Exponentially Weighted Multivariate HAR Model with Applications in the Stock Market.

This paper considers a multivariate time series model for stock prices in the stock market. A multivariate heterogeneous autoregressive (HAR) model is adopted with exponentially decaying coefficients. This model is not only suitable for multivariate data with strong cross-correlation and long memory, but also represents a common structure of the joint data in terms of decay rates. Tests are proposed to identify the existence of the decay rates in the multivariate HAR model. The null limiting distributions are established as the standard Brownian bridge and are proven by means of a modified martingale central limit theorem. Simulation studies are conducted to assess the performance of tests and estimates. Empirical analysis with joint datasets of U.S. stock prices illustrates that the proposed model outperforms the conventional HAR models via OLSE and LASSO with respect to residual errors.

Assessing Age-Friendliness: Individualistic vs. Collectivistic Cultures.

A major task ahead for South Korea is to create age-friendly communities and environments that can support older residents' health, well-being, and quality of life. To that end, international partnerships have emerged to share information, assess need, and develop response strategies. In this study, the transferability of a US-developed age-friendly community resident survey, based on the WHO framework, was tested in two South Korean cities by comparing results to the same survey conducted in a US city. Descriptive, relational, and predictive analyses revealed the survey items were a better fit for the US city than the South Korean cities. Limited response variances collected in the Korean cities challenged the comparison of data between the Korean sites. Thus, a cultural lens was used to explain response patterns that reflect their understanding of social norms including avoiding disagreement and conflict in order to maintain social equilibrium and five cultural dimensions found in Western and Eastern societies (Individualism vs. collectivism, universalism vs. particularism, low vs. high power distance, low vs. high context, and inner vs, outer control). Recommendations for future assessments in South Korea include shifting focus away from the individual to the individual's social network and community to improve understanding of need.

Prediction intervals of the COVID-19 cases by HAR models with growth rates and vaccination rates in top eight affected countries: Bootstrap improvement.

This paper is devoted to modeling and predicting COVID-19 confirmed cases through a multiple linear regression. Especially, prediction intervals of the COVID-19 cases are extensively studied. Due to long-memory feature of the COVID-19 data, a heterogeneous autoregression (HAR) is adopted with Growth rates and Vaccination rates; it is called HAR-G-V model. Top eight affected countries are taken with their daily confirmed cases and vaccination rates. Model criteria results such as root mean square error (RMSE), mean absolute error (MAE), R 2 , AIC and BIC are reported in the HAR models with/without the two rates. The HAR-G-V model performs better than other HAR models. Out-of-sample forecasting by the HAR-G-V model is conducted. Forecast accuracy measures such as RMSE, MAE, mean absolute percentage error and root relative square error are computed. Furthermore, three types of prediction intervals are constructed by approximating residuals to normal and Laplace distributions, as well as by employing bootstrap procedure. Empirical coverage probability, average length and mean interval score are evaluated for the three prediction intervals. This work contributes three folds: a novel trial to combine both growth rates and vaccination rates in modeling COVID-19; construction and comparison of three types of prediction intervals; and an attempt to improve coverage probability and mean interval score of prediction intervals via bootstrap technique.

Modeling and forecasting the COVID-19 pandemic with heterogeneous autoregression approaches: South Korea.

This paper deals with time series analysis for COVID-19 in South Korea. We adopt heterogeneous autoregressive (HAR) time series models and discuss the statistical inference for various COVID-19 data. Seven data sets such as cumulative confirmed (CC) case, cumulative recovered (CR) case and cumulative death (CD) case as well as recovery rate, fatality rate and infection rates for 14 and 21 days are handled for the statistical analysis. In the HAR models, model selections of orders are conducted by evaluating root mean square error (RMSE) and mean absolute error (MAE) as well as R 2 , AIC, and BIC. As a result of estimation, we provide coefficients estimates, standard errors and 95% confidence intervals in the HAR models. Our results report that fitted values via the HAR models are not only well-matched with the real cumulative cases but also differenced values from the fitted HAR models are well-matched with real daily cases. Additionally, because the CC and the CD cases are strongly correlated, we use a bivariate HAR model for the two data sets. Out-of-sample forecastings are carried out with the COVID-19 data sets to obtain multi-step ahead predicted values and 95% prediction intervals. As for the forecasting performances, four accuracy measures such as RMSE, MAE, mean absolute percentage error (MAPE) and root relative square error (RRSE) are evaluated. Contributions of this work are three folds: First, it is shown that the HAR models fit well to cumulative numbers of the COVID-19 data along with good criterion results. Second, a variety of analysis are studied for the COVID-19 series: confirmed, recovered, death cases, as well as the related rates. Third, forecast accuracy measures are evaluated as small values of errors, and thus it is concluded that the HAR model provides a good prediction model for the COVID-19.

A cross-cultural comparison of hospice development in Japan, South Korea, and Taiwan.

By 2050, one out of four people in Eastern Asia will be aged 65 and above. Thus, preparing to care for an older population is imperative. Addressing quality care for elders includes consideration of palliative and end-of-life care. A comparative study of the development of hospice and palliative care services in Japan, South Korea, and Taiwan, is presented, based on an extensive literature review. Both commonalities and differences were found. This article provides information on the origins and administration of hospice services in these three cases, as well as the degree of government involvement. Cultural and religious aspects are also considered, and obstacles to the spread of hospice services are discussed. This review compares experiences with hospice services and identifies factors that influence people's perceptions and adoption of hospice. Stronger financial support for hospice and palliative care through the government and insurance programs would help increase the availability and use of services. Also, the need for continuing education of healthcare providers, patients, families, and the community is urgent. However, promotion of understanding of better pain management and the worth of hospice and palliative care must be conducted in ways that are sensitive to the cultural values and traditions in Japan, South Korea, and Taiwan. Only when hospice and palliative care can be viewed as an admirable choice for one's loved ones, overcoming issues of truth telling, filial piety, worries about how one is judged, and religious considerations, will it become more widely accepted.