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Seçili Küresel Hisse Senedi Piyasaları ile Altın ve Gümüş Vadeli İşlemleri Arasındaki Bağımlılık Üzerine Bir Araştırma

Yıl 2025, , 50 - 64, 21.01.2025

Ozan Kaymak

https://doi.org/10.37880/cumuiibf.1516047

Öz

Küreselleşme, ekonomik ve ticari pratiklerin dünya genelinde daha yüksek hacim ve frekansta uygulanabilmesine olanak tanımıştır. Bunun sonucunda sermaye yayılımlarının etki alanlarının genişlemesiyle, finansal piyasaların karşılıklı bağımlılıklarının arttığı söylenebilir. Ancak ekonomik krizler, salgın hastalıklar, savaşlar ve kontrolsüz göçler gibi olumsuz gelişmeler, piyasalar arasındaki ilişkilerin zayıflamasına ve anlamlı sayıda yatırımcının emtia yatırımlarına yönelmesine yol açmaktadır. Bu çalışmada; Sermaye Varlıkları Fiyatlandırma Modeli (CAPM), sistematik ve sistematik olmayan riskler karşısında seçilen finansal varlıkların beklenen getirilerinin değişeceği teoreminin seçilen piyasa verilerinin ilgili dönemde geçerli olup olmadığı araştırılmıştır. Çalışmanın amacı, altın ve gümüş vadeli işlem getirileri arasındaki olası eşbütünleşmeyi ve bunların seçilmiş küresel hisse senedi piyasaları getirileri üzerindeki etkisini zaman serisi analizleri ile incelemektir. Bu çalışmanın amacı; seçili küresel hisse senedi piyasaları ile altın ve gümüş vadeli işlemleri arasındaki muhtemel eşbütünleşme ilişkisinin zaman serisi analizleri ile incelenmesidir. 2014 Ocak ile 2024 Mayıs döneminde, seçili küresel hisse senedi endekslerinin aylık getirileri ile altın ve gümüş vadeli işlemleri aylık endeks getirileri arasındaki muhtemel ilişkiler Gecikmesi Dağıtılmış Otoregresif Sınır Testi (ARDL) Yöntemine göre incelenmiştir. Hata düzeltme katsayılarının hesaplanmasıyla, hisse senedi piyasaları ile emtia piyasaları arasındaki dengenin bozulması durumunda, dengenin ne kadarlık bir sürede yeniden sağlanabildiği tespit edilmiştir. Araştırmanın sonucunda altın ve gümüş vadeli işlemleri endeks getirileri ile seçili küresel hisse senedi endeks getirileri arasında uzun dönemli eşbütünleşme ilişkisinin var olduğu tespit edilmiştir. Seçili küresel endekslere ait getiriler ile altın ve gümüş vadeli işlemleri endeks getirileri arasındaki ilişkide kısa dönemde dengenin bozulması durumunda, altın vadeli işlemleri endeks getirileri için 0.9042 ay, gümüş vadeli işlemleri endeks getirileri için ise 0.6549 içinde dengenin yeniden sağlandığı tespit edilmiştir.

Anahtar Kelimeler

Küresel Hisse Senedi Piyasaları Altın ve Gümüş Vadeli İşlemleri ARDL Sınır Testi

Kaynakça

  • Andrés Fernández, A. G. (2018). Sharing a Ride on the Commodities Roller Coaster: Common Factors in Business Cycles of Emerging Economies. Journal of International Economics, 111(1), 99-121. doi:https://doi.org/10.1016/j.jinteco.2017.11.008
  • Arhan Sheth, T. S. (2022). Global Economic Impact in Stock and Commodity Markets during Covid-19 Pandemic. Annals of Data Science, 9(5), 889-907. doi:10.1007/s40745-022-00403-x
  • Aviral Kumar Tiwari, E. J. (2022). Time-Varying Dependence Dynamics between International Commodity Prices and Australian Industry Stock Returns: a Perspective for Portfolio Diversification. Energy Economics, 108(1), 105891. doi:https://doi.org/10.1016/j.eneco.2022.105891
  • Blanchard, O. J. (1981). Output, The Stock Market, and Interest Rates. The American Economic Review,, 71(1), 132-143. Retrieved from https://www.jstor.org/stable/1805045
  • Breusch, T. (1978). Testing for Autocorrelation in Dynamic Linear Models. Australian Economic Papers, 17(31), 334-355. doi:https://doi.org/10.1111/j.1467-8454.1978.tb00635.x
  • Byrne, B. M. (2010). Structural Equation Modeling With AMOS. New York: Routledge.
  • Carlos M. Jarque, A. K. (1987). A Test for Normality of Observations and Regression Residuals. International Statistical Review, 55(2), 163-172. doi:https://doi.org/10.2307/1403192
  • Carmen M. Reinhart, V. R. (2016). Global Cycles: Capital Flows, Commodities, and Sovereign Defaults, 1815-2015. American Economic Review, 106(5), 574-580. doi:10.1257/aer.p20161014
  • Chung Yan Sam, R. M. (2019). An Augmented Autoregressive Distributed Lag Bounds Test for Cointegration. Economic Modelling, 80(1), 130-141. doi:https://doi.org/10.1016/j.econmod.2018.11.001
  • D. Kwiatkowski, & P. C. B. Phillips, P. S. (1992). Testing the Null Hypothesis of Stationarity against the Alternative of a Unit Root. Journal of Econometrics, 54(1), 1-3. doi: doi:10.1016/0304-4076(92)90104-Y
  • Darmansyah, R. T. (2019). The Effect of the Returns of Global Stock Indexes and Global Commodıtıes Toward IHSG Returns Perıod 2009-2018. International Journal of Business and Economy, 1(2), 31-41. Retrieved from https://myjms.mohe.gov.my/index.php/ijbec/article/view/7023
  • David A. Dickey, W. A. (1979). Distribution of the Estimators for Autoregressive Time Series With a Unit Root. Journal of the American Statistical Association, 74(1), 427-431. doi:10.2307/2286348
  • Geetesh Bhardwaj, A. D. (2013). The Business Cycle and the Correlation between Stocks and Commodities. Journal of Investment Consulting, 14(2), 14-25. Retrieved from https://ssrn.com/abstract=2371355
  • Godfrey, L. (1978). Testing against General Autoregressive and Moving Average Error Models When the Regressors Include Lagged Dependent Variables. Econometrica, 46(6), 1293-1301. doi:https://doi.org/10.2307/1913829
  • Hector O. Zapata, J. E. (2023). A Cyclical Phenomenon among Stock & Commodity Markets. Journal of Risk and Financial Management, 16(7), 320-336. doi:https://doi.org/10.3390/jrfm16070320
  • Ihsan Badshah, S. B. (2018). Asymmetric Linkages Among the Fear Index and Emerging Market Volatility Indices. Emerging Markets Review, 37(1), 17-31. doi:https://doi.org/10.1016/j.ememar.2018.03.002
  • J. Scott Davis, G. V. (2021). Global Drivers of Gross and Net Capital Flows. Journal of International Economics, 128(1), 103397. doi:https://doi.org/10.1016/j.jinteco.2020.103397
  • Jaffe, J. F. (1989). Gold and Gold Stocks as Investments for Institutional Portfolios. Financial Analysts Journal, 45(2), 53-59. doi:https://doi.org/10.2469/faj.v45.n2.53
  • Jozef Baruník, E. K. (2016). Gold, oil, and stocks: Dynamic correlations. International Review of Economics & Finance, 42(1), 186-201. doi:https://doi.org/10.1016/j.iref.2015.08.006
  • M. Hashem Pesaran, Y. S. (2001). Bounds Testing Approaches to the Analysis of Level Relationships. Journal of Applied Econometrics, 16(1), 289-326. doi:https://doi.org/10.1002/jae.616
  • Manas Paul, N. B. (2023). On the Similarities between Precious Metals, Precious Metal Stocks and Equities – International Evidence for Gold and Silver. Resources Policy, 83(1), 103629. doi:https://doi.org/10.1016/j.resourpol.2023.103629
  • Martin Enilov, G. F. (2021). Global connectivity between commodity prices and national stock markets: A time-varying MIDAS analysis. International Journal of Finance & Economics, 28(3), 2607-2619. doi:https://doi.org/10.1002/ijfe.2552
  • Mohamed El Hedi Arouri, A. L. (2015). World Gold Prices and Stock Returns in China: Insights for Hedging and Diversification Strategies. Economic Modelling, 44(1), 173-282. doi:https://doi.org/10.1016/j.econmod.2014.10.030
  • Moshirian, F. (2011). The Global Financial Crisis and the Evolution of Markets, Institutions and Regulation. Journal of Banking & Finance, 35(3), 502-511. doi:https://doi.org/10.1016/j.jbankfin.2010.08.01
  • Muneer Shaik, S. A. (2023). Impact of Geo-Political Risk on Stocks, Oil, and Gold Returns during GFC, COVID-19, and Russian – Ukraine War. Cogent Economics & Finance, 11(1), 2190213. doi:https://doi.org/10.1080/23322039.2023.2190213
  • Narayan, P. K. (2005). The Saving and Investment Nexus for China: Evidence from Cointegration Tests. Applied Economics, 37(17), 1979-1990. doi:10.1080/00036840500278103
  • Page, E. S. (1954). Continuous Inspection Schemes. Biometrika, 41(1), 100-115. doi:10.1093/biomet/41.1-2.100
  • Peter C. B. Phillips, P. P. (1988). Testing for a Unit Root in Time Series Regression. Biometrika, 75(2), 335-346. doi:https://doi.org/10.1093/biomet/75.2.335
  • Ramsey, J. B. (1969). Tests for Specification Errors in Classical Linear Least-Squares Regression Analysis. Journal of the Royal Statistical Society. Series B (Methodological), 31(2), 350-371. Retrieved from https://www.jstor.org/stable/2984219
  • Rida Waheed, S. S. (2020). The Impact of COVID-19 on Karachi Stock Exchange: Quantile-on-Quantile Approach Using Secondary and Predicted Data. Jounal of Puplic Affairs, 20(2), 1-6. doi:https://doi.org/10.1002/pa.2290
  • Rong-Gang Cong, Y.-M. W.-L. (2008). Relationships between Oil Price Shocks and Stock Market: An Empirical Analysis from China. Energy Policy, 36(9), 3544-3553. doi:https://doi.org/10.1016/j.enpol.2008.06.006
  • Safika Praveen Sheikh, S. A. (2023). Do Implied Volatilities of Stock and Commodity Markets Affect Conventional & Shariah Indices Differently? An Evidence by OVX, GVZ and VIX. Heliyon, 9(11), 21094. doi:https://doi.org/10.1016/j.heliyon.2023.e21094
  • Sajid Ali, E. B. (2020). Revisiting the Valuable Roles of Commodities for International Stock Markets. Resources Policy, 101603. doi:https://doi.org/10.1016/j.resourpol.2020.101603
  • Silvia Miranda-Agrippino, H. R. (2022). Chapter 1 - The Global Financial Cycle. In E. H. Gita Gopinath, Handbook of International Economics (pp. 1-43). Elsevier. doi:https://doi.org/10.1016/bs.hesint.2022.02.008
  • Sims, C. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1-48. doi:https://doi.org/10.2307/1912017
  • Taufiq Choudhry, F. I. (2016). Stock Market Volatility and Business Cycle: Evidence from Linear and Nonlinear Causality Tests. Journal of Banking & Finance, 66(1), 89-101. doi:https://doi.org/10.1016/j.jbankfin.2016.02.005
  • Trevor Breusch, A. R. (1979). A Simple Test for Heteroskedasticity and Random Coefficient Variation. Econometrica, 47(5), 1287-1294. doi:10.2307/1911963
  • Wensheng Kang, R. A. (2020). Global Commodity Prices and Global Stock Market Volatility Shocks: Effects Across Countries. Journal of Asian Economics, 71(1), 101249. doi:https://doi.org/10.1016/j.asieco.2020.101249
  • Wensheng Kang, R. A. (2020). Global Commodity Prices and Global Stock Volatility Shocks: Effects Across Countries. Journal of Asian Economics, 71(1), 101249. doi:https://doi.org/10.1016/j.asieco.2020.101249
  • Xinhong Lu, K. M. (2008). 2008. Economics Letters, 100(2), 234-237. doi:https://doi.org/10.1016/j.econlet.2008.01.018
  • Yanan Chen, H. Q. (2024). Dynamic Interplay between Chinese Energy, Renewable Energy Stocks, and Commodity Markets: Time-Frequency Causality Study. Renewable Energy, 228(1), 120578. doi:https://doi.org/10.1016/j.renene.2024.120578

A Study on the Dependency Between Selected Global Stock Markets and Gold and Silver Futures

Yıl 2025, , 50 - 64, 21.01.2025

Ozan Kaymak

https://doi.org/10.37880/cumuiibf.1516047

Öz

Globalization has enabled greater volume and frequency of economic and commercial practices to be implemented worldwide. As a result, with the expansion of the scope of capital expansion, the interdependence of financial markets increases. However, negative developments such as economic crises, epidemics, wars, and uncontrolled migrations cause the relations between markets to weaken and a significant number of investors to turn to commodity investments. This study aims to evaluate the validity of the Capital Asset Pricing Model (CAPM) theorem, which posits that the expected returns of financial assets are influenced by systematic and unsystematic risks within the context of the selected market data for the specified period. Specifically, the study seeks to analyze the potential cointegration and the effects of gold and silver futures returns on the returns of selected global stock markets using time-series analysis. The potential relationships between the monthly returns of selected global stock indices and the monthly returns of gold and silver futures were analyzed for the period from January 2014 to May 2024 using the Autoregressive Distributed Lag (ARDL) Bound Test method. By calculating the error correction coefficients, it has been determined how long it takes to restore the balance in case the balance between the stock markets and commodity markets is disrupted. As a result of the research, it was determined that there is a long-term cointegration relationship between gold and silver futures index returns and selected global stock index returns. In the case of a short-term imbalance in the relationship between the yields of selected global indices and the index returns of gold and silver-term transactions, the balance was recovered within 0.9042 months for the index return of gold-term operations and 0.6549 months for the index return of silver-term operations.

Anahtar Kelimeler

Global Stock Markets Gold and Silver Futures ARDL Bond Test

Kaynakça

  • Andrés Fernández, A. G. (2018). Sharing a Ride on the Commodities Roller Coaster: Common Factors in Business Cycles of Emerging Economies. Journal of International Economics, 111(1), 99-121. doi:https://doi.org/10.1016/j.jinteco.2017.11.008
  • Arhan Sheth, T. S. (2022). Global Economic Impact in Stock and Commodity Markets during Covid-19 Pandemic. Annals of Data Science, 9(5), 889-907. doi:10.1007/s40745-022-00403-x
  • Aviral Kumar Tiwari, E. J. (2022). Time-Varying Dependence Dynamics between International Commodity Prices and Australian Industry Stock Returns: a Perspective for Portfolio Diversification. Energy Economics, 108(1), 105891. doi:https://doi.org/10.1016/j.eneco.2022.105891
  • Blanchard, O. J. (1981). Output, The Stock Market, and Interest Rates. The American Economic Review,, 71(1), 132-143. Retrieved from https://www.jstor.org/stable/1805045
  • Breusch, T. (1978). Testing for Autocorrelation in Dynamic Linear Models. Australian Economic Papers, 17(31), 334-355. doi:https://doi.org/10.1111/j.1467-8454.1978.tb00635.x
  • Byrne, B. M. (2010). Structural Equation Modeling With AMOS. New York: Routledge.
  • Carlos M. Jarque, A. K. (1987). A Test for Normality of Observations and Regression Residuals. International Statistical Review, 55(2), 163-172. doi:https://doi.org/10.2307/1403192
  • Carmen M. Reinhart, V. R. (2016). Global Cycles: Capital Flows, Commodities, and Sovereign Defaults, 1815-2015. American Economic Review, 106(5), 574-580. doi:10.1257/aer.p20161014
  • Chung Yan Sam, R. M. (2019). An Augmented Autoregressive Distributed Lag Bounds Test for Cointegration. Economic Modelling, 80(1), 130-141. doi:https://doi.org/10.1016/j.econmod.2018.11.001
  • D. Kwiatkowski, & P. C. B. Phillips, P. S. (1992). Testing the Null Hypothesis of Stationarity against the Alternative of a Unit Root. Journal of Econometrics, 54(1), 1-3. doi: doi:10.1016/0304-4076(92)90104-Y
  • Darmansyah, R. T. (2019). The Effect of the Returns of Global Stock Indexes and Global Commodıtıes Toward IHSG Returns Perıod 2009-2018. International Journal of Business and Economy, 1(2), 31-41. Retrieved from https://myjms.mohe.gov.my/index.php/ijbec/article/view/7023
  • David A. Dickey, W. A. (1979). Distribution of the Estimators for Autoregressive Time Series With a Unit Root. Journal of the American Statistical Association, 74(1), 427-431. doi:10.2307/2286348
  • Geetesh Bhardwaj, A. D. (2013). The Business Cycle and the Correlation between Stocks and Commodities. Journal of Investment Consulting, 14(2), 14-25. Retrieved from https://ssrn.com/abstract=2371355
  • Godfrey, L. (1978). Testing against General Autoregressive and Moving Average Error Models When the Regressors Include Lagged Dependent Variables. Econometrica, 46(6), 1293-1301. doi:https://doi.org/10.2307/1913829
  • Hector O. Zapata, J. E. (2023). A Cyclical Phenomenon among Stock & Commodity Markets. Journal of Risk and Financial Management, 16(7), 320-336. doi:https://doi.org/10.3390/jrfm16070320
  • Ihsan Badshah, S. B. (2018). Asymmetric Linkages Among the Fear Index and Emerging Market Volatility Indices. Emerging Markets Review, 37(1), 17-31. doi:https://doi.org/10.1016/j.ememar.2018.03.002
  • J. Scott Davis, G. V. (2021). Global Drivers of Gross and Net Capital Flows. Journal of International Economics, 128(1), 103397. doi:https://doi.org/10.1016/j.jinteco.2020.103397
  • Jaffe, J. F. (1989). Gold and Gold Stocks as Investments for Institutional Portfolios. Financial Analysts Journal, 45(2), 53-59. doi:https://doi.org/10.2469/faj.v45.n2.53
  • Jozef Baruník, E. K. (2016). Gold, oil, and stocks: Dynamic correlations. International Review of Economics & Finance, 42(1), 186-201. doi:https://doi.org/10.1016/j.iref.2015.08.006
  • M. Hashem Pesaran, Y. S. (2001). Bounds Testing Approaches to the Analysis of Level Relationships. Journal of Applied Econometrics, 16(1), 289-326. doi:https://doi.org/10.1002/jae.616
  • Manas Paul, N. B. (2023). On the Similarities between Precious Metals, Precious Metal Stocks and Equities – International Evidence for Gold and Silver. Resources Policy, 83(1), 103629. doi:https://doi.org/10.1016/j.resourpol.2023.103629
  • Martin Enilov, G. F. (2021). Global connectivity between commodity prices and national stock markets: A time-varying MIDAS analysis. International Journal of Finance & Economics, 28(3), 2607-2619. doi:https://doi.org/10.1002/ijfe.2552
  • Mohamed El Hedi Arouri, A. L. (2015). World Gold Prices and Stock Returns in China: Insights for Hedging and Diversification Strategies. Economic Modelling, 44(1), 173-282. doi:https://doi.org/10.1016/j.econmod.2014.10.030
  • Moshirian, F. (2011). The Global Financial Crisis and the Evolution of Markets, Institutions and Regulation. Journal of Banking & Finance, 35(3), 502-511. doi:https://doi.org/10.1016/j.jbankfin.2010.08.01
  • Muneer Shaik, S. A. (2023). Impact of Geo-Political Risk on Stocks, Oil, and Gold Returns during GFC, COVID-19, and Russian – Ukraine War. Cogent Economics & Finance, 11(1), 2190213. doi:https://doi.org/10.1080/23322039.2023.2190213
  • Narayan, P. K. (2005). The Saving and Investment Nexus for China: Evidence from Cointegration Tests. Applied Economics, 37(17), 1979-1990. doi:10.1080/00036840500278103
  • Page, E. S. (1954). Continuous Inspection Schemes. Biometrika, 41(1), 100-115. doi:10.1093/biomet/41.1-2.100
  • Peter C. B. Phillips, P. P. (1988). Testing for a Unit Root in Time Series Regression. Biometrika, 75(2), 335-346. doi:https://doi.org/10.1093/biomet/75.2.335
  • Ramsey, J. B. (1969). Tests for Specification Errors in Classical Linear Least-Squares Regression Analysis. Journal of the Royal Statistical Society. Series B (Methodological), 31(2), 350-371. Retrieved from https://www.jstor.org/stable/2984219
  • Rida Waheed, S. S. (2020). The Impact of COVID-19 on Karachi Stock Exchange: Quantile-on-Quantile Approach Using Secondary and Predicted Data. Jounal of Puplic Affairs, 20(2), 1-6. doi:https://doi.org/10.1002/pa.2290
  • Rong-Gang Cong, Y.-M. W.-L. (2008). Relationships between Oil Price Shocks and Stock Market: An Empirical Analysis from China. Energy Policy, 36(9), 3544-3553. doi:https://doi.org/10.1016/j.enpol.2008.06.006
  • Safika Praveen Sheikh, S. A. (2023). Do Implied Volatilities of Stock and Commodity Markets Affect Conventional & Shariah Indices Differently? An Evidence by OVX, GVZ and VIX. Heliyon, 9(11), 21094. doi:https://doi.org/10.1016/j.heliyon.2023.e21094
  • Sajid Ali, E. B. (2020). Revisiting the Valuable Roles of Commodities for International Stock Markets. Resources Policy, 101603. doi:https://doi.org/10.1016/j.resourpol.2020.101603
  • Silvia Miranda-Agrippino, H. R. (2022). Chapter 1 - The Global Financial Cycle. In E. H. Gita Gopinath, Handbook of International Economics (pp. 1-43). Elsevier. doi:https://doi.org/10.1016/bs.hesint.2022.02.008
  • Sims, C. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1-48. doi:https://doi.org/10.2307/1912017
  • Taufiq Choudhry, F. I. (2016). Stock Market Volatility and Business Cycle: Evidence from Linear and Nonlinear Causality Tests. Journal of Banking & Finance, 66(1), 89-101. doi:https://doi.org/10.1016/j.jbankfin.2016.02.005
  • Trevor Breusch, A. R. (1979). A Simple Test for Heteroskedasticity and Random Coefficient Variation. Econometrica, 47(5), 1287-1294. doi:10.2307/1911963
  • Wensheng Kang, R. A. (2020). Global Commodity Prices and Global Stock Market Volatility Shocks: Effects Across Countries. Journal of Asian Economics, 71(1), 101249. doi:https://doi.org/10.1016/j.asieco.2020.101249
  • Wensheng Kang, R. A. (2020). Global Commodity Prices and Global Stock Volatility Shocks: Effects Across Countries. Journal of Asian Economics, 71(1), 101249. doi:https://doi.org/10.1016/j.asieco.2020.101249
  • Xinhong Lu, K. M. (2008). 2008. Economics Letters, 100(2), 234-237. doi:https://doi.org/10.1016/j.econlet.2008.01.018
  • Yanan Chen, H. Q. (2024). Dynamic Interplay between Chinese Energy, Renewable Energy Stocks, and Commodity Markets: Time-Frequency Causality Study. Renewable Energy, 228(1), 120578. doi:https://doi.org/10.1016/j.renene.2024.120578
Toplam 41 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Finans, Finans ve Yatırım (Diğer)
Bölüm Makaleler
Yazarlar

Ozan Kaymak 0000-0001-5492-2877

Erken Görünüm Tarihi 19 Ocak 2025
Yayımlanma Tarihi 21 Ocak 2025
Gönderilme Tarihi 14 Temmuz 2024
Kabul Tarihi 28 Ekim 2024
Yayımlandığı Sayı Yıl 2025

Kaynak Göster

APA Kaymak, O. (2025). A Study on the Dependency Between Selected Global Stock Markets and Gold and Silver Futures. Cumhuriyet Üniversitesi İktisadi Ve İdari Bilimler Dergisi, 26(1), 50-64. https://doi.org/10.37880/cumuiibf.1516047

Cumhuriyet Üniversitesi İktisadi ve İdari Bilimler Dergisi Creative Commons Atıf-GayriTicari 4.0 Uluslararası Lisansı (CC BY NC) ile lisanslanmıştır.