• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.15-22
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• 2021

This study aims to obtain a stock investment strategy model based on the industrial sector in Indonesia Stock Exchange (IDX). This study uses IDX data for the period of January 1996 to December 2016. This study uses the Markov Regime Switching Model to identify trends in market conditions that occur in industrial sectors on IDX. Furthermore, by using the Logit Regression Model, we can see the influence of economic factors in determining trends in market conditions sectorally and the probability of trends in market conditions. This probability can be the basis for determining stock investment decisions in certain sectors. The results showed descriptively that the stocks of the consumer goods industry sector had the highest average return and the lowest standard deviation. The trend in sectoral stock market conditions that occur in IDX can be divided into two conditions, namely bullish condition (high returns and low volatility) and bearish condition (low returns and high volatility). Differences in the conditions are mainly due to differences in volatility. The use of a Logit Regression Model to produce probability of market conditions and to estimate the influence of economic factors in determining stock market conditions produces models that have varying predictive abilities.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.77-88
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• 2021

The stock markets in the BRICS (Brazil, Russia, India, China and South Africa) countries are the leading emerging markets globally. Therefore, it is pertinent to ascertain the critical drivers of stock market development in these economies. The currrent study empirically investigates to identify the linkages between stock market development, key macro-economic factors and institutional factors in the BRICS economies. The study covers the time period from 2000 to 2017. The dependent variable is the country's stock market development and the independent variables consist of six macroeconomic variables and five institutional variables. The study employs a panel cointegration test, Fully Modified OLS (FMOLS), a Pooled Mean Group (PMG) approach and a heterogeneous panel non-causality test.The findings of the study indicate co-integration among the selected variables across the BRICS stock markets. Long-run estimations reveal that five macroeconomic variables and four variables related to institutional quality are positive and statistically significant. Further, short-run causalities between stock market capitalization and selected variables are detected through the test of non-causality in a heterogeneous panel setting. The findings suggest that policymakers in the BRICS countries should enhance robust macroeconomic conditions to support their financial markets and should strengthen the institutional quality drivers to stimulate the pace of stock market development in their countries.

• KDI Journal of Economic Policy
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• v.35 no.4
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• pp.63-94
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• 2013

This study aims to understand the long-run movement of volatility in Korean stock market by decomposing stock volatility into the long-lived and the short-lived components. In addition, I analyze how the low-frequency movement of stock market volatility is related to changes in macroeconomic conditions. The volatility decomposition is made based on the GARCH-MIDAS model, in which the long-lived volatility is constructed based on the combination of realized volatilities (RVs). The results show that the long-lived volatility contains information of up to 3~4 years of past RVs. In addition, the changes in the long-lived volatility can explain about two thirds of volatility changes in the Korean stock market from 1994 to 2009. Meanwhile, the low-frequency movement in the market volatility can be related to changes in macroeconomic conditions. The analysis shows that the stock market volatility appears to be countercyclical while showing a positive correlation with the inflation. In addition, the stock market volatility tends to rise as macroeconomic uncertainty increases. These results imply that macroeconomic policies aiming at economic stabilization could contribute to reduction in the stock market volatility.

• Journal of the Korean Home Economics Association
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• v.49 no.8
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• pp.37-46
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• 2011

Using the 1987-2008 quarterly aggregated data of the Household Income and Expenditure Survey, this study investigated the factors influencing household saving rate. The independent variables in the AR regression model were the GDP growth rate, shares of the total household expenditure allocated to tax & social insurance, and education, the variables reflecting the conditions of the asset market including interest rate, stock market index, and real estate price index, and the variables representing the social economic conditions including the index of aging and income inequality. Among the independent variables interest rate, stock market index, and income inequality were found to be significantly associated with the household saving rate. These results suggested that the redistribution and financial market policies favorable to savers may be effective for raising the household saving rate.

• East Asian Economic Review
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• v.21 no.2
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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 Korean Journal of Applied Statistics
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• v.24 no.1
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• pp.103-114
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• 2011

Current series for testing stock market cointegrations tend to be restricted to analyzing the relations between stock market prices and may not be able to understand the whole picture of the variations in the stock market system. The nature of the variations in the stock prices, between the countries that experienced economic crisis and those did not, are different for a certain period of time, and accordingly excluding the potentially important variables in the stock market system causes statistical bias. This study considers domestic foreign exchange markets and financial markets in testing for the cointegrating relations of the stock prices in Korea and major investing countries. The results demonstrate the possibility of specification errors unless those markets are included in the statistical modeling process.

• Management & Information Systems Review
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• v.38 no.3
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• pp.1-19
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• 2019

This paper investigates the asymmetric effects of crude oil price uncertainty on industrial stock returns under different market conditions (bearish and bullish stock markets). We consider a quantile regression method using monthly oil volatility index, KOSPI and 22 industrial stock indices from May 2007 to February 2019. Especially, we take care of the positive and negative changes of the oil volatility index to analyze asymmetric effects of the oil price uncertainty for the bearish and bullish stock market conditions. During the bearish markets, the oil volatility index has relatively strong statistically significant negative effects on the industrial stock returns. These effects gradually decrease when the market conditions became more bullish markets. In particular, positive changes in the oil volatility index yields a further significant decrease in 12 industrial stock returns during the extreme bearish markets. Moreover, during the bullish markets, negative changes in the oil volatility index have statistically significant negative effects on the 12 industrial stock returns. From the empirical results, we see that participants of the Korean stock market are sensitive to bad news in a recession.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.1
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• pp.31-41
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• 2004

This study analyzes the structure of the variations In the domestic bank earnings and examines their dynamic features by estimating the short-run response and the long-run adjustment Process after the changes in financial market variables. A system of the equations for the bank stock price index and KOSPI is formulated to utilize the whole information in the market and simultaneously estimated to identify the relationships between the market variables and the bank earnings. Since the bank stock price is found to be responsive to changes in none of the market variables in the short run, while being relatively responsive to dollar exchange rate and business state, It implies that a good economic conditions and a stable foreign exchange rate should be maintained to Improve the level of the stock price In the long run. In addition, the dynamic structure of the responses of the bank stock price index and KOSPI to the initial changes in the market variable are compared and anlayzed. The response of the bank stock price appears to take much longer in adjusting to the long-run eouilibrium level than that of KOSPI. As a result, the cumulative response of the bank stock price index over time is found much bigger than that of HOSPI.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.683-692
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• 2020

The primary purpose of the study is to investigate the volatility spillovers from global economic policy uncertainty and macroeconomic factors to the Islamic stock market returns. The study focuses on the Islamic stock indices of emerging economies including Indonesia, Malaysia, and Turkey. The Macroeconomic factors are industrial production, consumer price index, exchange rate. EGARCH model is employed for investigation of volatility spillovers. The results show that the global economic policy uncertainty has a significant spillover effect only on the returns of Turkish Islamic stock index. Similarly, the shocks in macroeconomic factors have little influence on the volatility of Islamic indices returns. The volatility of Indonesian and the Turkish Islamic stock indices returns is not influenced from the fluctuations in macroeconomic factors. However, there is significant volatility spillover only from industrial production to the returns of Malaysian Islamic index. The results suggest that the Islamic stock markets are less likely to influence from the global economic policies and macroeconomic factors. The stability of Islamic stocks provide opportunity for diversification of portfolios, particularly in stressed market conditions. The major price factors of Islamic markets could be firms' specific factors or investors' behaviors. The findings are helpful for policy makers and investors in formulating policies and portfolios.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.7
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• pp.197-203
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• 2022

The agricultural sector has an important contribution to the economic development of Vietnam in particular and other countries in general. The growth of enterprises in the industry is an important bridge in promoting the economic development of the country. Currently, the policies of the Government of Vietnam always create favorable conditions for enterprises to conduct business, especially enterprises in the agricultural sector. The study aims to assess factors influencing the profitability of listed firms in Vietnam's stock market. Using 40 enterprises in the agricultural industry listed on the Ho Chi Minh City Stock Exchange and the Hanoi Stock Exchange and using advanced econometric modeling, dealing with defects in the regression model, the research results show that large-scale firm has higher economic efficiency than small-scale firm. In addition, a firm with higher use of loan capital is associated with a more efficient firm, reflected in the relatively good debt management ability of enterprises in the agricultural sector. Adversely, growth and age do not have any impact on firm performance. Macroeconomic factors do not impact profitability. Finally, the study has some policy implications for developing agricultural businesses in the case of Vietnam.