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

Year 2017, , 24 - 28, 30.12.2017

Kenan Ilarslan

https://doi.org/10.17261/Pressacademia.2017.740

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

• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• Le, T.H. ve Chang, Y. (2016). Dynamics between strategic commodities and financial variables: evidence from japan. Resources policy, vol. 50, p. 1-9.
• 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.
• 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.
• 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.
• Rachev, S.T., Hsu, J.S, Bagasheva, B.S. ve Fabozzi, F.J. (2008). Bayesian Methods in Finance. NJ, USA: John Wiley Sons
• 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.
• 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