• Korean Business Review
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• v.16
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• pp.43-60
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• 2003

There are several stylized facts concerning stock return volatility. First, it is persistent, so an increase in current volatility lasts for many periods. Second, stock volatility increases after stock prices fall. Third, stock volatility is related to macroeconomic volatility, recessions, and banking crises. On the other hand, there are many competing parametric models to represent conditional heteroskedasticity of stock returns. For this article, I adopt the strategy followed by French, Schwert, and Stambaugh(1987) and Schwert(l989, 1990). The models in this article provide a more structured analysis of the time-series properties of stock market volatility. Briefly, these models remove autoregressive and seasonal effects from daily returns to estimate unexpected returns. Then the absolute values of the unexpected returns are used in an autoregressive model to predict stock volatility.

• Journal of vocational education research
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• v.35 no.4
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• pp.89-107
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• 2016

The purpose of this study was to verify the causal relationship between self-directed learning ability and career maturity by Middle and High School Students in Seoul. This study used Seoul Education Longitudinal Study(SELS) data. Using autoregressive cross-lagged modeling, the results was followed. first, self-directed learning ability value was had a statistically significant positive effect in accordance with the time course from middle school 1st grade to high school 3rd grade. Second, career maturity also had a statistically significant positive effect in accordance with the time course from middle school 1st grade to high school 3rd grade. Third, previous self-directed learning ability had significant positive effect on the later career maturity, but the previous career maturity had no significant effect on later self-directed learning ability.

• The Mathematical Education
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• v.61 no.2
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• pp.359-373
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• 2022

This study aims to examine the differences in the longitudinal relationship between academic stress, mathematics self-efficacy, and engagement in mathematics class according to the math achievement level. According to the results, academic stress, math self-efficacy, and math class engagement were stable over time for the high and low groups. Also, In the high group, math self-efficacy had a negative longitudinal mediation effect in the influence of academic stress to math class engagement. Whereas, in the low group math class engagement had a positive longitudinal mediation effect in the influence of academic stress to math self-efficacy. This means that the academic stress affects differently according to the math achievement level, and mathematics teachers should reflect these results in their teaching/learning strategies so that students can increase their mathematics self-efficacy along with their engagement in mathematics classes.

• The Korean Journal of Applied Statistics
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• v.22 no.1
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• pp.17-28
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• 2009

This study attempts to perform the statistical test for the causality between the Korean and the U.S. business conditions in association with the lead-lag relationship between the domestic stock price and the business condition. Their causal relationships are clearly identified after the outbreak of the IMF financial crisis. The vector autoregression for the corresponding period appears to reflect the strong interrelationships between the market variables and the dependency of the domestic business conditions on the U.S. market. The estimation results validate the leading effect of the stock price and the U.S. business behavior.

• Journal of the Korean Data and Information Science Society
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• v.11 no.1
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• pp.1-18
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• 2000

In this paper, we study several parameter estimation methods used for autoregressive processes and compare them in view of forecasting. The least square estimation, least absolute deviation estimation, robust estimation are compared through Monte Carlo simulations.

• Communications for Statistical Applications and Methods
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• v.18 no.1
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• pp.13-21
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• 2011

This paper studies the analysis of multivariate nonstationary time series with seasonality. Three types of multivariate time series models are considered: seasonal cointegration model, nonseasonal cointegration model with seasonal dummies, and vector autoregressive model in seasonal differences that are compared for forecasting performances using Korean macro-economic time series data. The cointegration models produce smaller forecast errors in short horizons; however, when longer forecasting periods are considered the vector autoregressive model appears preferable.

• The Korean Journal of Applied Statistics
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• v.16 no.1
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• pp.141-150
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• 2003

This paper presents the multiple testing method of an autoregressive parameter in stationary AR(1) model using the usual Bayes factor. As prior distributions of parameters in each model, uniform prior and noninformative improper priors are assumed. Posterior probabilities through the usual Bayes factors are used for the model selection. Finally, to check whether these theoretical results are correct, simulated data and real data are analyzed.

• Proceedings of the Korea Water Resources Association Conference
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• 1993.07a
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• pp.409-415
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• 1993

• The Korean Journal of Applied Statistics
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• v.19 no.2
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• pp.305-317
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• 2006

Outliers adversely affect model identification, parameter estimation, and forecast in time series data. In particular, when outliers consist of a patch of additive outliers, the current outlier detection procedures suffer from the masking and swamping effects which make them inefficient. In this paper, we propose new outlier detection procedure based on high breakdown estimators, called as the dual robust filtering. Empirical and simulation studies in the autoregressive model with orders p show that the proposed procedure is effective.

• The Korean Journal of Financial Management
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• v.10 no.2
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• pp.239-262
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• 1993

본 연구에서는 한국 주식시장에서의 주가결정과정에 비합리적인 요소가 내포되어 있는지의 여부를 정가하기 위하여 Fama-French(1988)의 검증방법론을 이용하여 한국종합주가지수, 자본금규모별 주가지수, 산업 별 주가지수, 그리고 한경다우지수 등을 대상으로 실증분석을 실시하였다. 주가의 평균회귀과정(mean-reverting process)이 주식수익률들간의 음의 자기상관관계를 유발한다는 관찰에서 출발한 본 연구는 미국에서의 실증분석 결과와는 판이하게 주식수익률들이 2년까지의 수익률계산기간(return horizon)에서 지속적인 양의 자기 상관을 갖고 있음을 발견하였다. 본 연구에서 발견된 실증분식결과는 대상주가지수에 관계없이 일관성있는 패턴을 유지하고 있는데, 이는 Fama-French(1988)의 결과에 정면으로 배치된다. 따라서 본 연구에서의 실증분석 결과는 우리나라 주식시장의 경우 주가에 비합리적인 평균회귀요소(mean-reverting components)가 포함되어 있다는 가설을 지지하지 않는 것으로 해석 될 수 있을 것이다. 물론, 이것이 반드시 우리 주식 시장에서의 주가결정이 합리적으로 이루어진다는 것을 의미하지는 않으며, 단지 본 연구에서 주장되고 있는 것은 우리 주식시장에서의 주가결정과정을 랜덤웍과 평균회귀과정의 합성 혹은 평균회귀과정 그 자체로 모형화하려는 시도는 실증적 증거에 뿌리를 두고 있지 않다는