The Cross-Sectional Analysis of Technical Trading Rules in the Korean Stock Market

2017 ◽  
Vol 19 (5) ◽  
pp. 2601-2610
Author(s):  
Ki Yool Ohk ◽  
Keyword(s):  
Stock Market ◽  
Technical Trading ◽  
Cross Sectional ◽  
Technical Trading Rules ◽  
Trading Rules ◽  
Cross Sectional Analysis ◽  
Korean Stock Market ◽  
The Cross ◽  
Sectional Analysis

An Examination of Audit Report Lag for Banks: A Panel Data Approach

2000 ◽  
Vol 19 (2) ◽  
pp. 159-174 ◽  
Author(s):  
B. Charlene Henderson ◽  
Steven E. Kaplan
Keyword(s):  
Data Analysis ◽  
Panel Data ◽  
Panel Data Analysis ◽  
Explanatory Power ◽  
Omitted Variables ◽  
Audit Report ◽  
Cross Sectional ◽  
Cross Sectional Analysis ◽  
The Cross ◽  
Sectional Analysis

This study investigates the determinants of audit report lag (ARL) for a sample of banks. Researchers have been interested in the determinants of ARL, in part, because it impacts the timeliness of public disclosures. However, prior ARL research has relied exclusively on regression analysis of cross-sectional samples of companies from many industries. In addition to focusing exclusively on banks, panel data analysis is introduced and compared with cross-sectional analysis to demonstrate its power in dynamic settings and its potential to improve estimation. Results reveal important differences between cross-sectional analysis and panel data analysis. First, bank size is negatively related to ARL in cross-section but positively related to ARL using panel data analysis. The cross-sectional size estimate is subject to omitted variables bias, and furthermore, cross-sectional analysis fails to capture variation in size over time in relation to ARL. Panel data analysis both accounts for omitted variables and captures the dynamics of the relationship between size and ARL. As well, the panel data model's explanatory power far exceeds that of the cross-sectional model. This is primarily due to the panel model's use of firm-specific intercepts that both capture the role of reporting tradition and eliminate heterogeneity bias. Thus, panel data analysis proves to be a powerful tool in the analysis of ARL.

Association between the FINDRISC score and the risk of metabolic syndrome and hepatic steatosis

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
D Godoi Bernardes Da Silva ◽  
R Dias Santos ◽  
M Sommer Bittencourt ◽  
J.A.M Carvalho ◽  
M Franken ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Hepatic Steatosis ◽  
Longitudinal Analysis ◽  
Metabolic Diseases ◽  
Low Cost ◽  
Cross Sectional ◽  
Predictive Values ◽  
Cross Sectional Analysis ◽  
The Cross ◽  
Sectional Analysis

Abstract Introduction The Finnish Diabetes Risk Score (FINDRISC) was developed in Europe to predict type 2 diabetes mellitus (T2DM) risk without need of laboratory tests. Small cross-sectional studies analyzed the association between RF with metabolic syndrome (MS) or hepatic steatosis (HS). Our objective was to test the association of FINDRISC with MS or HS, in a transversal and longitudinal way. Methods In 41,668 individuals (age 41.9±9.7 years; 30.8% women) who underwent health evaluation between 2008 and 2016 in a single centre in Brazil, we tested the transversal association between FINDRISC and MS or HS, in multivariate models. The same analyzes were performed longitudinally in non-diabetic subgroups, followed for 5±3 years, to test the predictive value of FINDRISC and the incidental risk of MS (n=10,075 individuals) or HS (n=7,097 individuals), using logistic regression. Models were adjusted for confounders such as sex, use of medications for dyslipidemia, smoking, and baseline plasma levels of glucose, creatinine and lipids. A receiver operating characteristic (ROC) curve was used to evaluate the discriminative and predictive values of FINDRISC for MS and HS. Results In the cross-sectional analysis, 2,252 (5%) individuals had MS and 14,176 (34%) HS. In the longitudinal analysis, there were 302 cases of incidental MS (2%) and 1,096 cases of HS (15%). FINDRISC was independently associated with MS and HS in the cross-sectional analysis (respectively, OR 1.27, 95% CI: 1.25–1.28, P<0.001; and OR 1.21, 95% CI: 1.20–1.22, P<0.001, per FINDRISC unit) and in longitudinal analysis (respectively, OR of 1.18, 95% CI: 1.15–1.21, P<0.001; and OR of 1.10, 95% CI: 1.08–1.11, P<0.001, per FINDRISC unit). In comparison with individuals with low FINDRISC, those with moderate, high and very high values showed significant and proportional increases of the 12 to 77 fold in the chance of current SM (P<0.001) and 3 to 10 fold in the chance of HS (P<0.001). During follow-up, these increases were 3 to 10 fold in the chance of incidental MS (P<0.001) and 1 to 3 fold in the chance of HS (P<0.001). The AUC from cross-sectional analysis for MS and HS were respectively 0.82 (95% CI 0.81–0.83) and 0.76 (95% CI 0.75–0.76), and in longitudinal analysis 0.73 (95% CI 0.70–0.76) and 0.63 (95% CI 0.61–0.65), respectively. Conclusion FINDRISC was associated with the presence and onset of MS and HS, but it predicted better metabolic syndrome risk than hepatic steatosis. Therefore, this simple, practical and low-cost score can be useful for population screening and identification of subgroups of individuals at higher risk future metabolic diseases. Funding Acknowledgement Type of funding source: None

scholarly journals Cross-Sectional Analysis of the Resistance of Rc Members Subjected to Bending With/without Axial Force

2021 ◽  
Author(s):  
Marek Lechman
Keyword(s):  
Cross Section ◽  
Axial Force ◽  
Rectangular Cross Section ◽  
Bending Moment ◽  
Equilibrium Equations ◽  
Cross Sectional ◽  
Cross Sectional Analysis ◽  
Nonlinear Stress ◽  
The Cross ◽  
Sectional Analysis

The paper presents section models for analysis of the resistance of RC members subjected to bending moment with or without axial force. To determine the section resistance the nonlinear stress-strain relationship for concrete in compression is assumed, taking into account the concrete softening. It adequately describes the behavior of RC members up to failure. For the reinforcing steel linear elastic-ideal plastic model is applied. For the ring cross-section subjected to bending with axial force the normalized resistances are derived in the analytical form by integrating the cross-sectional equilibrium equations. They are presented in the form of interaction diagrams and compared with the results obtained by testing conducted on RC columns under eccentric compression. Furthermore, the ultimate normalized bending moment has been derived for the rectangular cross-section subjected to bending without axial force. It was applied in the cross-sectional analysis of steel and concrete composite beams, named BH beams, consisting of the RC rectangular core placed inside a reversed TT welded profile. The comparisons made indicated good agreements between the proposed section models and experimental results.

Association between the Prime Diet Quality Score and depressive symptoms in a Mediterranean population with metabolic syndrome. Cross-sectional and 2-year follow-up assessment from PREDIMED-PLUS study

2021 ◽  
pp. 1-25
Author(s):  
Naomi Cano-Ibáñez ◽  
Lluis Serra-Majem ◽  
Sandra Martín-Peláez ◽  
Miguel Ángel Martínez-González ◽  
Jordi Salas-Salvadó ◽  
...  
Keyword(s):  
Depressive Symptoms ◽  
Diet Quality ◽  
Quality Score ◽  
High Quality ◽  
Cross Sectional ◽  
Cross Sectional Analysis ◽  
Prevalence Of Depression ◽  
The Cross ◽  
Sectional Analysis

Abstract The burden of depression is increasing worldwide, specifically in older adults. Unhealthy dietary patterns may partly explain this phenomenon. In the Spanish PREDIMED-Plus study we explored (1) the cross-sectional association between the adherence to the Prime Diet Quality Score- (PDQS), an a priori-defined high-quality food pattern and the prevalence of depressive symptoms at baseline (cross-sectional analysis), and (2) the prospective association of baseline PDQS with changes in depressive symptomatology after 2 years of follow-up. After exclusions, we assessed 6612 participants in the cross-sectional analysis and 5523 participants in the prospective analysis. An energy-adjusted high-quality dietary score (PDQS) was assessed using a validated food-frequency questionnaire (FFQ). The cross-sectional association between PDQS and the prevalence of depression, presence of depressive symptoms and prospectively assessed changes in depressive symptoms was evaluated through multivariable regression models (logistic and linear models and mixed linear-effects models). PDQS was inversely associated with depressive status in the cross-sectional analysis. Participants in the highest quintile of PDQS (Q5) showed a significantly reduced odds of depression prevalence as compared to participants in the lowest quartile of PDQS (Q1) [OR (95%) CI= 0.82 (0.68, 0.98))]. The baseline prevalence of depression decreased across PDQS quintiles (p for trend=0.015). A statistically significant association between PDQS and changes in depressive symptoms after 2-y follow-up was found (β (95%) CI = −0.67 z-score (−1.17, −0.18). A higher PDQS was cross-sectionally related to a lower depressive status. Nevertheless, the null finding in our prospective analysis, raises the possibility of reverse causality. Further prospective investigation is required to ascertain the association between PDQS and changes in depressive symptoms along time.

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