The effect of macroeconomic fundamentals on financial market fluctuations in Iran (Combined Data Pattern Method with Different Frequency (Midas))

Document Type : Research Paper

Authors

1 PHD student, Islamic Azad University, Yazd Branch

2 Assistant Professor, Islamic Azad University, Yazd Branch

Abstract

Modeling fluctuations in financial markets is of interest to academic researchers due to its importance for the economy. Despite the empirical work done, modeling volatility in these markets is still a challenge. For this purpose, in the present study, the fluctuations of the financial markets and macroeconomic foundations in Iran were investigated using the mixed data pattern method with different frequency (MIDAS) for different seasonal and annual time frames.
The present study analyzes the fluctuations of financial markets and the foundations of macroeconomics in Iran (method of mixed data pattern with different frequency (Midas)) based on the frequency of data for different seasonal and annual periods. In the estimated model, annual data on trade openness, government spending, productivity, inflation and interest rates, and quarterly data on oil price fluctuations, exchange rate fluctuations, money supply and stock price index for the years 1370-1397 have been used. Data related to 1398 were not used in the initial estimation of the relationship in order to test the predictive power of the model outside the estimation range.          According to the results of inflation, money supply, exchange rate fluctuations and crude oil price fluctuations have a positive effect on financial market fluctuations and for one percent increase in inflation rate and money supply, financial market fluctuations increase by 92 and 82 percent. In other words, in terms of economic structure and according to the principles of economics, a steady increase in the exchange rate causes economic prosperity in society, but if this increase is temporary, economic prosperity cannot be observed. Also, by comparing the predicted values ​​with the realized values ​​and adding the second, third and fourth chapters to the model, the prediction accuracy of the model goes higher and gets closer to the real values

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Main Subjects


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