ANALYSIS OF THE RELATIONSHIP BETWEEN GOLD PRICES AND ISE 100 INDEX THROUGH BAYES THEOREM FRAMEWORK

Abstract

Objective- In the context of finance theory, predicting the return / price or movements of financial assets over the historic data provides elemination of the uncertainty and make such assets manageable. Therefore, modeling the financial asset behaviors with objective and scientific methods greatly contribute to reduce and manage the risk. In this study, the direction of the relationship between the Gold prices and the BIST 100 index was determined and tried to be estimated within a certain probability  and how the change in the Gold prices in the Bayes Theorem would be reflected in the BIST 100 index.

Methodology- Variables used in the study are the bullion gold gram sale price and BIST 100 index and the monthly closing prices of the mentioned variables are used as data set for the 18 years (2000: 01-2017: 07) period. The data were compiled from the official website of the Central Bank of the Republic of Turkey. E-Views 9 SV program was used for statistical analysis of data. During the methodological process, statistical methods such as Pearson Correlation Analysis and Bayes Theorem were used. 

Findings- In the study, it was found that positive correlation (0,91) exist between these two financial assets. In addition, the significance of the correlation coefficient at the 5% significance level was tested and it was determined that there was a significant correlation between the Gold prices and the BIST 100 index.  At a later stage, it was tried to estimate with certain probability, how the BIST 100 index would react to an increase in gold prices. As a result of the analysis carried out in the framework of the Bayes theorem, it is found that increase of the gold prices will also lead to increase the BIST 100 index with  52.1%  probability. 

Conclusion- It is important, valuable and necessary for investors to make accurate and on-the-spot decisions, especially in uncertainty and risk environment in the markets. If this uncertainty is managed by being reduced to a measurable risk level, it offers the opportunity to provide extraordinary returns or to minimize losses for individual and / or institutional investors. Working with scientific data and methods to understand, mitigate and manage the future risks of assets in this framework makes a significant contribution to the success of risk management strategies implemented by financial institutions. In this context, a positively and statistically significant relationship was found between gold price and BIST 100 index in the study. Moreover, in the case of an increase in gold prices, the BIST 100 index will increase too with 52.1% probability.

Keywords

• Assets prices,gold prices,ISE 100,Bayes Theorem,financial prediction

References

1. Açıkalın, S. ve Başçı, E.S. (2016). Cointegration and causality relationship between bıst 100 and bist gold ındices. Yönetim ve ekonomi, cilt. 23, sayı.2, s. 565-574.
2. Basit, A. (2013). Impact of kse-100 index on oil prices and gold prices in Pakistan. IOSR journal of business and management vol.9, no.5, p.66-69.
3. Doğru, B. ve Uysal, M. (2015). Bir yatırım aracı olarak altın ile hisse senedi endeksi arasındaki ilişkinin analizi: Türkiye üzerine ampirik uygulama. Çukurova üniversitesi sosyal bilimler enstitüsü dergisi, cilt.24, sayı.1, s.239-254.
4. Gayathri, V. ve Dhanabhakyam, D. (2014). Cointegration and causal relationship between gold price and nifty – an empirical study. Journal of research in management & technology, vol.3, no. 7, p. 14-21.
5. Gilmore, C.G., Mcmanus, G.M., Sharma, R. ve Tezel, A. (2009). The dynamics of gold prices, gold mining stock prices and stock market prices comovements. Research in applied economics, vol. 1, no.1, p. 1-19.
6. İlarslan, K. (2017). Altın fiyatları ile borsa endeksi arasında eş bütünleşme ve nedensellik ilişkisi, Avrasya sosyal ve ekonomi araştırmaları dergisi, cilt. 4, sayı.6, s. 114-125.
7. Kothari, A. ve Gulati, D.(2015). Investment in gold and stock market: an analytical comparison. Pacific business review international, vol. 7, no. 9, p. 65-68.
8. Le, T.H. ve Chang, Y. (2016). Dynamics between strategic commodities and financial variables: evidence from japan. Resources policy, vol. 50, p. 1-9.

9. Mishra, P. K. (2014). Gold price and capital market movement in India: the toda–yamamoto approach. Global business review, vol. 15, no.1, p. 37-45.
10. Öncü, M.A., Çömlekçi, İ., Yazgan, H.İ. ve Bar, M. (2015). Yatırım araçları arasındaki eş bütünleşme (bist100, altın, reel döviz kuru). Aibü sosyal bilimler enstitüsü dergisi, cilt. 15, s. 43-57.
11. Patel, S.A. (2013). Causal relationship between stock market ındices and gold price: evidence from India. The IUP journal of applied finance, vol. 19, no. 1, p. 99-109.
12. Rachev, S.T., Hsu, J.S, Bagasheva, B.S. ve Fabozzi, F.J. (2008). Bayesian Methods in Finance. NJ, USA: John Wiley Sons
13. Sharma, g.d. ve Mahendru, M. (2010). Impact of macro-economic variables on stock prices in India. Global journal of management and busines research, vol.10, no.7, p. 19-26.
14. Tripathi, L.K., Parashar, A. ve Singh, R. (2014). Global factors & gold prıce in India- a causal study. International journal of advanced research in management and social sciences, vol.3, no. 7, p. 161-18