macroeconomic factors and market returns,] are employed to fit regression model. The Indian market returns are stable and positive but show intense volatility. When the series is stationary after the first difference, heteroskedasticity and serial correlation are not present. Different forecast accuracy measures point out macroeconomics can forecast future market returns of the Indian stock market. The step-by-step econometric tests show the long-run affiliation among macroeconomic antecedents.

• SUVANNABHUMI
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• v.13 no.2
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• pp.7-35
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• 2021

This research is an attempt to understand the economic and social consequences that are occurring in Indonesia due to the spread of COVID-19. Indonesia, which has maintained solid economic growth since the inauguration of President Jokowi's government, is also experiencing difficulties to deal with unexpected COVID-19 pandemic as the global economic turmoil has had a very significant impact on its economy. The economic impact of COVID-19 can be felt, starting from the phenomenon of panic buying, the free fall of the stock price index, the depreciation of the Rupiah against the Dollar, sluggish activities in the processing industry, and ultimately it has an impact on slowing economic growth. Various policies and measures have been taken by the Indonesian government to minimize the negative impact caused by the COVID-19 pandemic on the economy. One such area is electronic commerce business or e-commerce that witnessed a vast increase of online and non-cash transaction amid rising voices that the country needs to prepare for the advent of a new economic system, the so-called New Normal era. The Covid-19 pandemic will temporarily slow economic growth and delay some development projects and policy initiatives as the Indonesian government diverts capital from infrastructure development to help respond to the crisis. However, the Jokowi administration's efforts for continuous reform are expected to accelerate the transition to the digital economy.

• Economic Analysis
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• v.25 no.3
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• pp.70-99
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• 2019

Using a stochastic volatility-in-mean VAR model consisting of the KOSPI index, the foreign exchange rate, the government bond rate, and the credit spread, this study investigates the effects of financial market uncertainty on financial markets. We find that higher uncertainty has recessionary effects on financial markets. The effects are especially stronger in equity markets and in won-dollar exchange markets. We also find that the effects of uncertainty become stronger during times of financial market stress compared to normal times. Finally, the results imply that financial market uncertainty may potentially affect the real sector, too.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.2
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• pp.1-17
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• 2015

In this paper, we propose a portfolio selection model utilizing a Markov chain for investing in the foreign exchange market based on market forecasts and exchange rate movement predictions. The proposed model is utilized to compute optimum investment portfolio weights for investing in margin-based markets such as the FX margin market. We further present an objective investment algorithm for applying the proposed model in real-life investments. Empirical performance of the proposed model and investment algorithm is evaluated by conducting an experiment in the FX market consisting of the 7 most traded currency pairs, for a period of 9 years, from the beginning of 2005 to the end of 2013. We compare performance with 1) the Dollar Index, 2) a 1/N Portfolio that invests the equal amount in the N target assets, and 3) the Barclay BTOP FX Index. Performance is compared in terms of cumulated returns and Sharpe ratios. The results suggest that the proposed model outperforms all benchmarks during the period of our experiment, for both performance measures. Even when compared in terms of pre- and post-financial crisis, the proposed model outperformed all other benchmarks, showing that the model based on objective data and mathematical optimization achieves superior performance empirically.

• Journal of Preventive Medicine and Public Health
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• v.55 no.4
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• pp.379-388
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• 2022

Objectives: Throughout history, societies have been impacted by inequality. Many studies have been conducted on the topic more broadly, but only a few have investigated inequalities in out-of-pocket health payments (OHP). This study measures OHP inequality trends among the Iranian households. Methods: This study used data from the Iranian Statistics Center on Iranian household income and expenditures. The analysis included a total of 995 300 households during the 36 years from 1984 to 2019. The Gini coefficient, Atkinson index, and Theil index were calculated for Iranian OHP. Results: Average Iranian household OHP increased from 33 US dollar (USD) in 1984 to 47 USD in 2019. During this 36-year span, the average±standard deviation Gini coefficient for OHP was 0.73±0.04, and the Atkinson and Theil indexes were 0.68±0.05 and 1.14±0.29, respectively. The Gini coefficients for the subcategories of OHP of outpatient diagnostic services, medical assistant accessories, hospital inpatient services, and addiction cessation were 0.70, 0.61, 0.84, and 0.64, respectively. Conclusions: In this study, we scrutinized trends of inequality in the OHP of Iranian households. Inequality in OHP decreased slightly over the past four decades. An analysis of trends among different subgroups revealed that affluent households, such as households with insurance coverage and households in higher income deciles, experienced higher inequality. Therefore, lower inequality in health care expenditures may be related to restricted access to health care services in Iran.

• Asian Journal of Turfgrass Science
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• v.25 no.2
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• pp.147-152
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• 2011

This study was conducted to evaluate the growth characteristics of creeping bentgrass cultivars for fairway of golf course at Yeoju area in Korea. At germination and coverage rate of creeping bentgrass, 'Shark' and 'CY-2' were excellent, 'L-93', 'Alpha', 'T-1 was in order', respectively. Visual qualities of 'Shark' and 'CY-2' also were excellent. Especially, 'Shark', 'T-1', and 'CY-2' showed excellent visual quality in summer days, the critical times for the bentgrass fairway quality. 'Shark', 'CY-2' and 'T-1' were excellent in Chlorophyll contents throughout the evaluation period. Chlorophyll content of 'T-1' was maintained very high in summer. 'CY-2' and 'Shark' showed the best root growth at the beginning of the study and contained longer and hairy roots. Which might make these two cultivars' water absorption easier than other's. NDVI (normalized difference vegetation index)of 'Shark', 'L-93' and 'CY-2' was excellent, respectively. 'T-1' showed the highest density and 'Shark', 'CY-2', 'Alpha', 'L-93' was followed by. The density of 'T-1' was rather increased in summer season, while those of other cultivars were decreased. Three diseases such as anthracnose, brown patch, and dollar spot, were appeared during the evaluation period. 'T-1' and 'L-93' were very sensitive to anthracnose which occurred at the beginning days of the study. The most susceptible cultivars to brown patch were 'Alpha' and 'L-93'. 'T-1' was the least resistant to dollar spot which occurred at the same time with brown patch.

• International Area Studies Review
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• v.20 no.2
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• pp.3-23
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• 2016

In this study, we used actual proof analysis, based on SVAR model according to economy theory, to observe the impact of actual and financial market of Korea, Japan, and China that have adopted quantitative easing export based strategy of growth, an unconventional monetary policy of the U.S. As a result of estimation, it appears that real effective exchange rate rise shock of Korea, Japan, and China against U.S. dollar has a negative influence on current account and index of industrial product, which are real economy. It can be implied that the result is driven from the fact that strong home currency of Korea, Japan, and China decreases price competitiveness of exports, causing negative influence on real economy. The real effective exchange rate shock against U.S. dollar appeared to decrease national bond rate of Korea and Japan, while increasing that of China. In instances of Korea and Japan, it is implied that national bond rate decreases as foreigner investment funds flow in, considering foreign-exchange profit through advanced financial market with high opening extent. On the other hand, because there are strong regulation on opening extent of Chinese financial markets, the influence seems to be greater for domestic policy, rather than a foreign influence. Lastly, Korea showed a more dramatic variable reaction to exchange rate shock compared to Japan or China. It is implied from the result that Korea is relatively more susceptible and fragile in regards of international status of economic size and currency.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.195-220
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• 2018

In this study, we conducted an empirical analysis of the factors that affect the change of Bitcoin Closing Price. Previous studies have focused on the security of the block chain system, the economic ripple effects caused by the cryptocurrency, legal implications and the acceptance to consumer about cryptocurrency. In various area, cryptocurrency was studied and many researcher and people including government, regardless of country, try to utilize cryptocurrency and applicate to its technology. Despite of rapid and dramatic change of cryptocurrencies' price and growth of its effects, empirical study of the factors affecting the price change of cryptocurrency was lack. There were only a few limited studies, business reports and short working paper. Therefore, it is necessary to determine what factors effect on the change of closing Bitcoin price. For analysis, hypotheses were constructed from three dimensions of consumer, industry, and macroeconomics for analysis, and time series data were collected for variables of each dimension. Consumer variables consist of search traffic of Bitcoin, search traffic of bitcoin ban, search traffic of ransomware and search traffic of war. Industry variables were composed GPU vendors' stock price and memory vendors' stock price. Macro-economy variables were contemplated such as U.S. dollar index futures, FOMC policy interest rates, WTI crude oil price. Using above variables, we did times series regression analysis to find relationship between those variables and change of Bitcoin Closing Price. Before the regression analysis to confirm the relationship between change of Bitcoin Closing Price and the other variables, we performed the Unit-root test to verifying the stationary of time series data to avoid spurious regression. Then, using a stationary data, we did the regression analysis. As a result of the analysis, we found that the change of Bitcoin Closing Price has negative effects with search traffic of 'Bitcoin Ban' and US dollar index futures, while change of GPU vendors' stock price and change of WTI crude oil price showed positive effects. In case of 'Bitcoin Ban', it is directly determining the maintenance or abolition of Bitcoin trade, that's why consumer reacted sensitively and effected on change of Bitcoin Closing Price. GPU is raw material of Bitcoin mining. Generally, increasing of companies' stock price means the growth of the sales of those companies' products and services. GPU's demands increases are indirectly reflected to the GPU vendors' stock price. Making an interpretation, a rise in prices of GPU has put a crimp on the mining of Bitcoin. Consequently, GPU vendors' stock price effects on change of Bitcoin Closing Price. And we confirmed U.S. dollar index futures moved in the opposite direction with change of Bitcoin Closing Price. It moved like Gold. Gold was considered as a safe asset to consumers and it means consumer think that Bitcoin is a safe asset. On the other hand, WTI oil price went Bitcoin Closing Price's way. It implies that Bitcoin are regarded to investment asset like raw materials market's product. The variables that were not significant in the analysis were search traffic of bitcoin, search traffic of ransomware, search traffic of war, memory vendor's stock price, FOMC policy interest rates. In search traffic of bitcoin, we judged that interest in Bitcoin did not lead to purchase of Bitcoin. It means search traffic of Bitcoin didn't reflect all of Bitcoin's demand. So, it implies there are some factors that regulate and mediate the Bitcoin purchase. In search traffic of ransomware, it is hard to say concern of ransomware determined the whole Bitcoin demand. Because only a few people damaged by ransomware and the percentage of hackers requiring Bitcoins was low. Also, its information security problem is events not continuous issues. Search traffic of war was not significant. Like stock market, generally it has negative in relation to war, but exceptional case like Gulf war, it moves stakeholders' profits and environment. We think that this is the same case. In memory vendor stock price, this is because memory vendors' flagship products were not VRAM which is essential for Bitcoin supply. In FOMC policy interest rates, when the interest rate is low, the surplus capital is invested in securities such as stocks. But Bitcoin' price fluctuation was large so it is not recognized as an attractive commodity to the consumers. In addition, unlike the stock market, Bitcoin doesn't have any safety policy such as Circuit breakers and Sidecar. Through this study, we verified what factors effect on change of Bitcoin Closing Price, and interpreted why such change happened. In addition, establishing the characteristics of Bitcoin as a safe asset and investment asset, we provide a guide how consumer, financial institution and government organization approach to the cryptocurrency. Moreover, corroborating the factors affecting change of Bitcoin Closing Price, researcher will get some clue and qualification which factors have to be considered in hereafter cryptocurrency study.

• Journal of Navigation and Port Research
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• v.38 no.6
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• pp.701-708
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• 2014

This study is aimed to obtain the influence of port hinterlands on container cargo volumes of Incheon port using System Dynamics(SD). Also, macro economic index such as exchange rates(US dollar), balance of current account, capital balance, Japan trade, China trade, export unit value index, import unit value index, total turnover of Incheon port were used as the factors that influence container cargo volumes of Incheon port. Moreover micro index regarding port hinterlands' operating companies such as total sales, rental fee, number of employees were introduced in the simulation model. In order to measure accuracy of the simulation, this study implemented MAPE analysis. And after the implementation, the simulation was decided as a much more accurate model because MAPE value was calculated to be within 10%. This study respectively examined factors using the sensitivity analysis. As a result, in terms of the effects on cargo volume in Incheon Port, the factor named 'cargo volumes of port hinterlands' operating companies' is most significant. And increasing the rental fee of hinterland was resulted in decreasing the cargo volumes of Incheon port.

• The Korean Journal of Applied Statistics
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• v.29 no.1
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• pp.85-98
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• 2016

This study makes an empirical comparison of various realized volatilities (RVs) in terms of overnight returns. In financial asset markets, during overnight or holidays, no or few trading data are available causing a difficulty in computing RVs for a whole span of a day. A review will be made on several RVs reflecting overnight return variations. The comparison is made for forecast accuracies of several RVs for some financial assets: the US S&P500 index, the US NASDAQ index, the KOSPI (Korean Stock Price Index), and the foreign exchange rate of the Korea won relative to the US dollar. The RV of a day is compared with the square of the next day log-return, which is a proxy for the integrated volatility of the day. The comparison is made by investigating the Mean Absolute Error (MAE) and the Root Mean Square Error (RMSE). Statistical inference of MAE and RMSE is made by applying the model confidence set (MCS) approach and the Diebold-Mariano test. For the three index data, a specific RV emerges as the best one, which addresses overnight return variations by inflating daytime RV.