Endeksler Borsa Yatırımcıları İçin İyi Tahminciler mi? BDI, VIX ve GEPU Endeksleri ile Borsa Getirileri Arasındaki İlişkinin Analizi: Seçilmiş Bazı Gelişmiş Ülkelerin Borsaları Üzerine Bir Araştırma

Bu çalışmada Baltık Kuru Yük Endeksi (BDI), Volatilite Endeksi (VIX) ve Küresel Ekonomik Politika Belirsizlik Endeksi (GEPU) ile gelişmiş dünya borsaları arasındaki ilişki incelenmiştir. Çalışmanın temel amacı, bu endekslerin hisse senedi yatırım zamanlamasında kullanılabilecek iyi birer tahmin edici olup olmadığını analiz etmektir. Bu amaçla 2012 Temmuz ve 2021 Mayıs dönemine ait BDI, VIX, GEPU endeks verileri ile ABD, ALMANYA, İngiltere, İTALYA, FRANSA ve KANADA borsa verileri kullanılmıştır. Çalışmada regresyon analizi ve Granger nedensellik testi uygulanmıştır. Analiz sonucunda, örneklemde yer alan hisse senedi endeksleri üzerinde BDI, VIX ve GEPU endekslerinin istatistiksel olarak anlamlı bir etkiye sahip olduğu ve yatırımcıların bu endekslere bakarak bu borsalarda etkin zamanlama yapabilecekleri tespit edilmiştir.

Are Indices Good Estimators for the Stock Investors? Analysis of the Relationship Between BDI, VIX and GEPU Indices and Stock Exchanges: A Research on Stock Exchanges of Some Selected Developed Countries

In this study, the relationship between the Baltic Dry Index (BDI), Volatility Index (VIX) and Global Economic Policy Uncertainity Index (GEPU) with the developed world stock markets has been examined. The main purpose of the study is to analyze whether these indices are good predictors that can be used in stock investment timing. For this purpose, the BDI, VIX, GEPU index data for the 2012 July and 2021 May period and the data of the USA, GERMANY, UK, ITALY, FRANCE and CANADA stock markets are used. In the study, regression analysis and Granger causality test are applied. As a result of the analysis, it has been determined that the BDI, VIX and GEPU indices have a statistically significant effect on the stock indices in the sample and investors can make efficient timing in these stock markets by looking at these indices.

___

  • Andreou, E. and E. Ghysels (2021). Predicting the VIX and the volatility risk premium: The role of short-run funding spreads volatility factors. Journal of Econometrics, 220, 366–398.
  • Ang, A., Hodrick, R.J., Xing, Y., Zhang, X. (2006). The Cross-Section of Volatility and Expected Returns, The Journal of Finance, 61(1), pp.259-299.
  • Bekaert, G., Hoerova, M. (2014). The VIX, the variance premium and stock market volatility, Journal of Econometrics, 183 (2), pp. 181 -192.
  • Berkowitz, J.P., DeLisle, R.J. (2020). Practical Applications of Volatility as an Asset Class: Holding VIX in a Portfolio, Practical Applications, 7 (4), DOI: https://doi.org/10.3905/pa.7.4.367
  • Bildirici, M., Kayıkçı, F., Onat., I.Ş. (2016). BDI, Gold Price and Economic Growth, Procedia Economics and Finance, 38, pp.280-286. https://doi.org/10.1016/S2212-5671(16)30200-3
  • Carr, P., Wu, L. (2006). A Tale of Two Indices, The Journal of Derivatives, 13 (3), pp.13-29. https://doi.org/10.3905/jod.2006.616865
  • Liu, L., Zhang, T., 2015. Economic policy uncertainty and stock market volatility. Finance Res. Lett. 15, 99–105.
  • M. Chou, "A Fuzzy Time Series Model to Forecast the BDI," 2008 Fourth International Conference on Networked Computing and Advanced Information Management, 2008, pp. 50-53, doi: 10.1109/NCM.2008.94.
  • Ma, R., Zhou, C., Cai, H., Deng, C., 2019. The forecasting power of EPU for crude oil return volatility. Energy Rep. 5, 866–873. Ruan, Q., Jiang, W., Ma, G., 2016. Cross-correlations between price and volume in Chinese gold markets. Phys. A Stat. Mech. Its Appl. 451, 10–22.
  • Wang, G.J., Xie, C., Wen, D., Zhao, L., 2019. When Bitcoin meets economic policy uncertainty (EPU): measuring risk spillover effect from EPU to Bitcoin. Financ. Res. Lett. 31, 489–497.
  • Wang, J., X. Lu, F. He, and F. Ma, 2020, Which popular predictor is more useful to forecast international stock markets during the coronavirus pandemic: VIX vs EPU? International Review of Financial Analysis 72, 101596.
  • Whaley, R.E. (2009). Understanding the VIX, The Journal of Portfolio Management, 35 (3), pp. 98-105. DOI: 10.3905/JPM.2009.35.3.098
  • Yu, J., Shi, X., Guo, D., et al., 2020. Economic policy uncertainty (EPU) and firm carbon emissions: evidence using a China provincial EPU index[. J]. Energ. Econ. 94, 105071.
  • Zhang, S., Pei, L. (2017). Correlation Research of Shanghai Index and the BDI, Advances in Economics, Business and Management Research, volume 53, 7th International Conference on Education and Management (ICEM 2017) Copyright © 2018, the Authors. Published by Atlantis Press.
  • https://www.investopedia.com/terms/b/baltic_dry_index.asp (Accessed date: 23.09.2021)
  • https://www.balticexchange.com/en/data-services/market-information0/dry-services.html (Accessed date: 23.09.2021)
  • https://www.hurriyet.com.tr/ekonomi/vix-endeksi-nedir-41726408 (Accessed date: 23.09.2021)
  • https://www.policyuncertainty.com/methodology.html (Accessed date: 24.09.2021)
  • https://www.cboe.com/ (Accessed date: 24.09.2021)