• Journal of Convergence for Information Technology
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• v.11 no.9
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• pp.84-93
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• 2021

The purpose of this study is to analyze whether the spread of COVID-19 infectious diseases acts as a fear to investors and affects the direction and volatility of stock returns. The investor fear index was proposed using the domestic confirmed patient information of COVID-19, and the influence on stock prices was empirically analyzed. The direction and volatility models of stock prices used the Granger causality and GARCH models, respectively. The results of empirical analysis using the KOSPI index from February 20, 2020 to June 30, 2021 are as follows: First, the COVID-19 fear index showed causality to future stock prices. Second, the COVID-19 fear index has a negative effect on the volatility of KOSPI index returns. In future studies, it is necessary to document the cause by using individual business performance and stock price instead of the stock index.

• International Area Studies Review
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• v.20 no.3
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• pp.123-144
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• 2016

This paper investigates the linkages between returns both in foreign exchange and stock markets, and uncertainties in two markets using daily data for the period of 16 July 2004 to 30 June 2014 in Nepalese economy. Four hypotheses are tested about how uncertainty influences the stock index and exchange rates. From the empirical results, a bivariate EGARCH-M model is the best to explain the volatility in the two markets. There is a negative relationship from the exchange rates return to stock price return. Empirical results do provide strong empirical confirmation that negative effect of stock index uncertainty and positive effect of exchange rates uncertainty on average stock index. GARCH-in-mean variables in AR modeling are significant and shows that there is positive effect of exchange rates uncertainty and negative effect of stock index uncertainty on average exchange rates. Stock index shocks have longer lived effects on uncertainty in the stock market than exchange rates shock have on uncertainly in the foreign exchange market. The effect of the last period's shock, volatility is more sensitive to its own lagged values.

• The Korean Journal of Applied Statistics
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• v.16 no.2
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• pp.217-224
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• 2003

The volatility in the financial data is usually measured by conditional variance. Two main streams for gauging conditional variance are stochastic volatility (SV) model and autoregressive type approach (GARCH). This article is conducting comparative study between SV and GARCH through the Korean Stock Prices Index (KOSPI) data. It is seen that SV model is slightly better than GARCH(1,1) in analyzing KOSPI data.

• KDI Journal of Economic Policy
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• v.44 no.4
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• pp.79-108
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• 2022

This study examines the impact of sentiment shock, which is defined as a stochastic innovation to the Housing Market Confidence Index (HMCI) that is orthogonal to past housing price changes, on aggregate housing price changes and housing price volatility. This paper documents empirical evidence that sentiment shock has a statistically significant relationship with Korea's aggregate housing price changes. Specifically, the key findings show that an increase in sentiment shock predicts a rise in the aggregate housing price and a drop in its volatility at the national level. For the Seoul Metropolitan Region (SMR), this study also suggests that sentiment shock is positively associated with one-month-ahead aggregate housing price changes, whereas an increase in sentiment volatility tends to increase housing price volatility as well. In addition, the out-of-sample forecasting exercises conducted here reveal that the prediction model endowed with sentiment shock and sentiment volatility outperforms other competing prediction models.

• The Korean Journal of Financial Management
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• v.15 no.1
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• pp.73-94
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• 1998

This paper contributes to the ongoing controversy over price and volatility spillovers across countries by providing new evidence with the futures data of the S&P 500 and Nikkei 225 index futures contacts from January 3, 1990 to April 16, 1996. Based on the two-stage symmetric and asymmetric GARCH models we document that both the U.S. and the Japanese daytime returns significantly influence the subsequent overnight returns of the other market. We find no signs of volatility spillovers between two international markets with the symmetric model. However, with the asymmetric models, we find that the magnitude of foreign negative shocks are different from the positive ones. The findings generally suggest that the two markets are more sensitive to the bad news originating in the other market. This nature of transmission between two markets would have important implications to the arbitragers who are trying to exploit the short-term dynamics of price and volatility movements across two security markets.

• Journal of Distribution Science
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• v.11 no.10
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• pp.73-79
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• 2013

Purpose - This study examines the impact of oil price volatility on economic activities in Korea. The new millennium has seen a deregulation in the crude oil market, which invited immense capital inflow into Korea. It has also raised oil price levels and volatility. Drawing on the recent theoretical literature that emphasizes the role of volatility, this paper attends to the asymmetric changes in economic growth in response to the oil price movement. This study further examines several key macroeconomic variables, such as interest rate, production, and inflation. We come to the conclusion that oil price volatility can, in some part, explain the structural changes. Research design, data, and methodology - We use two methodological frameworks in this study. First, in regards to the oil price uncertainty, we use an Exponential-GARCH (Exponential Generalized Autoregressive Conditional Heteroskedasticity: EGARCH) model estimate to elucidate the asymmetric effect of oil price shock on the conditional oil price volatility. Second, along with the estimation of the conditional volatility by the EGARCH model, we use the estimates in a VECM (Vector Error Correction Model). The study thus examines the dynamic impacts of oil price volatility on industrial production, price levels, and monetary policy responses. We also approximate the monetary policy function by the yield of monetary stabilization bond. The data collected for the study ranges from 1990: M1 to 2013: M7. In the VECM analysis section, the time span is split into two sub-periods; one from 1990 to 1999, and another from 2000 to 2013, due to the U.S. CFTC (Commodity Futures Trading Commission) deregulation on the crude oil futures that became effective in 2000. This paper intends to probe the relationship between oil price uncertainty and macroeconomic variables since the structural change in the oil market became effective. Results and Conclusions - The dynamic impulse response functions obtained from the VECM show a prolonged dampening effect of oil price volatility shock on the industrial production across all sub-periods. We also find that inflation measured by CPI rises by one standard deviation shock in response to oil price uncertainty, and lasts for the ensuing period. In addition, the impulse response functions allude that South Korea practices an expansionary monetary policy in response to oil price shocks, which stems from oil price uncertainty. Moreover, a comparison of the results of the dynamic impulse response functions from the two sub-periods suggests that the dynamic relationships have strengthened since 2000. Specifically, the results are most drastic in terms of industrial production; the impact of oil price volatility shocks has more than doubled from the year 2000 onwards. These results again indicate that the relationships between crude oil price uncertainty and Korean macroeconomic activities have been strengthened since the year2000, which resulted in a structural change in the crude oil market due to the deregulation of the crude oil futures.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.5
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• pp.19-27
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• 2022

The size of the government is one of the most fundamental debates of open economies. In any economy, government plays an important role, but a pertinent level of economic prosperity has never been obtained in history without government. Therefore, the objective of this paper investigates the association of government size, economic volatility, and institutional quality for 182 economies from the time period 1996-2016 is collected from the World Bank database. GE is defined as the General government's final consumption expenditure. Health expenditure is represented by HE. Government expenditure on education is denoted by EDUEXP. The economic volatility is measured by the rolling standard deviation of GDP per capita growth rate, Population growth, Trade openness, GINI represented Gini index which measures the degree to which the income distributed or consumption expenses among citizens deviates from a perfectly equal distribution. The results proposed that economic volatility has a significant effect on government size and institutional qualities. Moreover, the paper extends the investigation by finding the link between economic volatility with government health and education expenditure separately. The policy implication drawn from this analysis is that controlling economic volatility may reduce the size of government and also significantly affect health and education expenditures.

• The Korean Journal of Applied Statistics
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• v.36 no.6
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• pp.561-571
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• 2023

Volatility of a time series is defined as the conditional variance on the past information. In particular, for financial time series, volatility is regarded as a time-varying measure of risk for the financial series. To capture the intrinsic asymmetry in the risk of financial series, various asymmetric volatility processes including threshold-ARCH (TARCH, for short) have been proposed in the literature (see, for instance, Choi et al., 2012). This paper proposes a volatility function featuring non-zero origin in which the origin of the volatility is shifted from the zero and therefore the resulting volatility function is certainly asymmetric around zero and achieves the minimum at a non-zero (rather than zero) point. To validate the proposed volatility function, we analyze the Korea stock prices index (KOSPI) time series during the Covid-19 pandemic period for which origin shift to the left of the zero in volatility is shown to be apparent using the minimum AIC as well as via parametric bootstrap verification.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1999.06a
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• pp.359-365
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• 1999

We have evaluated the performance and some physical properties of 25 automotive engine oils (21 domestic and 5 imported products) which are purchased on the market to verify the API(American Petroleum Institute) or ILSAC(International Lubricant Standardization and Approval Committee) certification marks attached on the products and to determine the necessity of the quality control of the engine oils on the market. 12 test items are chosen according to API engine oil specification, which are flash point, pour point, cold cranking simulator apparent viscosity, pumping viscosity, gelation index, HTHS(High Temperature High Shear viscosity), foam, high temperature foam, filterability, volatility, high temperature deposit(TEOST), phosphorus content. We have found one product which did not meet the API specification on gelation index, one on HTHS, four on foam, and one on volatility, which implies that the quality control system is in need to check the fidelity of the certification marks attached on the engine oils being marketed. In addition, this works raises the necessity of the upgrade of the present Korean engine oil specification.

• Communications for Statistical Applications and Methods
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• v.17 no.2
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• pp.293-308
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• 2010

In this paper, we examine the forecasting KOSPI 200 realized volatility by volatility measurements. The empirical investigation for KOSPI 200 daily returns is done during the period from 3 January 2003 to 29 June 2007. Since Korea Exchange(KRX) will launch VKOSPI futures contract in 2010, forecasting VKOSPI can be an important issue. So we analyze which volatility measurements forecast VKOSPI better. To test this hypothesis, we use 5-minute interval returns to measure realized volatilities. Also, we propose a new methodology that reflects the synchronized bidding and simultaneously takes it account the difference between overnight volatility and intra-daily volatility. The t-test and F-test show that our new realized volatility is not only different from the realized volatility by a conventional method at less than 0.01% significance level, also more stable in summary statistics. We use the correlation analysis, regression analysis, cross validation test to investigate the forecast performance. The empirical result shows that the realized volatility we propose is better than other volatilities, including historical volatility, implied volatility, and convention realized volatility, for forecasting VKOSPI. Also, the regression analysis on the predictive abilities for realized volatility, which is measured by our new methodology and conventional one, shows that VKOSPI is an efficient estimator compared to historical volatility and CRR implied volatility.