Forecasting Implied Volatilities for Options on Index Futures: Time-Series and Cross-Sectional Analysis versus Constant Elasticity of Variance (CEV) Model

2016 ◽  
pp. 355-387
Author(s):  
Tzu Tai ◽  
Cheng Few Lee
Keyword(s):  
Time Series ◽  
Cev Model ◽  
Cross Sectional ◽  
Constant Elasticity ◽  
Constant Elasticity Of Variance ◽  
Index Futures ◽  
Cross Sectional Analysis ◽  
Sectional Analysis

The influence of welfare state factors on nursing professionalization and nursing human resources: A time‐series cross‐sectional analysis, 2000–2015

2019 ◽  
Vol 75 (11) ◽  
pp. 2797-2810 ◽  
Author(s):  
Virginia Gunn ◽  
Carles Muntaner ◽  
Edwin Ng ◽  
Michael Villeneuve ◽  
Montserrat Gea‐Sanchez ◽  
...  
Keyword(s):  
Time Series ◽  
Human Resources ◽  
Welfare State ◽  
Cross Sectional ◽  
Cross Sectional Analysis ◽  
Sectional Analysis

scholarly journals International Migration and Turnout Bias

2019 ◽  
Vol 53 (1) ◽  
pp. 33-38
Author(s):  
Michael J. Wigginton ◽  
Daniel Stockemer ◽  
Jasmine van Schouwen
Keyword(s):  
Time Series ◽  
International Migration ◽  
Potential Bias ◽  
Cross Sectional ◽  
Cross Sectional Analysis ◽  
Percentage Points ◽  
Voting Age ◽  
Migration Flows ◽  
Registered Voters ◽  
Sectional Analysis

ABSTRACTThis article focuses on two commonly used indicators of turnout, VAP turnout (the number of votes cast as a percentage of the voting-age population) and RV turnout (votes cast as a percentage of the number of registered voters), and discusses possible biases induced by migration flows. Using a global dataset on elections in more than 100 democracies between 1990 and 2012, we tested the potential bias induced by the percentage of resident noncitizens and nationals living abroad on VAP and RV turnout, respectively. Through time-series cross-sectional analysis, we found that the number of resident noncitizens negatively biases VAP turnout, to the extent that a country with 10% noncitizen residents would have turnout underreported by nearly 4 percentage points. In contrast, we found that the number of nationals living abroad does not induce a turnout bias.

Performance of China’s advertising agencies: a time series cross-sectional analysis

2018 ◽  
Vol 24 (5) ◽  
pp. 656-674
Author(s):  
Guangchao Charles Feng ◽  
Yuting Zhang ◽  
Qiuyu Hu ◽  
Hong Cheng
Keyword(s):  
Time Series ◽  
Advertising Agencies ◽  
Cross Sectional ◽  
Cross Sectional Analysis ◽  
Sectional Analysis

scholarly journals How strong is the epidemiological evidence to support any potential protective role for vitamin D levels on COVID-19 infections and mortality? - A time-series analysis of European Populations

2020 ◽  
Author(s):  
Samer Singh
Keyword(s):  
Vitamin D ◽  
Time Series ◽  
Serum Vitamin ◽  
Protective Role ◽  
Cross Sectional ◽  
Cross Sectional Analysis ◽  
Vitamin D Levels ◽  
Incidence And Mortality ◽  
Sectional Analysis

ABSTRACTA potential protective role of vitamin D serum levels on overall adverse outcomes of SARS-CoV-2 infection or COVID-19 on populations had been suggested previously based upon single-point cross-sectional analysis of 8 April 2020 data from 20 European countries assuming comparable underlying confounding variables for these populations, at an early stage of the current pandemic. Comparative time-series cross-sectional analysis of the COVID-19 data from 12 March (early pre-peak) to 26 July (late post-peak of infections) 2020 was performed to assess the strength of the assertion. The study subjects included 1,829,634 COVID-19 cases (11.11% of total worldwide) and 179,135 associated deaths (27.45 % of total worldwide) on 26 July 2012. Previously suggested cross-sectional study design and methodology could not consistently and significantly (p-value≥0.05) support the notion of the potential protective role of the mean serum vitamin D levels of the populations on COVID-19 incidence and mortality. However, the exponential correlative model, as well as alternative simple regression analysis on ln and Log10 transformed COVID-19 data for the time period indicated improved consistently negative covariation with vitamin D levels. Additionally, the later methodology increased the predictive potential for explaining the variability in data [R2 by 1.27-1.96 fold, adjusted-R2 by 1.33-2.47, p-value=0.0457-0.0035, for cases/million; R2 by 1.81-2.67, adjusted-R2 by 2.21-3.74 fold for deaths/million, p-value=0.0049-0.0228). Considering, the established role of vitamin D in immune system functioning randomized well-controlled trials may be suggested to evaluate/assess the potential protective role of vitamin D in reducing the COVID-19 impact on populations.

Sign in / Sign up

Export Citation Format

Share Document