Abstract
In the past two decades, especially after the financial crisis of 2007–09, the literature for examining the availability of integration between the stock exchanges in developed and developing markets has grown. The importance of this topic stems from the significant implications of the linkage between exchange markets on various decisions taken by interested parties, such as policymakers and investors, in the decisions for portfolio diversification. This study examines the relationship between a developing stock exchange index, Amman Stock Exchange Index (ASEI), and the number of international indices, including S&P 500, NASDAQ, Nikkei, DAX, CAC, and HSI for 2008‐2019. To validate the availability of the linkage between the indices, the author includes various tests of a correlation coefficient, stepwise regression analysis, and artificial neural network (ANN). Despite the results indicating that the ANN is more efficient than linear regression in investigating the availability of the relationship between ASEI and international indices, stepwise regression and neural network support this relationship. Furthermore, ANN results revealed that the S&P 500 index and year have the most substantial relationship with ASEI. Our research is theoretically and practically important; policymakers and investors can benefit from our findings. Future studies may explore the effect of different international stock market indices on ASEI or other developing markets. Further studies can use macroeconomic factors to build prediction models for stock market indices.
Highlights
Financial markets are the key role players in the financial system of countries because of their ability to facilitate the flow of saving and investing decisions in the economy
Results and Discussion is section explains the outcomes of the main parts discussed in the former section to validate the research methodology in this study. e results include the Pearson correlation coefficient, graphical representation between international and Amman Stock Exchange Index (ASEI), running stepwise regression model, and building perdition model using artificial neural network (ANN)
In the past two decades, especially after the financial crisis of 2007-08, the literature for examining the availability of integration between stock exchanges in developed and developing markets has been growing. e importance of this topic stems from the significant implications of the linkage between exchange markets on various decisions taken by interested parties such as policymakers, investors, and academics
Summary
Financial markets are the key role players in the financial system of countries because of their ability to facilitate the flow of saving and investing decisions in the economy. Financial markets are considered the most profitable and riskiest field for investors because they need accurate expectations of stock indices’ movement to help them take the appropriate profitable investment decisions [1–4]. Making these right decisions is a complicated mission because many macroeconomic variables and international factors interact to influence the movement of stock markets indices and subindices into unanticipated levels. Transfer entropy is an effective way to quantify the flow and interaction of information between indices
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