Research Article
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Year 2017, , 417 - 424, 30.12.2017
https://doi.org/10.17261/Pressacademia.2017.751

Abstract

References

  • Ahmadi, M., Behmiri, N.B. & Manera, M. (2016). How is volatility in commodity markets linked to oil price shocks?. Energy Economics, vol. 59, pp. 11-23.
  • Bachmeier, L. (2008). Monetary policy and the transmission of oil shocks. Journal of Macroeconomics, vol. 30, pp. 1738-1755.
  • Bashar, O.H.M.N., Wadud, I.K.M.M. & Ahmed, H.J.A. (2013). Oil price uncertainty, monetary policy and the macroeconomy: The Canadian perspective. Economic Modelling, vol. 35, pp. 249-259.
  • Brahmasrene, T., Huang, J.C. & Sissoko, Y. (2014). Crude oil prices and exchange rates: Causality, variance decomposition and impulse response. Energy Economics, vol. 44, pp. 407-412.
  • De Truchis, G., Keddad, B. (2016). On the risk comovements between the crude oil market and U.S. dollar exchange rates. Economic Modelling, vol. 52, pp. 206-215.
  • Davidson, R., MacKinnon, J.G. (1993). Estimation and Inference in Econometrics. London. Oxford University Press. Granger, C.W.J. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, vol. 37, pp. 424438.
  • Hussain, M., Zebende, G.F., Bashir, U. & Donghong, D. (2017). Oil price and exchange rate co-movements in Asian countries: Detrended cross-correlation approach. Physica A, vol. 465, pp. 338-346.
  • Jawadi, F., Louhichi, W., Ameur, H.B. & Cheffou, A.I. (2016). On oil-US exchange rate volatility relationships: An intraday analysis. Economic Modelling, vol. 59, pp. 329-334.
  • JMulTi (Time Series Analysis with Java) Econometric Software Help System. Version 4.23.
  • Kanjilal, K., Ghosh, S. (2017). Dynamics of crude oil and gold price post 2008 global financial crisis – New evidence from threshold vector error-correction model. Resources Policy, vol. 52, pp. 358-365.
  • Kohlscheen, E. (2014). The impact of monetary policy on the exchange rate: A high frequency exchange rate puzzle in emerging economies. Journal of International Money and Finance, vol. 44, pp. 69-96.
  • Lütkepohl, H. (2007a). Vector Autoregressive and Vector Error Correction Models. In Lütkepohl, H., Kratzig., M. (Ed.). Applied Time Series Econometrics (pp. 86-158). Berlin. Springer.
  • Lütkepohl, H. (2007b). Univariate Time Series Analysis. In Lütkepohl, H., Kratzig., M. (Ed.). Applied Time Series Econometrics (pp. 8-85). Berlin. Springer.
  • Nazlioglu, S., Soytas, U. & Gupta, R. (2015). Oil prices and financial stress: A volatility spillover analysis. Energy Policy, vol. 82, pp. 278-288.
  • Pantula, S.G. (1989). Testing For Unit Roots in Time Series Data. Econometric Theory, vol. 5, pp. 256-271.
  • Sims. C.A. (1980). Macroeconomics and Reality. Econometrica, vol. 48, pp. 1-48.
  • Sun, X., Lu, X., Yue, G. & Li, J. (2017). Cross-correlations between the US monetary policy, US dollar index and crude oil market. Physica A, vol. 467, pp. 326-344.
  • Turhan, M.I., Sensoy, A. & Hacihasanoglu, E. (2014). A comparative analysis of the dynamic relationship between oil prices and exchange rates. Journal of International Financial Markets, Institutions & Money, vol. 32, pp. 397-414.

SHORT AND LONG-TERM CAUSALITY RELATIONS BETWEEN BROAD MONEY AND CRUDE OIL, EXCHANGE RATE, COMMODITY OPTION VOLATILITIES

Year 2017, , 417 - 424, 30.12.2017
https://doi.org/10.17261/Pressacademia.2017.751

Abstract

Purpose- The purpose of the study is to examine the dynamics linking
broad money (M3) growth and crude oil volatility, euro/dollar volatility,
commodity option volatility for the case of the US.

Methodology- Causality analysis depending on Vector Error
Correction (VEC) models is employed to estimate the relationship between broad
money (M3) growth and crude oil volatility, euro/dollar volatility, commodity
option volatility for the case of the US.

Findings- Causality analysis results stresses that the balance
sheet size of FED increase the uncertainties commodity and currency markets and
thus volatility in euro/dollar and spot oil price and commodity options can be
raised in the long-term. Both instantaneous causality and Granger causality
indicate that money demand behavior of US economic agents are not affected from
the commodity option, euro/dollar and crude oil volatilities both in short- and
long-run.  

Conclusion- Our empirical analysis implies that monetary aggregate
targeting policy of FED can not be negatively mitigated by commodity option
volatility, euro/dollar volatility, crude oil volatility indices. For further
studies and analysis, we suggest the clarification of channels between monetary
policy stance and financial instruments traded in commodity and currency
markets. 

References

  • Ahmadi, M., Behmiri, N.B. & Manera, M. (2016). How is volatility in commodity markets linked to oil price shocks?. Energy Economics, vol. 59, pp. 11-23.
  • Bachmeier, L. (2008). Monetary policy and the transmission of oil shocks. Journal of Macroeconomics, vol. 30, pp. 1738-1755.
  • Bashar, O.H.M.N., Wadud, I.K.M.M. & Ahmed, H.J.A. (2013). Oil price uncertainty, monetary policy and the macroeconomy: The Canadian perspective. Economic Modelling, vol. 35, pp. 249-259.
  • Brahmasrene, T., Huang, J.C. & Sissoko, Y. (2014). Crude oil prices and exchange rates: Causality, variance decomposition and impulse response. Energy Economics, vol. 44, pp. 407-412.
  • De Truchis, G., Keddad, B. (2016). On the risk comovements between the crude oil market and U.S. dollar exchange rates. Economic Modelling, vol. 52, pp. 206-215.
  • Davidson, R., MacKinnon, J.G. (1993). Estimation and Inference in Econometrics. London. Oxford University Press. Granger, C.W.J. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, vol. 37, pp. 424438.
  • Hussain, M., Zebende, G.F., Bashir, U. & Donghong, D. (2017). Oil price and exchange rate co-movements in Asian countries: Detrended cross-correlation approach. Physica A, vol. 465, pp. 338-346.
  • Jawadi, F., Louhichi, W., Ameur, H.B. & Cheffou, A.I. (2016). On oil-US exchange rate volatility relationships: An intraday analysis. Economic Modelling, vol. 59, pp. 329-334.
  • JMulTi (Time Series Analysis with Java) Econometric Software Help System. Version 4.23.
  • Kanjilal, K., Ghosh, S. (2017). Dynamics of crude oil and gold price post 2008 global financial crisis – New evidence from threshold vector error-correction model. Resources Policy, vol. 52, pp. 358-365.
  • Kohlscheen, E. (2014). The impact of monetary policy on the exchange rate: A high frequency exchange rate puzzle in emerging economies. Journal of International Money and Finance, vol. 44, pp. 69-96.
  • Lütkepohl, H. (2007a). Vector Autoregressive and Vector Error Correction Models. In Lütkepohl, H., Kratzig., M. (Ed.). Applied Time Series Econometrics (pp. 86-158). Berlin. Springer.
  • Lütkepohl, H. (2007b). Univariate Time Series Analysis. In Lütkepohl, H., Kratzig., M. (Ed.). Applied Time Series Econometrics (pp. 8-85). Berlin. Springer.
  • Nazlioglu, S., Soytas, U. & Gupta, R. (2015). Oil prices and financial stress: A volatility spillover analysis. Energy Policy, vol. 82, pp. 278-288.
  • Pantula, S.G. (1989). Testing For Unit Roots in Time Series Data. Econometric Theory, vol. 5, pp. 256-271.
  • Sims. C.A. (1980). Macroeconomics and Reality. Econometrica, vol. 48, pp. 1-48.
  • Sun, X., Lu, X., Yue, G. & Li, J. (2017). Cross-correlations between the US monetary policy, US dollar index and crude oil market. Physica A, vol. 467, pp. 326-344.
  • Turhan, M.I., Sensoy, A. & Hacihasanoglu, E. (2014). A comparative analysis of the dynamic relationship between oil prices and exchange rates. Journal of International Financial Markets, Institutions & Money, vol. 32, pp. 397-414.
There are 18 citations in total.

Details

Primary Language English
Journal Section Articles
Authors

Kaya Tokmakcioglu

Oguzhan Ozcelebi

Publication Date December 30, 2017
Published in Issue Year 2017

Cite

APA Tokmakcioglu, K., & Ozcelebi, O. (2017). SHORT AND LONG-TERM CAUSALITY RELATIONS BETWEEN BROAD MONEY AND CRUDE OIL, EXCHANGE RATE, COMMODITY OPTION VOLATILITIES. Journal of Economics Finance and Accounting, 4(4), 417-424. https://doi.org/10.17261/Pressacademia.2017.751

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