Purpose: To evaluate open lower limb trauma management in children. Me-thod: We conducted a twelve-month cross-sectional prospective study. Results: Open trauma of lower limb had 7.9% of hospital frequency. Mean age w...Purpose: To evaluate open lower limb trauma management in children. Me-thod: We conducted a twelve-month cross-sectional prospective study. Results: Open trauma of lower limb had 7.9% of hospital frequency. Mean age was 8 years with a sex ratio of 2.45. In 68.4% of cases, trauma occurred in road traffic accidents. Average consultation time was 2.4 hours. Trauma mainly affected the leg in 39.5% of cases, and the thigh in 34.2%. Soft tissue wounds occurred in 52.6% of cases, and open fractures in 47.4%. Average response time was one hour. Wound trimming and suturing were performed in 76.3% of cases and combined with bone nailing in 15.8%. The outcome was favorable in 92.1% of cases. Average hospital stay was 4.37 days. Conclusion: Open trauma to the lower limb is a frequent and occurs mainly in road traffic accidents. Management was early, with a favorable outcome for most patients and a short hospital stay.展开更多
Exposure to market risk is a core objective of the Capital Asset Pricing Model(CAPM)with a focus on systematic risk.However,traditional OLS Beta model estimations(Ordinary Least Squares)are plagued with several statis...Exposure to market risk is a core objective of the Capital Asset Pricing Model(CAPM)with a focus on systematic risk.However,traditional OLS Beta model estimations(Ordinary Least Squares)are plagued with several statistical issues.Moreover,the CAPM considers only one source of risk and supposes that investors only engage in similar behaviors.In order to analyze short and long exposures to different sources of risk,we developed a Time–Frequency Multi-Betas Model with ARMA-EGARCH errors(Auto Regressive Moving Average Exponential AutoRegressive Conditional Heteroskedasticity).Our model considers gold,oil,and Fama–French factors as supplementary sources of risk and wavelets decompositions.We used 30 French stocks listed on the CAC40(Cotations Assistées Continues 40)within a daily period from 2005 to 2015.The conjugation of the wavelet decompositions and the parameters estimates constitutes decision-making support for managers by multiplying the interpretive possibilities.In the short-run,(“Noise Trader”and“High-Frequency Trader”)only a few equities are insensitive to Oil and Gold fluctuations,and the estimated Market Betas parameters are scant different compared to the Model without wavelets.Oppositely,in the long-run,(fundamentalists investors),Oil and Gold affect all stocks but their impact varies according to the Beta(sensitivity to the market).We also observed significant differences between parameters estimated with and without wavelets.展开更多
The spread of the coronavirus has reduced the value of stock indexes,depressed energy and metals commodities prices including oil,and caused instability in financial markets around the world.Due to this situation,inve...The spread of the coronavirus has reduced the value of stock indexes,depressed energy and metals commodities prices including oil,and caused instability in financial markets around the world.Due to this situation,investors should consider investing in more secure assets,such as real estate property,cash,gold,and crypto assets.In recent years,among secure assets,cryptoassets are gaining more attention than traditional investments.This study compares the Bitcoin market,the gold market,and American stock indexes(S&P500,Nasdaq,and Dow Jones)before and during the COVID-19 pandemic.For this purpose,the dynamic conditional correlation exponential generalized autoregressive conditional heteroskedasticity model was used to estimate the DCC coefficient and compare this model with the artificial neural network approach to predict volatility of these markets.Our empirical findings showed a substantial dynamic conditional correlation between Bitcoin,gold,and stock markets.In particular,we observed that Bitcoin offered better diversification opportunities to reduce risks in key stock markets during the COVID-19 period.This paper provides practical impacts on risk management and portfolio diversification.展开更多
文摘Purpose: To evaluate open lower limb trauma management in children. Me-thod: We conducted a twelve-month cross-sectional prospective study. Results: Open trauma of lower limb had 7.9% of hospital frequency. Mean age was 8 years with a sex ratio of 2.45. In 68.4% of cases, trauma occurred in road traffic accidents. Average consultation time was 2.4 hours. Trauma mainly affected the leg in 39.5% of cases, and the thigh in 34.2%. Soft tissue wounds occurred in 52.6% of cases, and open fractures in 47.4%. Average response time was one hour. Wound trimming and suturing were performed in 76.3% of cases and combined with bone nailing in 15.8%. The outcome was favorable in 92.1% of cases. Average hospital stay was 4.37 days. Conclusion: Open trauma to the lower limb is a frequent and occurs mainly in road traffic accidents. Management was early, with a favorable outcome for most patients and a short hospital stay.
文摘Exposure to market risk is a core objective of the Capital Asset Pricing Model(CAPM)with a focus on systematic risk.However,traditional OLS Beta model estimations(Ordinary Least Squares)are plagued with several statistical issues.Moreover,the CAPM considers only one source of risk and supposes that investors only engage in similar behaviors.In order to analyze short and long exposures to different sources of risk,we developed a Time–Frequency Multi-Betas Model with ARMA-EGARCH errors(Auto Regressive Moving Average Exponential AutoRegressive Conditional Heteroskedasticity).Our model considers gold,oil,and Fama–French factors as supplementary sources of risk and wavelets decompositions.We used 30 French stocks listed on the CAC40(Cotations Assistées Continues 40)within a daily period from 2005 to 2015.The conjugation of the wavelet decompositions and the parameters estimates constitutes decision-making support for managers by multiplying the interpretive possibilities.In the short-run,(“Noise Trader”and“High-Frequency Trader”)only a few equities are insensitive to Oil and Gold fluctuations,and the estimated Market Betas parameters are scant different compared to the Model without wavelets.Oppositely,in the long-run,(fundamentalists investors),Oil and Gold affect all stocks but their impact varies according to the Beta(sensitivity to the market).We also observed significant differences between parameters estimated with and without wavelets.
基金supported by the Department of Economics and Management,University of Luxembourgfinancial support from the Department of Economics and Management,University of Luxembourg.
文摘The spread of the coronavirus has reduced the value of stock indexes,depressed energy and metals commodities prices including oil,and caused instability in financial markets around the world.Due to this situation,investors should consider investing in more secure assets,such as real estate property,cash,gold,and crypto assets.In recent years,among secure assets,cryptoassets are gaining more attention than traditional investments.This study compares the Bitcoin market,the gold market,and American stock indexes(S&P500,Nasdaq,and Dow Jones)before and during the COVID-19 pandemic.For this purpose,the dynamic conditional correlation exponential generalized autoregressive conditional heteroskedasticity model was used to estimate the DCC coefficient and compare this model with the artificial neural network approach to predict volatility of these markets.Our empirical findings showed a substantial dynamic conditional correlation between Bitcoin,gold,and stock markets.In particular,we observed that Bitcoin offered better diversification opportunities to reduce risks in key stock markets during the COVID-19 period.This paper provides practical impacts on risk management and portfolio diversification.
