https://etalpykla.vilniustech.lt/handle/123456789/154007 2026-04-04T13:26:57Z https://etalpykla.vilniustech.lt/handle/123456789/154210 Influence of macroeconomic factors on stock prices in Poland – cross section and time series analysis Schabek, Tomasz; Maknickienė, Nijolė The purpose of the study is to determine if the macroeconomic factors influence rates of returns from broad index of stocks in Poland. The study investigates stability of relation between macroeconomic and stock market variables in short and long time period. After running time series regressions we check if selected macro variables are still significant in cross-section of stock returns including control variables like price to book value, capitalization and momentum. The study is based on large sample of individual rates of returns and macroeconomic variables describing real sphere of the economy. Mine findings suggest that the short and long term relation is statistically and economically significant although not stable in the both analysed time horizons. Macroeconomic beta parameter (sensitivity to macro variables measure) is not significant in cross-sectional test proving that traditionally accepted variables (in our study only price to book-value and momentum) still better explain the expected returns. 2018-01-01T00:00:00Z https://etalpykla.vilniustech.lt/handle/123456789/154209 Computation intelligence based daily algorithmic strategies for trading in the foreign exchange market Maknickienė, Nijolė; Kekytė, Ieva; Maknickas, Algirdas Successful trading in financial markets is not possible without a support system that manages the preparation of the data, prediction system, and risk management and evaluates the trading efficiency. Selected orthogonal data was used to predict exchange rates by applying recurrent neural network (RNN) software based on the open source framework Keras and the graphical processing unit (GPU) NVIDIA GTX1070 to accelerate RNN learning. The newly developed software on the GPU predicted ten high-low distributions in approximately 90 minutes. This paper compares different daily algorithmic trading strategies based on four methods of portfolio creation: split equally, optimisation, orthogonality, and maximal expectations. Each investigated portfolio has opportunities and limitations dependent on market state and behaviour of investors, and the efficiencies of the trading support systems for investors in foreign exchange market were tested in a demo FOREX market in real time and compared with similar results obtained for risk-free rates. 2018-01-01T00:00:00Z https://etalpykla.vilniustech.lt/handle/123456789/154208 Profitability analysis of public-private partnership in healthcare delivery in Spain González-de Julián, Silvia; Polo-Garrido, Fernando; Barrachina-Martinez, Isabel; Vivas-Consuelo, David In the Valencian Community (Spain) there are 5 health districts managed by public-private partnerships. They are the so-called Alzira model, where the concessionaire builds and maintains the hospital facilities and provides health care services. The purpose of this paper is to address problems raised in the calculation of the limiting clause of profitability and to develop a financial statement analysis in order to assess profitability, solvency and liquidity. Results indicate that all concessionaires show very high debt-to-assets ratio, low liquidity, ROA fluctuates between 2.45% and 12.42%, and the IRR varies between 3.47% and 13.15%. Despite this, four of five concessionaries exceed the limiting clause using an “ad hoc” method as proxy of “cash flows”. 2018-01-01T00:00:00Z https://etalpykla.vilniustech.lt/handle/123456789/154207 Forecasting consumer price index (CPI) using time series models and multi regression models (Albania case study) Gjika (Dhamo), Eralda; Puka, Llukan; Zaçaj, Oriana In this work we analyse the CPI index as the official index to measure inflation in Albania, Harmonized Indices of Consumer Prices (HICPs) as the bases for comparative measurement of inflation in European countries and other financial indicators that may affect CPI. This study is an attempt to model CPI based on combination of multiple regression model with time series forecasting models. In the first approach, time series models were used directly on the CPI time series index to obtain the forecast. In the second approach, the time series models (SARIMA, ETS) were used to model and simulate forecast for each subcomponent with significant correlation to CPI and then use the multiple regression model to obtain CPI forecast. The projection of this indicator is important for understanding the country's economic and social development. This study helps researchers in the field of time series modeling, economic analysis and investments. 2018-01-01T00:00:00Z