Uncertainty index and stock volatility prediction:evidence from international markets

This study investigates the predictability of a fixed uncertainty index(UI)for realized variances(volatility)in the international stock markets from a high-frequency perspective.We construct a composite UI based on the scaled principal component analysis(s-PCA)method and demonstrate that it exhibits significant in-and out-of-sample predictabilities for realized variances in global stock markets.This predictive power is more powerful than those of two commonly employed competing methods,namely,PCA and the partial least squares(PLS)methods.The result is robust in several checks.Further,we explain that s-PCA outperforms other dimension-reduction methods since it can effectively increase the impacts of strong predictors and decrease those of weak factors.The implications of this research are significant for investors who allocate assets globally.

Uncertainties of snow cover extraction caused by the nature of topography and underlying surface

Manas River,the largest inland river to the north of the Tianshan Mountains,provides important water resources for human production and living.The seasonal snow cover and snowmelt play essential roles in the regulation of spring runoff in the Manas River Basin（MRB）.Snow cover is one of the most significant input parameters for obtaining accurate simulations and predictions of spring runoff.Therefore,it is especially important to extract snow-covered area correctly in the MRB.In this study,we qualitatively and quantitatively analyzed the uncertainties of snow cover extraction caused by the terrain factors and land cover types using TM and DEM data,along with the Per（the ratio of the difference between snow-covered area extracted by the Normalized Difference Snow Index（NDSI） method and visual interpretation method to the actual snow-covered area） and roughness.The results indicated that the difference of snow-covered area extracted by the two methods was primarily reflected in the snow boundary and shadowy areas.The value of Per varied significantly in different elevation zones.That is,the value generally presented a normal distribution with the increase of elevation.The peak value of Per occurred in the elevation zone of 3,700–4,200 m.Aspects caused the uncertainties of snow cover extraction with the order of sunny slope〉semi-shady and semi-sunny slope〉shady slope,due to the differences in solar radiation received by each aspect.Regarding the influences of various land cover types on snow cover extraction in the study area,bare rock was more influential on snow cover extraction than grassland.Moreover,shrub had the weakest impact on snow cover extraction.

How Does COVID-19 Affect Demographic,Administrative,and Social Economic Domain?Empirical Evidence from an Emerging Economy

Worldwide,the COVID-19 pandemic has had a significant impact on social and economic conditions as well as mental and physical health.Pakistan is considered in high ranks on Uncertainty Avoidance Index(UAI).The peo-ple of Pakistan have already faced numerous obstacles in terms of food and housing prospects.Job security,inflated prices of food items,andfinancial distress are the foremost vital challenges of Pakistan’s people during the Pandemic.This study examines the people’s perception of social,economic,and psychological impact and explores the causes and trends of spreading the COVID-19 pandemic in Pakistan.A primary survey method was conducted to collect the data from all Punjab divisions via questionnaire,and 471 respondents werefinally selected for data analysis.The data collection instrument was a questionnaire,and the data analysis tool was SPSS.Investors,analysts,business professionals,economists,business faculty staff,and civil society are the study’s popu-lations.Thefindings show that the overall social and economic life has been affected(82%of respondents agree)by the COVID-19 pandemic.60.5%of respondents manage their spending through salary(mean value=4.45),while 45%use savings(mean value=4.25).Moreover,Government support(mean value=3.95)plays a vital role in managing expenditure in this COVID-19 outbreak in Pakistan.Consequently,this study confirms that the lock-down implementation measure(mean value=2.20)is not considered useful in reducing COVID-19 due to Pakistan’sfinancial and economic uncertainty.This study concluded the social distance and testing measures are vital tools in reducing the COVID-19 pandemic in Pakistan.However,the study established that micro-smart lockdown,increased COVID-19 testing kits,and adequate medical equipment in the Hospital of Pakistan are the key mechanism to control the pandemic.Consequently,this study recommends that thorough long-term plan-ning be undertaken to mitigate the pandemic’s worst effects and develop a comprehensive strategy with society as the primary focus.

Changes in Lyrics of Tayu Lo and Bob Dylan under Hofstede's cultural dimensions theory

Bob Dylan,one of the most influential singers in the United State in 1960s,and Tayu Lo,the godfather of Chinese music hold different stance toward“changes”.By analyzing under Uncertainty Avoidance theory by Hofstede,the paper would dig deeper on the sources(on philosophy,political and economic background).

Classification and evaluation of uncertain influence factors for farm machinery service

Uncertainty extremely interferes with the execution of farm machinery operation.Treating uncertainties is especially important for machinery cooperatives providing social service since they face more uncertain influence factors(UIFs)than family farms.Under social service circumstance,uncertainties may arise from participants and environments.Classification and evaluation of UIFs were studied in this research.According to the production system,32 UIFs are defined and classified into six categories,which include supply,demand,interactivity,nature,society and others.Uncertainty composite index(UCI)is defined to evaluate the importance of UIFs,which is the square root of the product of occurrence frequency(OF)and impact degree(ID)calculated from the well-designed questionnaire responded by farm machinery operators.UCI is divided into five ranks based on normalization distribution test to illustrate the level of importance.Results from questionnaire showed that natural UIFs have an extreme impact on farm operation,UIFs of the demand and the supply have a serious influence on farm operation,UIFs of interactivity cannot be ignored,and social UIFs have a weak impact on farm operations.This study discovered the uncertainty problems under the specific circumstance of farm machinery service,which may provide a theoretical basis and potential methods for risk management of machinery cooperatives.