IDEAS home Printed from https://ideas.repec.org/a/wsi/ijtafx/v11y2008i05ns0219024908004889.html
   My bibliography  Save this article

Measuring The Market Risk Of Freight Rates: A Value-At-Risk Approach

Author

Listed:
  • TIMOTHEOS ANGELIDIS

    (Department of Economics, University of Peloponnese, Greece)

  • GEORGE SKIADOPOULOS

    (Department of Banking and Financial Management, University of Piraeus, Greece;
    Financial Options Research Centre, Warwick Business School, University of Warwick, Greece)

Abstract

The fluctuation of shipping freight rates (freight rate risk) is an important source of market risk for all participants in the freight markets including hedge funds, commodity and energy producers. We measure the freight rate risk by the Value-at-Risk (VaR) approach. A range of parametric and non-parametric VaR methods is applied to various popular freight markets for dry and wet cargoes. Backtesting is conducted in two stages by means of statistical tests and a subjective loss function that uses the Expected Shortfall, respectively. We find that the simplest non-parametric methods should be used to measure freight rate risk. In addition, freight rate risk is greater in the wet cargoes markets. The margins in the growing freight derivatives markets should be set accordingly.

Suggested Citation

  • Timotheos Angelidis & George Skiadopoulos, 2008. "Measuring The Market Risk Of Freight Rates: A Value-At-Risk Approach," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 11(05), pages 447-469.
  • Handle: RePEc:wsi:ijtafx:v:11:y:2008:i:05:n:s0219024908004889
    DOI: 10.1142/S0219024908004889
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0219024908004889
    Download Restriction: Access to full text is restricted to subscribers

    File URL: https://libkey.io/10.1142/S0219024908004889?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. repec:dau:papers:123456789/607 is not listed on IDEAS
    2. Christoffersen, Peter, 2011. "Elements of Financial Risk Management," Elsevier Monographs, Elsevier, edition 2, number 9780123744487.
    3. Helyette Geman, 2005. "Commodities and Commodity Derivatives. Modeling and Pricing for Agriculturals, Metals and Energy," Post-Print halshs-00144182, HAL.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Alexandridis, George & Kavussanos, Manolis G. & Kim, Chi Y. & Tsouknidis, Dimitris A. & Visvikis, Ilias D., 2018. "A survey of shipping finance research: Setting the future research agenda," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 115(C), pages 164-212.
    2. Alizadeh, Amir H., 2013. "Trading volume and volatility in the shipping forward freight market," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 49(1), pages 250-265.
    3. Wessam M. T. Abouarghoub & Iris Biefang-Frisancho Mariscal, 2011. "Measuring level of risk exposure in tanker Shipping freight markets," International Journal of Business and Social Research, LAR Center Press, vol. 1(1), pages 20-44, December.
    4. Wenming Shi & Kevin X. Li & Zhongzhi Yang & Ganggang Wang, 2017. "Time-varying copula models in the shipping derivatives market," Empirical Economics, Springer, vol. 53(3), pages 1039-1058, November.
    5. Javier Población & Gregorio Serna, 2018. "A common long-term trend for bulk shipping prices," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 20(3), pages 421-432, September.
    6. Charalampos Basdekis & Apostolos Christopoulos & Alexandros Gkolfinopoulos & Ioannis Katsampoxakis, 2022. "VaR as a risk management framework for the spot and futures tanker markets," Operational Research, Springer, vol. 22(4), pages 4287-4352, September.
    7. Goulas, Lambros & Skiadopoulos, George, 2012. "Are freight futures markets efficient? Evidence from IMAREX," International Journal of Forecasting, Elsevier, vol. 28(3), pages 644-659.
    8. Kostas Andriosopoulos & Nikos Nomikos, 2012. "Risk management in the energy markets and Value-at-Risk modelling: a Hybrid approach," RSCAS Working Papers 2012/47, European University Institute.
    9. Yingying Kang & Rajan Batta & Changhyun Kwon, 2014. "Value-at-Risk model for hazardous material transportation," Annals of Operations Research, Springer, vol. 222(1), pages 361-387, November.
    10. Kavussanos, Manolis G. & Dimitrakopoulos, Dimitris N., 2011. "Market risk model selection and medium-term risk with limited data: Application to ocean tanker freight markets," International Review of Financial Analysis, Elsevier, vol. 20(5), pages 258-268.
    11. Javier Población & Gregorio Serna, 2021. "Measuring bulk shipping prices risk," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 23(2), pages 291-309, June.

    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. Goulas, Lambros & Skiadopoulos, George, 2012. "Are freight futures markets efficient? Evidence from IMAREX," International Journal of Forecasting, Elsevier, vol. 28(3), pages 644-659.
    2. Joanna Janczura & Aleksander Weron, 2008. "Modelling energy forward prices," HSC Research Reports HSC/08/03, Hugo Steinhaus Center, Wroclaw University of Technology.
    3. Bai, Yizhou & Xue, Cheng, 2021. "An empirical study on the regulated Chinese agricultural commodity futures market based on skew Ornstein-Uhlenbeck model," Research in International Business and Finance, Elsevier, vol. 57(C).
    4. Torben G. Andersen & Tim Bollerslev & Peter Christoffersen & Francis X. Diebold, 2007. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," NBER Chapters, in: The Risks of Financial Institutions, pages 513-544, National Bureau of Economic Research, Inc.
    5. Alexander, Gordon J. & Baptista, Alexandre M. & Yan, Shu, 2012. "When more is less: Using multiple constraints to reduce tail risk," Journal of Banking & Finance, Elsevier, vol. 36(10), pages 2693-2716.
    6. Misund, Bård & Oglend, Atle, 2016. "Supply and demand determinants of natural gas price volatility in the U.K.: A vector autoregression approach," Energy, Elsevier, vol. 111(C), pages 178-189.
    7. Rau-Bredow, Hans, 2022. "Contango and Backwardation in Arbitrage-Free Futures-Markets," EconStor Preprints 249292, ZBW - Leibniz Information Centre for Economics.
    8. Dai, Yingtong & Harris, Richard D.F., 2023. "Average tail risk and aggregate stock returns," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    9. Abdullah Almansour and Margaret Insley, 2016. "The Impact of Stochastic Extraction Cost on the Value of an Exhaustible Resource: An Application to the Alberta Oil Sands," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    10. Juri Hinz & Martina Wilhelm, 2006. "Pricing Flow Commodity Derivatives Using Fixed Income Market Techniques," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 9(08), pages 1299-1321.
    11. 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.
    12. Toker Doganoglu & Christoph Hartz & Stefan Mittnik, 2007. "Portfolio optimization when risk factors are conditionally varying and heavy tailed," Computational Economics, Springer;Society for Computational Economics, vol. 29(3), pages 333-354, May.
    13. Dionne, Georges & Pacurar, Maria & Zhou, Xiaozhou, 2015. "Liquidity-adjusted Intraday Value at Risk modeling and risk management: An application to data from Deutsche Börse," Journal of Banking & Finance, Elsevier, vol. 59(C), pages 202-219.
    14. Petra Posedel, 2006. "Analysis of the Exchange Rate and Pricing Foreign Currency Options on the Croatian Market: the NGARCH Model as an Alternative to the Black-Scholes Model," Financial Theory and Practice, Institute of Public Finance, vol. 30(4), pages 347-368.
    15. Xuehai Zhang, 2019. "Value at Risk and Expected Shortfall under General Semi-parametric GARCH models," Working Papers CIE 123, Paderborn University, CIE Center for International Economics.
    16. Bernardo León & Andrés Mora, 2011. "CDS: relación con índices accionarios y medida de riesgo," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 29(64), pages 178-211, July.
    17. Christos Agiakloglou & Charalampos Agiropoulos, 2011. "The sensitivity of Value-at-Risk estimates using Monte Carlo approach," SPOUDAI Journal of Economics and Business, SPOUDAI Journal of Economics and Business, University of Piraeus, vol. 61(1-2), pages 7-12, January -.
    18. Matthias Janssen & Magnus Wobben, "undated". "Electricity Pricing and Market Power - Evidence from Germany," Working Papers 200121, Institute of Spatial and Housing Economics, Munster Universitary.
    19. Jorge M. Uribe & Julián Fernández, 2014. "Riesgo sistémico en el mercado de acciones colombiano: alternativas de diversificación bajo eventos extremos," Revista Cuadernos de Economia, Universidad Nacional de Colombia, FCE, CID, August.
    20. David Laughton & Raul Guerrero & Donald Lessard, 2008. "Real Asset Valuation: A Back‐to‐basics Approach," Journal of Applied Corporate Finance, Morgan Stanley, vol. 20(2), pages 46-65, March.

    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:wsi:ijtafx:v:11:y:2008:i:05:n:s0219024908004889. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/ijtaf/ijtaf.shtml .

    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.