Skip to main content

Ambit Processes, Their Volatility Determination and Their Applications

  • Chapter
  • First Online:
Modern Stochastics and Applications

Part of the book series: Springer Optimization and Its Applications ((SOIA,volume 90))

  • 2431 Accesses

Abstract

In this chapter we try to review the research done so far about ambit processes and their applications. The notion of ambit process was introduced by Barndorff-Nielsen and Schmiegel in 2007. Since then, many papers have been written studying their properties and applying them to model different natural or economic phenomena. As it is shown in the paper, these processes share their mathematical structure with the solutions of random evolution equations allowing them great flexibility for modelling. The goal of this paper is fourfold: to show the main characteristics of these processes; how to determine their main structural component: their volatility; how they can be used for modelling different random phenomena like turbulence or financial prices; and last but not least the mathematics behind.

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 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
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

  1. Audet, N., Heiskanen, P., Keppo, J., Vehviläinen, I.: Modelling electricity forward curve a dynamics in the Nordic Market. In: Bunn, D.W. (eds.) Modelling Prices in Competitive Electricity Markets, pp. 251–265. Wiley, Chichester (2004)

    Google Scholar 

  2. Backus, D.K., Zin S.E.: Long-memory inflation uncertainty: evidence from the term structure of interest rates. J. Money Credit Bank 25, 681–700 (1995)

    Article  Google Scholar 

  3. Barndorff-Nielsen, O.E., Corcuera, J.M., Podolskij, M.: Power variation for Gaussian processes with stationary increments. Stoch. Proc. Appl. 119, 1845–1865 (2009)

    Article  MATH  MathSciNet  Google Scholar 

  4. Barndorff-Nielsen, O.E., Corcuera, J.M., Podolskij, M., Woerner, J.H.C.: Bipower variation for Gaussian processes with stationary increments. J. Appl. Probab 46, 132–150 (2009)

    Article  MATH  MathSciNet  Google Scholar 

  5. Barndorff-Nielsen, O.E., Benth, F.E., Veraart, A.: Modelling Energy Spot Prices by Lévy Semistationary Processes (2010) Available at http://ssrn.com/abstract=1597700

  6. Barndorff-Nielsen, O.E., Benth, F.E., Veraart, A.: Ambit Processes and Stochastic Partial Differential Equation (2011) Available at http://ssrn.com/abstract=1597697

  7. Barndorff-Nielsen, O.E., Benth, F.E., Veraart, A.: Modelling electricity forward markets by ambit fields (2011) Available at http://ssrn.com/abstract=1938704

  8. Barndorff-Nielsen, O.E., Corcuera J.M. and Podolskij M.: Multipower variation for Brownian semistationary processes. Bernoulli 17(4), 1159–1194 (2011)

    Article  MATH  MathSciNet  Google Scholar 

  9. Barndorff-Nielsen, O.E., Benth, F.E., Veraart, A.: Recent Advances in Ambit Stochastics with a View Towards Tempo-Spatial Stocastic Volatility/Intermittency (2013). Available at arXiv: 1210.1354v1

    Google Scholar 

  10. Barndorff-Nielsen, O.E., Corcuera, J.M. and Podolskij, M.: Limit theorems for functionals of higher order differences of Brownian semi-stationary processes. In: Shiryaev, A., Varadhan, N., Presman, S.R.S., Ernst L. (eds.) Prokhorov and Contemporary Probability Theory, pp 69–96. Springer, Berlin (2013)

    Chapter  Google Scholar 

  11. Barndorff-Nielsen, O.E. Graversen, S.E.: Volatility determination in an ambit process setting. J Appl. Probab. 48(A), 263–275 (2011)

    Google Scholar 

  12. Barndorff-Nielsen, O.E., Schmiegel, J.: Ambit processes with applications to turbulence and cancer growth. In: Benth, F.E., Nunno, G.D., Linstrøm, T., Øksendal, B., Zhang, T. (eds.) Stochastic Analysis and Applications: The Abel Symposium 2005, pp. 93–124. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  13. Barndorff-Nielsen, O.E. Schmiegel, J.: Brownian semistationary processes and volatility/intermittency. In: Albrecher, H., Runggaldier, W., Schachermayer, W. (eds.) Advanced Financial Modelling, volume 8 of Radon Series on Computational and Applied Mathematics, pp. 1–25. Walter de Gruyter, Berlin (2009)

    Google Scholar 

  14. Basse, A.: Gaussian moving averages and semimartingales. Electron. J. Probab. 13(39), 1140–1165 (2008)

    MATH  MathSciNet  Google Scholar 

  15. Bensoussan, A.: Stochastic Navier-Stokes equations. Acta Appl. Math. 38, 267–304 (1995)

    MATH  MathSciNet  Google Scholar 

  16. Benth, F.E., Cartea, A., Kiesel, R.: Pricing forward contracts in power markets by the certainty equivalence principle: explaining the sign of the market risk premium. J. Bank. Financ. 32(10), 2006–2021 (2008)

    Article  Google Scholar 

  17. Benth, F.E., Suess, A.: Integration Theory for Infinite Dimensional Volatility Modulated Volterra Processes (2013). Available at arXiv: 1303.7143v1

    Google Scholar 

  18. Birnir, B.: Existence, uniqueness and statistical theory of turbulents solutions of the stochastic Navier-Stokes equation, in three dimensions an overview. Banach J. Math. Anal. 4(1), 53–86 (2010)

    MATH  MathSciNet  Google Scholar 

  19. Chong, C., Klüppelberg, C.: Integrability Conditions for Space-time Stochastic Integrals: Theory and Applications (2013). Available at arXiv: 1303.2468v1

    Google Scholar 

  20. Comte, F., Renault, E.: Long memory continuous time models. J. Econom. 73(1), 101–149 (1996)

    Article  MATH  MathSciNet  Google Scholar 

  21. Corcuera, J.M.: Power variation analysis of some long-memory processes. In: Benth, F.E., Nunno, G.D., Linstrøm, T., Øksendal, B., Zhang, T. (eds.) Stochastic Analysis and Applications: The Abel Symposium 2005, pp. 219–234. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  22. Corcuera, J.M., Nualart, D., Woerner, J.H.C.: Power variation of some integral fractional processes. Bernoulli 12, 713–735 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  23. Corcuera, J.M., Farkas G., Schoutens, W., Valkeyla, E.: A short rate model using ambit processes. In: Viens, F., Feng, J., Hu, Y., Nualart, E. (eds.) Malliavin Calculus and Stochastic Analysis, A Festschrift in Honor of David Nualart, pp. 525–553. Springer, New York (2013)

    Chapter  Google Scholar 

  24. Corcuera, J.M.; Hedevang, E., Pakkanen, M. and Podolskij, M.: Asymptotic theory for Brownian semi-stationary processes with application to turbulence (2013). Stoch. Proc. Appl. 123(7), 2552-2574 (2013).

    Article  MathSciNet  Google Scholar 

  25. Heath, D., Jarrow, R., Morton, A.: Bond pricing and the term structure of interest rates: a new methodology for contingent claims valuation. Econometrica 60(1), 77–105 (1992)

    Article  MATH  Google Scholar 

  26. Hedevang, E.: Stochastic modelling of turbulence with applications to wind energy. Ph.D Thesis (2012). Available at http://pure.au.dk/portal/files/51621098/math_phd_2012_eh.pdf.

  27. Hikspoors, S., Jaimungal, S.: Asymptotic pricing of commodity derivatives for stochastic volatility spot models. Appl. Math. Finance 15(5&6), 449–467 (2008)

    Article  MATH  MathSciNet  Google Scholar 

  28. Jeanblanc, M., Yor, M., Chesney, M.: Mathematical Methods for Financial Markets. Springer Finance, London (2009)

    Book  MATH  Google Scholar 

  29. Kailath, T.: Fredholm resolvents, Wiener-Hopf equations, and Riccati differential equations. IEEE Trans. Inf. Theory IT-15(6), 665–672 (1969)

    Google Scholar 

  30. Khoshnevisan, D.: A primer on Stochastic Partial Differential Equations. Lecture Notes in Mathematics, vol. 1962, pp. 1–36. Springer, Berlin (2009)

    Google Scholar 

  31. Koekebakker, S., Ollmar, F.: Forward curve dynamics in the Nordic electricity market. Manage. Financ. 31(6), 73–94 (2005)

    Google Scholar 

  32. Mikulevicius, R., Rozoskii, L.B.: Stochastic Navier-Stokes equations for turbulent flows. SIAM J. Math. Anal. 35(5), 1250–1310 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  33. Musiela, M., Rutkowski, M.: Martingale Methods in Financial Modelling. Stochastic Modelling and Applied Probability, vol. 36. Springer, Heildeberg (2006)

    Google Scholar 

  34. Mytnik, L., Neuman E.: Sample Path Properties of Volterra Processes (2011). Available at Arxiv: 1210.1354v1

    Google Scholar 

  35. Samuelson, P.: Proof that properly anticipated prices fluctuate randomly. Ind. Manage. Rev. 6, 41–44 (1965)

    Google Scholar 

  36. Schwartz, E.: The stochastic behavior of commodity prices: Implications for valuation and hedging. J. Financ. 52(3), 923–973 (1997)

    Article  Google Scholar 

  37. Varberg, D.E.: Convergence of quadratic forms in independent random variables. Ann. Math. Statist. 37, 567–576 (1966)

    Article  MATH  MathSciNet  Google Scholar 

  38. Veraart, A.E.D., Veraart, L.A.M.: Modelling electricity day-ahead prices by multivariate Levy semistationary processes. In: Benth, F.E., Kholodnyi, V., Laurence, P. (eds.) Quantitative Energy Finance. Springer, Heidelberg (2013)

    Google Scholar 

  39. Walsh, J.B.: An Introduction to Stochastic Partial Differential Equations. Lecture Notes in Mathematics vol. 1180, pp. 265–439. Springer, Berlin (1986)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to José Manuel Corcuera .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Corcuera, J.M., Farkas, G., Valdivia, A. (2014). Ambit Processes, Their Volatility Determination and Their Applications. In: Korolyuk, V., Limnios, N., Mishura, Y., Sakhno, L., Shevchenko, G. (eds) Modern Stochastics and Applications. Springer Optimization and Its Applications, vol 90. Springer, Cham. https://doi.org/10.1007/978-3-319-03512-3_14

Download citation

Publish with us

Policies and ethics