محمدرضا قدیم پور

The ability to predict the stock market and analyze market trends is invaluable to researchers and anyone interested in investing. However, this task is a challenging problem due to a large number of parameters and unpredictable noise that may affect the stock price. To overcome this issue, researchers have employed numerous approaches such as Moving Average (MA), Support Vector Machine (SVM), and Neural Networks. With technological advances, deep learning methods have become popular in processing time-series data. In this paper, we compare two recently introduced deep learning models, namely a Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), in forecasting daily movements of the Standard & Poor (S&P 500) index using the daily closing price of this index from 14/5/1991 to 14/5/2021. Results show that both models are effective and accurate in stock market prediction. In this case study, the mean squared error (MSE) and mean absolute error (MAE) for the GRU model are slightly lower than the LSTM model; hence, GRU outperformed the LSTM model despite its simpler structure. The results of this study are applicable in various instances where it is challenging to identify patterns among large volumes of unstructured data, such as medical data analysis, text mining, and financial time series modeling.

This study investigates the return connectedness across the major Middle East and North Africa (MENA) stock markets, Brent crude oil, and Gold, from April 2008 to July 2019 using the frequency-domain framework and causality among these markets. Three different periods, including the short term, medium term, and long term are considered to analyze the interconnectedness of markets. The results of the study indicate that the markets are more connected and speculative in the short term, thus there is less chance of portfolio diversification among these markets in the short term. The QE general contributes more to the Brent crude oil market in the short term, and Tadawul has more connectedness with this market in other timeframes. Moreover, among MENA stock markets, the QE general contributes more to the short term and medium term and ADX general has more influence on other markets in the long term. The financial crisis of 2008 and the oil price crash during 2014 increased the total return connectedness of these markets with the shocks having long-lasting effects. The findings of this study can offer new insights to policymakers and investors. JEL Classification: C18, C32, G15