Impact of macroeconomic variables on unobserved systematic risk using Kalman filter
Subject Areas : Journal of Investment Knowledge
Majid
Hatef Vahid
1
(PhD Student in Financial Engineering, Department of Economic Sciences, Faculty of Management, Islamic Azad University, Central Tehran Branch, Tehran, Iran)
Abbas
Saleh Ardestani
2
(Faculty member of the Department of Economic Sciences, School of Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran)
Keywords: multivariate regression, Data Panel, Macroeconomic variables, Unobserved Systematic Risk, Kalman Filter,
Abstract :
The main purpose of this study was to investigate the effect of macroeconomic variables on unobserved systematic risk using the Kalman filter. Systematic risk indicates the degree of dependence between changes in share prices and changes in the market index. However, the amount of systematic risk can be very different from the expected amount, due to the confusion in stock price changes, resulting from emotional transactions, overreactions and price manipulation. Therefore, it is necessary to control the effects of these disturbances in measuring systematic risk. The method of the present study is descriptive-correlational which was performed using statistical methods to examine the relationships between variables based on Ives software. To analyze the data in this study, it is suggested to use Kalman filter. Also, filtered and turbulent values have been used under the heading of unobserved systematic risk. According to the obtained result, it can be said that all variables have a significant relationship with the systematic risk not observed in the model. Then, using data analysis, the hypotheses were examined. The results obtained in relation to statistics and a significant level show the confirmation of all hypotheses in terms of the impact of economic variables on the components of inflation, economic growth, exchange rate, stock market index and volume. Money showed unprecedented systematic risk. Also, the effect of different variables and finally the estimation of coefficients showed that the highest coefficient among the variables is related to inflation index and stock market.
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