This study compares the results of two completely different models: statistical one (ARIMA) and deep learning one (LSTM) based on a chosen set of NASDAQ data. Both models are used to predict daily or monthly average prices of chosen companies listed on the NASDAQ stock exchange. Research shows which model performs better in terms of the chosen input data, parameters and number of features. The chosen models were compared using...

The main aim of this article is to examine the accuracy of different methods of share valuation used by Polish analysts in reports prepared in order to issue recommendations for companies listed on the Warsaw Stock Exchange. In the literature on the subject, the view which prevails is that the more sophisticated methods, i.e. those taking into account the discounting process, are characterised by higher valuation accuracy. However,...

The paper considers the forecasting of the Warsaw Stock Exchange price index WIG20 by applying a state space wavelet network model of the index price. The approach can be applied to the development of tools for predicting changes of other economic indicators, especially stock exchange indices. The paper presents a general state space wavelet network model and the underlying principles. The model is applied to produce one session...

The purpose of the study is to assess whether the inclusion of investments in gold and/or crude oil improves an investment portfolio consisting of shares of enterprises included in the WIG20 index (traditional invest-ments). All possible combinations of investment portfolios with minimal risk and maximum efficiency were tested. The portfolios were determined based on Markowitz’s portfolio theory. All results were compared...