Efficient market hypothesis

For many investors, it is important to predict the future trend of abnormal stock returns. Thus, in this research, the abnormal stock returns of the listed companies in Tehran Stock Exchange were tested since 2008- 2017 using three hypotheses. The first and second hypotheses examined the non-linearity and non-randomness of the abnormal stock returns ′ trend around the release date of annual financial statements, respectively. While, the third hypothesis tested the potential of the chaos model in explaining future abnormal returns based on the past abnormal returns around the release date of the annual financial statements. For this pur-pose, BDS, Teraesvirta Neural Network, and White Neural Network tests were used to investigate its non-linearity. In addition, Lyapunov exponent, correlation dimension, Dickey-Fuller, and Hurst exponent tests were used for testing non-randomness and the fitness of AR, SETAR, and LSTAR models to determine the optimal model in explaining the abnormal returns utilizing R software. Results of these tests represented a non-linear and non-random process and chaos in the abnormal stock returns, implying the predictability of abnormal stock returns. Also, among three used chaos models, the LSTAR model had lower error and more predictability than the other two models.

The purpose of this study is to study the indicators for evaluating the effectiveness of the implementation of investment processes on the securities market, taking into account the scientific foundations of information management systems and analysis of indicators of financial efficiency of the investment function of the securities market in Ukraine. The relevance of this study is due to the growing importance of management information systems in all sectors of the Ukrainian economy, in particular, the provision of solutions to the problems of activating investment processes in the securities market of Ukraine by analyzing and reassessing the effectiveness of investment processes at this level, taking into account the scientific basis of management information systems.  A set of indicators that best reflect the implementation of the investment function of the Ukrainian securities market is proposed. A matrix of characteristics of investment processes in the securities market is proposed. It is argued why domestic and foreign investors prefer local securities market indices when making investment decisions. Through the implementation of correlation-regression models, it has been proven that, on average, 87% of changes in investments in securities are due to changes in the number of licensed entities, which on the Chedoch scale indicates a close relationship between the indicators. The results obtained using statistical inference methods indicate a high impact of both external macroeconomic factors that inhibit the development of the securities market and internal, which in turn is reflected in the indicators of assessing the effectiveness of investment processes in the securities market.