|
|
MOVEMENT
Strach, Adam ; Coufal, Matěj (referee) ; Tobola, Ondřej (advisor)
The bachelor's thesis examines the dynamics of human movement in interaction with sports equipment in relation to the joy of movement. Part of the creative process is discovering one's own motivation to move. It uses the newly acquired knowledge when experimenting with various means of movement. The result of the work is a new sports activity and new sports equipment.
|
|
|
Significance of different financial ratios in predicting stock returns: NYSE - cross-industry analysis
Coufal, Matěj ; Mejstřík, Michal (advisor) ; Kurka, Josef (referee)
The goal of this research is to investigate the power of following seven variables to predict stock returns on the New York Stock Exchange: price to earnings ratio (P/E), dividend yield (DY), debt to equity ratio (D/E), book to market ratio (B/M), return on assets (ROA), return on equity (ROE) and market capitaliza- tion (MC). Companies selected for the analysis are divided into five industries (airlines, computers and software, financial services, food and beverages, energy) which enables to observe the difference between the sectors as far as the statistical significance of regressors is concerned. The ability of six financial ratios and MC to forecast stock returns is examined between February 2010 and February 2020, whereas three investment horizons are considered: three months, one year, three years. Panel data regression models reveal different significant variables for each industry and show that the strength of the relationship between these regressors and expected stock returns increases with a longer investment horizon.
|
|
|
Influence of stock market variables on correlations among S&P sectors
Coufal, Matěj ; Čech, František (advisor) ; Baruník, Jozef (referee)
This thesis investigates the influence of the exogenous variables (S&P 500 Index, 10-year US Treasury Note, crude oil, and CBOE Volatility Index (VIX)) on the dynamics of correlations among S&P sectors. We concentrate on daily and weekly investment horizons, and employ the bivariate Dynamic Conditional Correlation (DCC) model. Changes in correlations implied by the DCC model are further modelled using the exogenous variables. The results indicate that VIX has the best ability to predict future changes in correlations. An increase in VIX on day (week) t is expected to cause a rise in correlations on day (week) t + 1. Next, correlations of the Energy sector tend to increase in weeks when crude oil prices are falling. Further, correlations of the Information Technology sector are likely to increase on days of rising yield on the 10-year US Treasury Note. Although we detect a certain power to predict future changes in correlations, very little of these changes is actually explained. 1
|
|
|
MOVEMENT
Strach, Adam ; Coufal, Matěj (referee) ; Tobola, Ondřej (advisor)
The bachelor's thesis examines the dynamics of human movement in interaction with sports equipment in relation to the joy of movement. Part of the creative process is discovering one's own motivation to move. It uses the newly acquired knowledge when experimenting with various means of movement. The result of the work is a new sports activity and new sports equipment.
|
|
|
Significance of different financial ratios in predicting stock returns: NYSE - cross-industry analysis
Coufal, Matěj ; Mejstřík, Michal (advisor) ; Kurka, Josef (referee)
The goal of this research is to investigate the power of following seven variables to predict stock returns on the New York Stock Exchange: price to earnings ratio (P/E), dividend yield (DY), debt to equity ratio (D/E), book to market ratio (B/M), return on assets (ROA), return on equity (ROE) and market capitaliza- tion (MC). Companies selected for the analysis are divided into five industries (airlines, computers and software, financial services, food and beverages, energy) which enables to observe the difference between the sectors as far as the statistical significance of regressors is concerned. The ability of six financial ratios and MC to forecast stock returns is examined between February 2010 and February 2020, whereas three investment horizons are considered: three months, one year, three years. Panel data regression models reveal different significant variables for each industry and show that the strength of the relationship between these regressors and expected stock returns increases with a longer investment horizon.
|
guest ::
RSS feed.