An Application of Bayesian Model Averaging for Investigating of the Relationship Between Monetary Policy variables and Asset Price Fluctuations

Abstract

This study aims to investigate the relationship between liquidity and asset price fluctuations in the Iranian financial market applying innovative methods of averaging. The findings are useful for policymakers because the surveys can be used in monetary policy decisions. The data used in this research are quarterly from March 2006 to April 2020. To this end, the statistics from the economic time-series database of the Central Bank of the Islamic Republic of Iran and other related sources have been used. Bayesian Model Averaging (BMA) has successfully been used in the experimental growth literature as a way to overcome the sensitivity of the results to the characteristics of different models. The variables are the real liquidity as a dependent one and fluctuations in total stock price, total housing price, central bank assets, the government debt to banks, exchange rate, and the coin price are considered independent ones.In terms of the movable assets, the results show a positive and significant relationship between fluctuations in real total housing prices and liquidity and a negative relationship between Bahar-e Azadi Iranian Gold Coin fluctuation and liquidity. For immovable assets, the real net fluctuation of central bank assets and the government debt to banks have a positive relationship with liquidity. There is a negative relationship of real total stock price fluctuation and real exchange rate fluctuation with the liquidity.

Keywords

• bayesian model averaging
• liquidity
• asset price fluctuations
• movable and immovable assets