DSpace Collection:
http://dspace.wunu.edu.ua/handle/316497/14834
2024-03-28T08:44:54ZSignalling in the Stock Markets: Evidence from Juventus FC
http://dspace.wunu.edu.ua/handle/316497/31564
Title: Signalling in the Stock Markets: Evidence from Juventus FC
Authors: Wu, Maoguo
Abstract: In the paper, we examine the key drivers of the stock prices of a publicly
traded football club, Juventus Football Club, one of the leading football clubs in
the Italian Serie A. The underlying financial theory that we apply and test is the
news model, which states that changes in the stock prices are the results of the
emergence of the unexpected new public information. When applying it to sport
industries, it can be understood that unexpected match results affect stock price
of the club. In addition, by bringing the reversed news model into the paper, we
test whether major corporate governance related events have any explanatory
effect on stock prices.2012-01-01T00:00:00ZUrban Income Inequality, Time and Income Sources Analyses in China
http://dspace.wunu.edu.ua/handle/316497/31563
Title: Urban Income Inequality, Time and Income Sources Analyses in China
Authors: Wang, Feng; Liu, Xin
Abstract: This paper studied the income mobility and income sources with a sample
from the city of Shenzhen, the special economic region of China. The empirical
results show that Chinese urban residents’ long term income inequality is less
than short term inequality. The aggregate households’ income inequality is less
than the income in single income source. The income mobility of Shenzhen is
closing to the mobility of the developed countries. The mobility of income from a
single source is higher than the mobility of the aggregate household’s income.
The short term income mobility is less than the long term.2012-01-01T00:00:00ZDeterminants and Projections of Demand for Higher Education in Portugal
http://dspace.wunu.edu.ua/handle/316497/31562
Title: Determinants and Projections of Demand for Higher Education in Portugal
Authors: Vieira, Carlos Rodrigues; Vieira, Isabel Viegas
Abstract: Place the abstract of you Article This paper formulates a model of demand
for higher education in Portugal considering a wide range of demographic, economic, social and institutional explanatory variables. The estimation results suggest that the number of applicants reacts positively to demographic trends,
graduation rates at secondary education, female participation, compulsory
schooling and the recent Bologna process. Demand reacts negatively to the ex-
istence of tuition fees and to unemployment rates. Within an adverse demo-
graphic and economic context, forecasts of demand for the next two decades
suggest the need to increase participation rates, to avoid funding problems in
the higher education system and increase long-term economic development
prospects.2012-01-01T00:00:00ZClassification of Domestic and Foreign Commercial Banks in Turkey Based on Financial Performances Using Linear Discriminant Analysis, Logistic Regression and Artificial Neural Network Models
http://dspace.wunu.edu.ua/handle/316497/31561
Title: Classification of Domestic and Foreign Commercial Banks in Turkey Based on Financial Performances Using Linear Discriminant Analysis, Logistic Regression and Artificial Neural Network Models
Authors: Turkan, Semra; Polat, Esra; Gunay, Suleyman
Abstract: The Data Mining (DM) techniques of linear discriminant analysis (LDA),
logistic regression (LR) and artificial neural network (ANN) models are among
the multivariate techniques used for predicting the predefined class membership
of dependent variables. Hence, the aim of this study is to discuss and illustrate
LDA, stepwise LDA, LR, forward LR and four types ANNs and compare these
models’ correct classification ability. For this purpose, the data of commercial
banks operating in Turkey in two pre-defined groups, namely domestic and for-
eign banks, is used. In this study, the classification performance of ANN models
against to LDA and LR is investigated. The ability of these classification methods
in classifying the banks correctly is compared in terms of correct classification
rates. As the results reveal that ANN (ANN-Prune) outperforms LDA and LR in
terms of bank classification accuracy and thus, provide an effective alternative
for implementing bank classification.2012-01-01T00:00:00Z