• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.349-356
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• 2021

This study comprehensively investigates whether there is an impact of risk, size, profitability, earnings per share, dividend yield, and book-to-market equity on the stock prices of Jordanian banks listed on the Amman Stock Exchange (ASE) for the period 2006-2018. To mitigate endogeneity concerns and to control for within-bank dynamics, panel data fixed effects estimations are used. This study shows that size (SIZE), profitability (ROA), dividend yield (DY) and book-to-market equity (BE/ME) ratios are statistically significant determinants of stock prices. The risk (RISK) factor measured by volatility of ROA has a positive and significant effect on the stock prices, while earnings per share has minimum influence on the stock prices. The results show that ROA has a significant and positive effect and provides the largest effect among all variables used in this study, while the RISK factor has a positive and significant effect. In contrast, SIZE, DY, and BE/ME have a significant negative effect on stock prices. The paper presented new evidence showing that ROA is a better determinant of stock prices in Jordanian banks, and RISK significantly affects stock prices. The researcher recommends using a factor of profitability represented by ROA which has a significant positive effect on the stock prices in Jordanian banks and applying the ROA variable to other sectors.

• Journal of the Korean Regional Science Association
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• v.15 no.3
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• pp.33-51
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• 1999

After the 1997 currency crisis, the real estate prices had been rapidly dropped and the deregulation in the Korean real estate merket has been performed. It is analyzed whether these transactions caused a structural change in real estate market, or not. The Pettitt test shows there exists a turing point in real estate prices in 1998. It is found that the degrees of co-movement between the change in real estate prices and real GDP growth rate are increased. Consequently, the factor, represented as real GDP growth rate, determining the market fundamental of real estate prices will effect on the behavioral pattern and the real estate prices in the long run. While the factors determining the portfolio selection behaviors, such as interest rate and stock prices, will cause short-term variations.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.131-138
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• 2020

In accordance with huge demand for capital to meet the expansion of steel production, there are more and more steel companies who have officially listed their stocks in HOSE and HNX. One of the key issues in successful initial public offerings and seasonal offerings for these companies is how to make stocks of steel companies become more attractive in the eyes of investors. The purpose of this research is to analyze the determinants of share prices of listed steel companies in Vietnam. This study utilized macro-economic variables, ratios and indicators representing characteristics of steel industry collected from Quarter 1/2006 to Quarter 4/2019 in association with the panel data and the feasible generalized least square (FGLS) model to evaluate the degree of these factors on the share prices. The results of the research show that ROE, Cons_rate, and CO2_rate are three main factors affecting the share prices of listed steel companies. Among which, ROE and Cons_rate have a positive effect, while CO2_rate has a negative effect on the share prices of listed steel companies. It also confirms the relationship between the environmental factor, construction industry factor and the stock prices. This lays foundations for recommendations for the future policies towards environmental protection and sustainable development.

• Journal of Distribution Science
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• v.13 no.11
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• pp.39-46
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• 2015

Purpose - In Korea, there has been a recent trend that shows housing prices have risen rapidly following the International Monetary Fund crisis. The rapid rise in housing prices is spreading recognition of this as a factor in housing price volatility. In addition, this raises the expectations of housing prices in the future. These expectations are based on the assumption that a relationship exists between the current housing prices and expected housing prices in the real estate industry. By performing an empirical analysis on the validity of the claim that an increase in current housing prices can be correlated with expected housing prices, this study examines whether a long-term equilibrium relationship exists between expected housing prices and existing housing prices. If such a relationship exists, the recovery of equilibrium from disequilibrium is analyzed to derive related implications. Research design, data, and methodology - The relationship between current housing prices and expected housing prices was analyzed empirically using the Vector Error Correction Model. This model was applied to the co-integration test, the long-term equilibrium equation among variables, and the causality test. The housing prices used in the analysis were based on the National Housing Price Trend Survey released by Kookmin Bank. Additionally, the Index of Industrial Product and the Consumer Price Index were also used and were obtained from the Bank of Korea ECOS. The monthly data analyzed were from January 1987 to May 2015. Results - First, a long-term equilibrium relationship was established as one co-integration between current housing price distribution and expected housing prices. Second, the sign of the long-term equilibrium relationship variable was consistent with the theoretical sign, with the elasticity of housing price distribution to expected housing price, the industrial production, and the consumer price volatility revealed as 1.600, 0.104,and 0.092, respectively. This implies that the long-term effect of expected housing price volatility on housing price distribution is more significant than that of the industrial production and consumer price volatility. Third, the sign of the coefficient of the error correction term coincided with the theoretical sign. The absolute value of the coefficient of the correction term in the industrial production equation was 0.006, significantly larger than the coefficients for the expected housing price and the consumer price equation. In case of divergence from the long-term equilibrium relationship, the state of equilibrium will be restored through changes in the interest rate. Fourth, housing-price volatility was found to be causal to expected housing price, and was shown to be bi-directionally causal to industrial production. Conclusions - Based on the finding of this study, it is required to relieve the association between current housing price distribution and expected housing price by using property taxes and the loan-to-value policy to stabilize the housing market. Further, the relationship between housing price distribution and expected housing price can be examined and tested using a sophisticated methodology and policy variables.

• International Area Studies Review
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• v.21 no.4
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• pp.3-17
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• 2017

The purpose of the paper is to suggest the empirical evidences for the effects of factor prices on the export performance in the Korean manufacturing industries during the period 1975:1-2016:4. The paper is to set up the error correction model derived from the autoregressive distributed lag scheme and to estimate the factor price elasticities of export in the 8 manufacturing industries. The real wage, interest and import price index elasticities of export all were estimated to be statistically significant at 1% level in the most industries with showing negative signs as expected. And the real wage elasticity proved to likely be smaller as the industries become more capital-intensive while the import price index elasticity tended to become larger in industries with larger ratio of imported intermediate goods to output. The empirical results suggest that the declines in input factor prices since the foreign exchange crisis in the end of 1997 have positive effects on the export performance in the Korean manufacturing industries.

• Journal of the Korean Data and Information Science Society
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• v.28 no.1
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• pp.67-74
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• 2017

This paper analyzes the causal relationship from climate to international grain prices. Although climate is an important factor affecting the grain markets, it has been restrictively considered in previous studies analyzing the causal relationship of international grain prices. In this paper, monthly data from May 1987 to 2013 is used for the causal analysis in which the sea surface temperature (SST), a representative global climate variable, and the international prices of wheat, corn, and soybean, the world's three major crops, are considered. The test method is the parametric version of the nonparametric test for causality in high-order moments suggested by Nishiyama et al. (2011). The results show that the climate causes in the first moment the prices of all the three grains and causes in the second moment the prices of corn and soybean, but does not cause in the third moment any of the three grain prices.

• New & Renewable Energy
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• v.6 no.3
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• pp.13-21
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• 2010

This paper analyzes the factors of renewable energy consumption in Korea, China and Japan. We consider renewable energy consumption per capita as dependent variable, GDP per capita, $CO_2$ emissions per capita and real oil prices as independent variables. To analyze this model, this paper uses three econometric methods such as OLS, fixed effect model and panel GLS, utilizing data from 1990 to 2006 in Korea, China and Japan. According to the results by OLS for each country, an increase in GDP per capita or $CO_2$ emissions per capita or oil prices leads to an increase in renewable energy consumption. According to the results by fixed effect model, an increase in GDP per capita or $CO_2$ emissions per capita leads to an increase in renewable energy consumption. And real oil prices do not have a significant impacts on this model. According to the results by panel GLS, an increase in real GDP per capita as a proxy of income leads to an increase renewable energy consumption. And both $CO_2$ emissions per capita and real oil prices do not correlated closely with renewable energy consumption. Thus oil is not substituted to renewable energy in Northeast asian countries.

• Journal of Distribution Science
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• v.17 no.11
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• pp.93-101
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• 2019

Purpose: Blockchain technology suggests ways to solve the problems in the existing industry. Among them, Cryptocurrency system, which is an element of Blockchain technology, is a very important factor for operating Blockchain. While Blockchain cryptocurrency has attracted attention, studies on cryptocurrency prices have been mainly conducted, however previous studies mainly conducted on Bitcoin prices. On the other hand, in the context of the creation and trading of various cryptocurrencies based on the Blockchain system, little research has been done on cryptocurrencies other than Bitcoin. Hence, this study attempts to find variables related to the prices of Dash, Litecoin, and Monero cryptocurrencies using machine learning techniques. We also attempt to find differences in the variables related to the prices for each cryptocurrencies and to examine machine learning techniques that can provide better performance. Research design, data, and methodology: This study performed Dash, Litecoin, and Monero price prediction analysis of cryptocurrency using Blockchain information and machine learning techniques. We employed number of transactions in Blockchain, amount of generated cryptocurrency, transaction fees, number of activity accounts in Blockchain, Block creation difficulty, block size, umber of created blocks as independent variables. This study tried to ensure the reliability of the analysis results through 10-fold cross validation. Blockchain information was hierarchically added for price prediction, and the analysis result was measured as RMSE and MAPE. Results: The analysis shows that the prices of Dash, Litecoin and Monero cryptocurrency are related to Blockchain information. Also, we found that different Blockchain information improves the analysis results for each cryptocurrency. In addition, this study found that the neural network machine learning technique provides better analysis results than support-vector machine in predicting cryptocurrency prices. Conclusion: This study concludes that the information of Blockchain should be considered for the prediction of the price of Dash, Litecoin, and Monero cryptocurrency. It also suggests that Blockchain information related to the price of cryptocurrency differs depending on the type of cryptocurrency. We suggest that future research on various types of cryptocurrencies is needed. The findings of this study can provide a theoretical basis for future cryptocurrency research in distribution management.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.179-185
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• 2016

This study verifies whether speculative trading in commodity markets acted as the primary cause of the increase in commodity prices after the global financial crisis using the Structural Vector Autoregressive (SVAR) model. The effects of speculative trading on commodity prices increased by a factor of 3 to 6 after the crisis compared to those before the crisis. Although the demand related variables, such as industrial production, affected commodity prices significantly before the crisis, their effects decreased after the crisis. Consequently, the rebound of commodity prices after the crisis was mainly caused by the increase in speculative money, fortified by the expansion of the global liquidity supply. The global liquidity may well increase in the future, because the U.S. Federal Reserve Board is likely to continue to increase its interest rate. This study claims that when global liquidity shrinks as a result of a change in the Fed's monetary policy stance, speculative trading will slow down, leading to a decline in commodity prices.

• Journal of Korea Trade
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• v.25 no.1
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• pp.34-46
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• 2021

Purpose - This paper aims to analyze the impact of the terms of trade, export price, and import price on the Korean economy (that is, real GDP, CPI, money market rate, and real effective exchange rate), and vice versa in the simple vector autoregression. Design/methodology - We impose two assumptions, i.e., diagonality and bloc exogeneity, to correctly identify the impact of a factor to the others in the structural equation. With two contemporaneous assumptions in the structural VAR, this paper investigates the impacts of the terms of trade on the Korean economy and vice versa. Findings - Impulse responses to the shocks in the terms of trade and Korean economy show that 1) an impact of the terms of trade on the economy is different in export prices and in import prices. A higher export price is beneficial to the economy while a higher import price hurts the economy, and 2) an increase in real effective exchange rate and in interest rate constrains domestic production and lowers consumer prices. Originality/value - Unlike the conventional perception that a depreciation of a currency would promote exports and domestic production at the price of inflation, our result shows the opposite, and 3) real GDP and consumer prices are positively correlated. That is, an increase in real GDP does not only cause inflation, but an increase in consumer prices also promote domestic production. Yet, the only difference is that export prices and import prices end up higher with an increase in real GDP, but lower with inflation.