Vol. 8 No. 5 (2020): Business & Management Studies: An International Journal


MBA Student, Anadolu Üniversity
Lect., Anadolu University
Prof. Dr., Anadolu Üniversity

Published 2020-12-25


  • Oil Prices BIST100 VAR Analysis
  • Petrol Fiyatları, BIST100, VAR Analizi

How to Cite

KAKACAK, K., MERİÇ, E., & TEMİZEL, F. (2020). ANALYSIS OF THE IMPACT OF OIL PRICES ON BIST100 INDEX. Business & Management Studies: An International Journal, 8(5), 3751–3771. https://doi.org/10.15295/bmij.v8i5.1532



                Some of the studies in the literature are the sources of the effects of oil prices evaluated in this study on the BIST100 index. In the study of Güler and Nalın (2013), which is one of the studies in the literature, they analyzed the IMKB100, plastic, oil and chemistry indices of the oil prices that they examined with Granger causality and co-integration tests. In their analysis, they concluded that oil prices were not effective on these indices. In a similar study, Şener, Yılancı and Tıraşoğlu (2013) examined the relationship between Hatemi-J & Irandoust test, which is linked to causality and co-integration tests, and oil prices and BIST closing prices. As a result of the study, it was revealed that there is a co-integration between oil prices and the BIST closing index. Also, Özmerdivanlı (2014) found a causality between oil prices and BIST100 index in her study in 2014. These studies were based on to examine the effects of oil prices on the BIST100 index and were the source of the study to evaluate the causality relationship between the variables.


                Oil prices were the subject of this study with the BIST100 macro variable, which is accepted as the base indicator. While examining the relationship of the variables, Maghyereh, Awartani and Bouri (2016) and the work Ciner did in 2013 were considered as the primary sources.


                This study aims to investigate whether oil prices, which affect many stock market indexes, have an effect and a relationship on BIST100 index. The importance of the study is that it has proved the existence of oil prices with the results of the analysis.


                The effects of oil prices on BIST100 between 1.4.2000 and 7.14.2020 were investigated with the examinations. The reactions of these two variables in the changes that occur during this period will contribute to the interpretation of the changes that will occur in the market.


                Due to the frequent use of oil both as raw material and as a fuel, oil has a large share among the goods subject to import and export. For this reason, increases or decreases in oil prices may cause significant effects in financial markets and capital markets. The causality of these effects was examined in the design of the study, and the effects of oil price changes were analyzed by an applied method. Hypotheses have been established with the data used for implementation.

A model has been established for the VAR technique to be applied within the framework of the hypotheses that have been established. In the model, the official figures published in the Electronic Data Delivery System (EVDS) for the period covering the prices of Brent oil prices and BIST100 index data between 1.4.2000 and 7.14.2020 were used. Data analysis technique was preferred due to the quantitative data used.


                In the study, an applied method was preferred to investigate the effects of oil prices on BIST100. In line with the information obtained from the application, the effects of oil prices were evaluated.




                Due to the use of oil as both production and consumption, oil prices are essential for financial markets and capital markets. For this reason, the effects of oil price changes should be analyzed. The effects of changes in oil prices should also be examined on the base index, BIST100. This situation creates the problem of the study and determines the purpose of the study.


                Oil price and BIST100 index data were obtained through EVDS. In the analysis, monthly data covering the period between 1.4.2000 and 7.14.2020 were used as samples.


                Within the scope of the study, the quantitative research method, which allows the numerical data to be analyzed, was used. Connectivity and experimental methods were preferred among the quantitative research models. The reason for choosing these methods is to examine whether there is a relationship between the two macroeconomic variables and to determine the effect between the two variables.


                In this study, the VAR technique was preferred, and a model was created within the scope of this technique through Eviews 10 software. This model was found appropriate because the causality and effects between the variables were investigated for the model created.


                Two hypotheses have been established on the variables selected for the analysis in the study. These hypotheses are as follows;

H0: Changes in oil prices have an impact on the BIST100 index.

H1: Changes in oil prices do not affect BIST100 index.

The analysis was made based on these hypotheses.


                At the beginning of the analysis, stationarity was considered as the necessary condition of VAR technique, it was determined that the data sets used were not stationary, and the series was stationed. It has been tested whether the VAR model established for stationarity meets autocorrelation, heteroscedasticity, normality and unit root including conditions. Analysis has been started for the VAR model, which provides all these conditions. The model established within the scope of the analysis was subjected to causality test, impact-response test and variance decomposition test. As a result of the causality test, it was concluded that oil prices constitute the reason for BIST100 index. In addition to this result, a meaningful result was not obtained in the impact-response test. These study results are similar to the causality analysis studies in the literature. Although the studies examining the effects of oil prices on stocks include different period datasets, similar results have been achieved with many of them.


                In the Granger causality test conducted during the analysis, it was concluded that the oil prices were the cause of the BIST100 index, but the BIST100 index did not constitute the reason for the oil prices. According to the impulse-response test applied after the causality test, a meaningful result could not be reached.




                Hypotheses established at the beginning of the analysis were examined with different tests during the analysis. As a result, it was accepted that the established H0 hypothesis, that is, oil prices affected BIST100.

3.3. DISCUSSING the FINDINGS with the LITERATURE        

                The findings obtained are similar to many studies in the literature. Studies with different data sets gave similar results for the same variables.


                Based on the empirical findings obtained in the study, it was concluded that brent oil prices affected the BIST100 index. However, future studies should investigate the effects of oil prices on plastic, chemistry and automotive indices. In this study, data sets were limited to the source obtained.


  • As a result of the causality test, a one-way relationship has been found, and no mutual relationship has been found. The one-way relationship was found from oil prices to BIST100 index. Oil prices were effective on the BIST100 index, but no effect on oil was found for BIST100.
  • In addition to the one-way relationship, a meaningful result was not achieved in the impulse-response tests. BIST100 does not react significantly to a one-unit shock to oil prices. Likewise, oil prices do not respond significantly to a one-unit shock to the BIST100 index.
  • In the variance decomposition test, which has been done as a final test, a large part of the change in oil prices is met by itself.


  • It should be remembered that oil is used in the production and consumption areas. When examining oil prices, their effects should be evaluated from these aspects.
  • Investors should also search the chemical and plastic industry indices for oil used in production, as well as the automotive industry indices for oil in consumption.


In order to find out the general effects in the investigation of the effects of oil prices, the base index was preferred, and the data sets were limited within the framework of the source obtained.


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