BIST 100 Index Estimation Using Bayesian Regression Modelling

Abstract

Identification of factors, determining the fluctuations of stock indices in the market, possesses great importance for the capital market actors. Not only specifying the factors and market but also explaining the relationship between them correctly, will reduce the amount of exposure financial risk and bring this topic into the limelight of market actors. The most important indicator of good progress in the economic cycle can be observed as the stock market index which is also used as macroeconomic indicators for developed economies. It is generally observed that all the stock prices rise or fall in the same period and this question gives us the impression that there are some factors that have an influence in this period. Having the properties of dynamic, complex and non-linear structure makes this analysis tough and solving the problem requires very complex and difficult processes. Due to high uncertainty and volatility, while estimating the stock price behaviour, stock investments carry more risk than any other investment. Moreover, BIST index possesses very high chaotic structure, it is not possible to conclude the long-term predictability. Our study will address the portion of the macro factors affecting the stock index. Interest rates, exchange rates, money supply, inflation, gold, oil prices are investigated among the macro factors. For the study data was obtained using CBT from the Electronic Data Dissemination System monthly frequencies. The factors influencing the stock index was determined by the method of regression relationship between them, but the Bayesian method is used with regression for the estimation.

Keywords

• BIST 100 Index,Bayesian Regression Method,Forecasting

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