This study presents an integrated system where wavelet transforms and recurrent neural network (RNN) based on artificial bee colony (abc) algorithm (called ABC-RNN) are combined for stock price forecasting. The system comprises three stages. First, the wavelet transform using the Harr wavelet is applied to decompose the stock price time series and thus eliminate noise. Second, the RNN, which ha...

Stock price crash risk has a significant impact on investors, creditors, managers, and shareholders, so the prediction of this phenomenon is a very important issue in investment and risk management decisions. This research investigates the effect of business strategy and stock price synchronicity on stock price crash risk. Following Bentley et al.[2], composite strategy score has been used to ...

generally, high oil prices slow economic growth, cause inflationary pressures and creates global imbalances. in addition, oil price volatility increase uncertainty and restrain the much-needed investment in the capital market. thus, this paper applies the augmented dickey fuller and johansen co-integration tests in which the effect of oil price volatility, crude oil price and stock price is ana...

study of the changes in the stock price in tehran stock exchange is of great importance. this is because of its application in forecasting the stock price in the stock exchange. the aim of this article is to investigate the forces and mechanisms that cause the dramatic changes in stock price and the formation of chaotic trend. to test whether the chaotic trend in the tehran stock exchange exist...