IDEAS home Printed from https://ideas.repec.org/a/kap/netnom/v4y2002i2d10.1023_a1021206013952.html
   My bibliography  Save this article

Dynamics of Link Failure Events in Network Markets

Author

Listed:
  • Giorgos Cheliotis

    (Zurich Research Laboratory)

  • Chris Kenyon

    (Zurich Research Laboratory)

Abstract

We present a computational model and simulation results on the dynamics of local link failures in markets with network structure. Bandwidth markets are inherently networked, so we focus on telecommunications here. The objective of this paper is to test whether or not network failures will have serious economic consequences. We measure economic consequences by looking at changes in expected bandwidth prices, changes in value-at-risk (VAR) and in conditional-value-at-risk (CVAR). Bandwidth markets may be particularly sensitive to network failures because bandwidth is a non-storable commodity. On the other hand alternative paths with equivalent quality of service (QoS) are perfect substitutes so this may limit sensitivity. Non-storability has contributed to enormous volatility in deregulated electricity prices and observations of enormous price spikes. Bandwidth is a true network commodity in that links in the network itself are the traded commodities. Thus a local failure can affect alternative equivalent paths and this can have a knock-on effect in turn. We used a spot market model incorporating non-storability and alternative path selection on price grounds and limited by QoS-equivalence. Spike models are incorporated based on empirical data. We found that for a realistic large-scale market topology if there are, say, four failures per link per year, half of which are long enough to affect the market, then: expected link prices are increased 12%; VAR is increased by 30%; and CVAR by 40%. This is even with a spike size (×3) that is modest compared to observations in electricity markets (×10–×100). For market participants with capacity positions in such a market these consequences are likely to be serious. Thus if failures occur at this rate their consequence must be included in planning. Furthermore, whilst at low failure intensities the network acts as a dampening factor, at higher intensities it acts as an amplifier and thus cannot be neglected. We believe this amplification to be an emergent phenomenon of any market with network structure, although clearly more important for markets with no storage.

Suggested Citation

  • Giorgos Cheliotis & Chris Kenyon, 2002. "Dynamics of Link Failure Events in Network Markets," Netnomics, Springer, vol. 4(2), pages 163-185, November.
  • Handle: RePEc:kap:netnom:v:4:y:2002:i:2:d:10.1023_a:1021206013952
    DOI: 10.1023/A:1021206013952
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1023/A:1021206013952
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1023/A:1021206013952?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Eduardo Schwartz & James E. Smith, 2000. "Short-Term Variations and Long-Term Dynamics in Commodity Prices," Management Science, INFORMS, vol. 46(7), pages 893-911, July.
    2. Schwartz, Eduardo S, 1997. "The Stochastic Behavior of Commodity Prices: Implications for Valuation and Hedging," Journal of Finance, American Finance Association, vol. 52(3), pages 923-973, July.
    3. Glick, Reuven & Rose, Andrew K., 1999. "Contagion and trade: Why are currency crises regional?," Journal of International Money and Finance, Elsevier, vol. 18(4), pages 603-617, August.
    4. Mr. Paul R Masson, 1998. "Contagion: Monsoonal Effects, Spillovers, and Jumps Between Multiple Equilibria," IMF Working Papers 1998/142, International Monetary Fund.
    5. Merton, Robert C., 1976. "Option pricing when underlying stock returns are discontinuous," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 125-144.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chen, Shan & Insley, Margaret, 2012. "Regime switching in stochastic models of commodity prices: An application to an optimal tree harvesting problem," Journal of Economic Dynamics and Control, Elsevier, vol. 36(2), pages 201-219.
    2. Björn Lutz, 2010. "Pricing of Derivatives on Mean-Reverting Assets," Lecture Notes in Economics and Mathematical Systems, Springer, number 978-3-642-02909-7, December.
    3. Chris Brooks & Marcel Prokopczuk, 2013. "The dynamics of commodity prices," Quantitative Finance, Taylor & Francis Journals, vol. 13(4), pages 527-542, March.
    4. Arturo Lorenzo-Valdés, 2021. "Conditional Probability of Jumps in Oil Prices," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 16(4), pages 1-14, Octubre -.
    5. Neil A. Wilmot, 2019. "Heavy Metals: Might as Well Jump," IJFS, MDPI, vol. 7(2), pages 1-14, June.
    6. Jean-Thomas Bernard & Lynda Khalaf & Maral Kichian & Sebastien Mcmahon, 2008. "Forecasting commodity prices: GARCH, jumps, and mean reversion," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(4), pages 279-291.
    7. Dempster, M.A.H. & Medova, Elena & Tang, Ke, 2018. "Latent jump diffusion factor estimation for commodity futures," Journal of Commodity Markets, Elsevier, vol. 9(C), pages 35-54.
    8. Fernandes, Mário Correia & Dias, José Carlos & Nunes, João Pedro Vidal, 2021. "Modeling energy prices under energy transition: A novel stochastic-copula approach," Economic Modelling, Elsevier, vol. 105(C).
    9. Larsson, Karl & Nossman, Marcus, 2011. "Jumps and stochastic volatility in oil prices: Time series evidence," Energy Economics, Elsevier, vol. 33(3), pages 504-514, May.
    10. Mason, Charles F. & Wilmot, Neil A., 2020. "Jumps in the convenience yield of crude oil," Resource and Energy Economics, Elsevier, vol. 60(C).
    11. Askari, Hossein & Krichene, Noureddine, 2008. "Oil price dynamics (2002-2006)," Energy Economics, Elsevier, vol. 30(5), pages 2134-2153, September.
    12. Bernard, Jean-Thomas & Khalaf, Lynda & Kichian, Maral & McMahon, Sébastien, 2008. "Oil Prices: Heavy Tails, Mean Reversion and the Convenience Yield," Cahiers de recherche 0801, GREEN.
    13. Neil A. Wilmot and Charles F. Mason, 2013. "Jump Processes in the Market for Crude Oil," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    14. Yepes Rodri­guez, Ramón, 2008. "Real option valuation of free destination in long-term liquefied natural gas supplies," Energy Economics, Elsevier, vol. 30(4), pages 1909-1932, July.
    15. Xiong, Heng & Mamon, Rogemar, 2019. "A higher-order Markov chain-modulated model for electricity spot-price dynamics," Applied Energy, Elsevier, vol. 233, pages 495-515.
    16. Prilly Oktoviany & Robert Knobloch & Ralf Korn, 2021. "A machine learning-based price state prediction model for agricultural commodities using external factors," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 1063-1085, December.
    17. Gimet, Celine, 2007. "Conditions necessary for the sustainability of an emerging area: The importance of banking and financial regional criteria," Journal of Multinational Financial Management, Elsevier, vol. 17(4), pages 317-335, October.
    18. Guedes, José & Santos, Pedro, 2016. "Valuing an offshore oil exploration and production project through real options analysis," Energy Economics, Elsevier, vol. 60(C), pages 377-386.
    19. Jilong Chen & Christian Ewald & Ruolan Ouyang & Sjur Westgaard & Xiaoxia Xiao, 2022. "Pricing commodity futures and determining risk premia in a three factor model with stochastic volatility: the case of Brent crude oil," Annals of Operations Research, Springer, vol. 313(1), pages 29-46, June.
    20. Fiuza de Bragança, Gabriel Godofredo & Daglish, Toby, 2016. "Can market power in the electricity spot market translate into market power in the hedge market?," Energy Economics, Elsevier, vol. 58(C), pages 11-26.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:netnom:v:4:y:2002:i:2:d:10.1023_a:1021206013952. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.