Article Information
Journal: Business and Economics Research Journal
Title of Article: Examining the Dynamics of Macroeconomic Indicators and Banking Stock Returns with Bayesian Networks
Author(s): Fatma Busem Hatipoglu, Umut Uyar
Volume: 10
Number: 4
Year: 2019
Page: 807-822
ISSN: 2619-9491
DOI Number: 10.20409/berj.2019.202
According to the modern portfolio theory, the direction of the relationship between the securities in the portfolio is stated to be effective in reducing the risk. Moreover, securities in high correlation are avoided by taking place in the same portfolio. The models structured by the Bayesian networks are capable of visually illustrate the probabilistic relationship. Also, portfolio returns could be refreshed simultaneously when new information has arrived. The study aims to provide dynamic information through Bayesian networks and to investigate the relationship between macroeconomic indicators and stock returns of Turkish major bank stocks based on the Arbitrage Pricing Model. The dataset includes stock returns of four banks listed in the Borsa Istanbul from June 2001 to January 2017. Besides, macroeconomic variables such as BIST-100 Index, oil prices, inflation, exchange, and interest rate & money supply are gathered for the same period. The results suggest that the Bayesian network models allow dynamics among stock returns could be investigated in more detail. Additionally, it determines that macroeconomic variables would have various impacts on stock returns on bank stocks by comparison of the conventional methods.

Keywords: Arbitrage Pricing Model, Bayesian Networks, Machine Learning, Portfolio Selection Theory, Banking Stocks

JEL Classification: C11, G11, G12

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