Skip to main content
  • 627 Accesses

Abstract

The explicit linkage between spot and futures prices is highlighted in financial theory by both non-arbitrage and asset pricing theory. Many studies have considered the relationship between the spot and futures prices of the crude oil market; however, most of these works used traditional methods such as cointegration or the Granger test . The generalized autoregressive conditional heteroskedasticity, linear vector error correlation, and nonlinear threshold vector error correlation models are also employed to investigate the relationship between oil spot and futures markets.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 139.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 139.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • E. Alberola, J. Chevallier, B. Chèze, Price drivers and structural breaks in European carbon price 2005–2007. Energy Policy 36(2), 787–797 (2008)

    Google Scholar 

  • E. Alberola, J. Chevallier, B. Cheze, Emissions compliances and carbon prices under the EU ETS: a country specific analysis of industrial sectors. J. Policy Model. 31, 446–462 (2009)

    Google Scholar 

  • A. Boersen, B. Scholtens, The relationship between European electricity markets and emission allowance futures prices in phase II of the EU (European Union) emission trading scheme. Phys. A 74(1), 585–594 (2014)

    Google Scholar 

  • D.W. Bunn, C. Fezzi, Interaction of European carbon trading and energy prices (Social Science Electronic Publishing, 2007)

    Google Scholar 

  • G.X. Cao, J. Cao, L.B. Xu, L.Y. He, Multifractal detrended cross-correlation between the Chinese domestic and international gold markets based on DCCA and DMCA methods. Modern Phys. Lett. B 28(11), 243 (2014)

    Google Scholar 

  • J. Chevallier, Carbon futures and macroeconomic risk factors: a view from the EU ETS. Energy Econ. 31(4), 614–625 (2009)

    Article  Google Scholar 

  • F.J. Convery, L. Redmond, Market and price developments in the European Union emissionstrading scheme. Rev. Environ. Econ. Policy 1(1), 88–111 (2007)

    Article  Google Scholar 

  • S.J. Devlin, R. Gnanadesikan, J.R. Kettenring, Robust estimation and outlier detection with correlation coefficients. Biometrika 62(3), 531–545 (1975)

    Google Scholar 

  • R.F. Engle, C.W. Granger, Co-integration and error correction: representation, estimation, and testing. Econometrica 55(2), 251–276 (1987)

    Google Scholar 

  • C.W.J. Granger, Econometrica 37, 424–438 (1969)

    Article  Google Scholar 

  • S. Johansen, Statistical analysis of cointegration vectors. J. Econ. Dyn. Control 12(2), 231–254 (1988)

    Article  Google Scholar 

  • J.L. Kanen, Carbon trading and pricing (Environmental Finance Publications, London, 2006)

    Google Scholar 

  • L. Kristoufek, Measuring correlations between non-stationary series with DCCA coefficient. Phys. A 402, 291–298 (2014)

    Article  Google Scholar 

  • M. Mansanet-Bataller, A. Pardo, E. Valor, CO2 prices, energy and weather. Energy J. 28(3), 67–86 (2007)

    Article  Google Scholar 

  • M. Nicolau, Do spot prices move towards futures prices? A study on crude oil market. Acta Univ. Danub. Oecon. 8(5), 166–176 (2012)

    Google Scholar 

  • T. Ochiai, J.C. Nacher, Volatility-constrained correlation identifies the directionality of the influence between Japan’s Nikkei225 and other financial markets. Phys. A 393(1), 364–375 (2014)

    Article  Google Scholar 

  • B. Podobnik, Z.Q. Jiang, W.X. Zhou, H.E. Stanley, Statistical tests for power-law cross-correlated processes. Phys. Rev. E: Stat. Nonlin. Soft Matter Phys. 84(6 Pt 2), 066118 (2011)

    Article  Google Scholar 

  • B. Podobnik, H.E. Stanley, Detrended cross-correlation analysis: a new method for analyzing two nonstationary time series. Phys. Rev. Lett. 100(8), 084102 (2008)

    Google Scholar 

  • X. San Liang, Unraveling the cause-effect relation between time series, Phys. Rev. E 90(5), 052150 (2014)

    Google Scholar 

  • Y.D. Wang, C.F. Wu, Prevention of infant and childhood injury through an active pediatrician participated model, in APHA Meeting and Exposition (2013)

    Google Scholar 

  • Y.D. Wang, Y. Wei, C.F. Wu, Stock market network’s topological stability: evidence from planar maximally filtered graph and minimal spanning tree. Int. J. Mod. Phys. B 29(22), 1550161 (2015)

    Article  Google Scholar 

  • R.R. Wilcox, Robust regression (Chapter 10), in Introduction to Robust Estimation & Hypothesis Testing, vol. 18, 3rd edn (18) (2012), pp. 471–532

    Google Scholar 

  • G.F. Zebende, DCCA cross-correlation coefficient: quantifying level of cross-correlation. Phys. A Stat. Mech. Its Appl. 390(4), 614–618 (2011)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Guangxi Cao .

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Cao, G., He, LY., Cao, J. (2018). Asymmetric DCCA Cross-Correlation Coefficient. In: Multifractal Detrended Analysis Method and Its Application in Financial Markets. Springer, Singapore. https://doi.org/10.1007/978-981-10-7916-0_7

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-7916-0_7

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-7915-3

  • Online ISBN: 978-981-10-7916-0

  • eBook Packages: Economics and FinanceEconomics and Finance (R0)

Publish with us

Policies and ethics