| Abstract [eng] |
The theme of this Master’s degree paper is the Identification of Lithuanian Risky Stock Market Sector by Artificial Intelligence Techniques. The object of this job is the implement for Lithuania market risk. In 2008, held in the U.S. real estate crisis has grown into a global financial crisis affecting the Lithuania stock market. The main goal of the paper is identification the risky sector of Lithuania stock market in 2008 using Neural Network method. The main tasks to reach this goal are: divide all Lithuania stock market in to a groups. Write a program using Borland C++ Builder, based on neural network algorithm. Methodology developed in this work will help to identify the sectors of activity, which the crisis affected the most. With the help of artificial intelligence neural networks, it is shown that the financial sector is a risky investment sector. Using various explanatory variables (share profitability, average, dispersion, transactions amount and volumes), factors were identified, which had the most sensitive response to the crisis in the market. The length of this paper is 61 pages; there are 25 pictures and 28 tables in this paper. |
