Relationship Between the Volatility of Stock Returns and the Volatility of Macroeconomic Variables: A Case of Turkey

Tuğba Dayıoğlu,Yılmaz Aydın

doi:10.11648/j.ajtab.20190502.13

Tuğba Dayıoğlu, Yılmaz Aydın

Open Access

https://doi.org/10.11648/j.ajtab.20190502.13

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Abstract

In this paper, we examined the relationship between BIST-100 Index (SPI) and a set of macroeconomic variables volatility using Vector Autoregressive (VAR) model. The relationship between the stock market and macroeconomic variables has been subjected to serious economic research. A stock market plays important role for the reallocation of funds in many sectors of an economy. The macroeconomic factors make investors to choose the stock because investors are interested to know about the factors affecting the working of stock to manage their portfolios. Some investors show the stock prices volatility is based on directional trend in the stock prices but actually volatility is amount of fluctuation in stock prices. For this purpose we used the volatility of the variables. This study period 2006-2018 stock market using monthly data for Turkey is to examine the relationship between stock return volatility and macroeconomic volatility. We used the macroeconomic variables volatility these are industrial production (IP), money supply (M1), inflation rate (CPI), US dollar equivalent exchange rate (EX) and oil prices (OIL). We used montly data for the period between january 2006 and december 2018. Asymmetric GARCH models are used for the series volatility. The best performing GARCH model in these models are considered as volatlity. Exchange rate and industrial production index have an important effect on stock market volatility.

Highlights

The periods of high stock market volatility in advanced and emerging markets have intensified discussions about the reasons for such price movements
A study based on data from Finland [10, 11] shows that one-third and more than two-thirds of the changes in conditional stock market volatility are conditional on macroeconomic volatility; ie, inflation, industrial production and money supply
While the vast majority of the earlier studies relied on the Autoregressive Conditional Heteroscedasticity (ARCH) framework, there is a large and diverse time series literature on volatility modelling

Summary

Introduction

The periods of high stock market volatility in advanced and emerging markets have intensified discussions about the reasons for such price movements. Experiments were conducted to examine the relationship between stock market volatility and macroeconomic variables. The theoretical motivation of such a link is inspired by the ın simple discounted current-value model of the stock price. The study [16] has shown that macroeconomic variables, more clearly inflation, industrial production and money supply - will determine the stock market volatility for the US. Schwert's finding provides weak evidence that macroeconomic volatility determines stock market volatility. A study based on data from Finland [10, 11] shows that one-third and more than two-thirds of the changes in conditional stock market volatility are conditional on macroeconomic volatility; ie, inflation, industrial production and money supply. The study [12] examined the relationship between conditional stock market volatility and conditional macroeconomic volatility with UK data. The study [3] expanded the work of the study [14] using data from thirteen stock markets

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