IDEAS home Printed from https://ideas.repec.org/a/eee/ecmode/v70y2018icp496-510.html
   My bibliography  Save this article

Convenience yield, realised volatility and jumps: Evidence from non-ferrous metals

Author

Listed:
  • Omura, Akihiro
  • Li, Bin
  • Chung, Richard
  • Todorova, Neda

Abstract

Under the notion of convenience yield, a price of spot contract inherits relative implied value, against futures/forward contracts, for being readily available. This study examines the presence of a short-term lead-lag relationship between the volatility of futures price changes (including its decomposed components) and the convenience yield of major base metals, namely, aluminium, copper, nickel and zinc. Since an increase in the level of volatility may stimulate the demand for inventory, this study aims to provide alternative measures to understand the dynamic behaviour of convenience yield. Taken together, the results mostly support the presence of statistically significant relationships between the convenience yield and the realised volatility, which can be used for constructing effective inventory and investment strategies.

Suggested Citation

  • Omura, Akihiro & Li, Bin & Chung, Richard & Todorova, Neda, 2018. "Convenience yield, realised volatility and jumps: Evidence from non-ferrous metals," Economic Modelling, Elsevier, vol. 70(C), pages 496-510.
    • Handle: RePEc:eee:ecmode:v:70:y:2018:i:c:p:496-510
    DOI: 10.1016/j.econmod.2017.08.033
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0264999317312257
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econmod.2017.08.033?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. Corsi, Fulvio & Pirino, Davide & Renò, Roberto, 2010. "Threshold bipower variation and the impact of jumps on volatility forecasting," Journal of Econometrics, Elsevier, vol. 159(2), pages 276-288, December.
    2. Markus Hochradl & Margarethe Rammerstorfer, 2012. "The convenience yield implied in European natural gas hub trading," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 32(5), pages 459-479, May.
    3. Creti, Anna & Joëts, Marc & Mignon, Valérie, 2013. "On the links between stock and commodity markets' volatility," Energy Economics, Elsevier, vol. 37(C), pages 16-28.
    4. Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Narayan, Paresh Kumar, 2016. "Intraday volatility interaction between the crude oil and equity markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 40(C), pages 1-13.
    5. Ole E. Barndorff-Nielsen & Neil Shephard, 2004. "Econometric Analysis of Realized Covariation: High Frequency Based Covariance, Regression, and Correlation in Financial Economics," Econometrica, Econometric Society, vol. 72(3), pages 885-925, May.
    6. Todorova, Neda, 2015. "The course of realized volatility in the LME non-ferrous metal market," Economic Modelling, Elsevier, vol. 51(C), pages 1-12.
    7. Stepanek, Christian & Walter, Matthias & Rathgeber, Andreas, 2013. "Is the convenience yield a good indicator of a commodity's supply risk?," Resources Policy, Elsevier, vol. 38(3), pages 395-405.
    8. repec:dau:papers:123456789/14980 is not listed on IDEAS
    9. Koopman, Siem Jan & Jungbacker, Borus & Hol, Eugenie, 2005. "Forecasting daily variability of the S&P 100 stock index using historical, realised and implied volatility measurements," Journal of Empirical Finance, Elsevier, vol. 12(3), pages 445-475, June.
    10. Andersen, Torben G. & Dobrev, Dobrislav & Schaumburg, Ernst, 2012. "Jump-robust volatility estimation using nearest neighbor truncation," Journal of Econometrics, Elsevier, vol. 169(1), pages 75-93.
    11. repec:hal:journl:peer-00741630 is not listed on IDEAS
    12. Liu, Peng (Peter) & Tang, Ke, 2010. "No-arbitrage conditions for storable commodities and the modeling of futures term structures," Journal of Banking & Finance, Elsevier, vol. 34(7), pages 1675-1687, July.
    13. Narayan, Paresh Kumar & Narayan, Seema & Sharma, Susan Sunila, 2013. "An analysis of commodity markets: What gain for investors?," Journal of Banking & Finance, Elsevier, vol. 37(10), pages 3878-3889.
    14. Liu, Lily Y. & Patton, Andrew J. & Sheppard, Kevin, 2015. "Does anything beat 5-minute RV? A comparison of realized measures across multiple asset classes," Journal of Econometrics, Elsevier, vol. 187(1), pages 293-311.
    15. Geman, Hélyette & Smith, William O., 2013. "Theory of storage, inventory and volatility in the LME base metals," Resources Policy, Elsevier, vol. 38(1), pages 18-28.
    16. Xin Huang & George Tauchen, 2005. "The Relative Contribution of Jumps to Total Price Variance," Journal of Financial Econometrics, Oxford University Press, vol. 3(4), pages 456-499.
    17. Barndorff-Nielsen, Ole E. & Shephard, Neil & Winkel, Matthias, 2006. "Limit theorems for multipower variation in the presence of jumps," Stochastic Processes and their Applications, Elsevier, vol. 116(5), pages 796-806, May.
    18. Fernandez, Viviana, 2016. "Futures markets and fundamentals of base metals," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 215-229.
    19. Omura, Akihiro & West, Jason, 2015. "Convenience yield and the theory of storage: applying an option-based approach," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 59(3), July.
    20. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
    21. Busch, Thomas & Christensen, Bent Jesper & Nielsen, Morten Ørregaard, 2011. "The role of implied volatility in forecasting future realized volatility and jumps in foreign exchange, stock, and bond markets," Journal of Econometrics, Elsevier, vol. 160(1), pages 48-57, January.
    22. Christopher R. Knittel & Robert S. Pindyck, 2016. "The Simple Economics of Commodity Price Speculation," American Economic Journal: Macroeconomics, American Economic Association, vol. 8(2), pages 85-110, April.
    23. John Powell & Jing Shi & Tom Smith & Robert Whaley, 2009. "Common Divisors, Payout Persistence, and Return Predictability," International Review of Finance, International Review of Finance Ltd., vol. 9(4), pages 335-357, December.
    24. repec:dau:papers:123456789/4596 is not listed on IDEAS
    25. Gilder, Dudley & Shackleton, Mark B. & Taylor, Stephen J., 2014. "Cojumps in stock prices: Empirical evidence," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 443-459.
    26. Ole E. Barndorff-Nielsen, 2004. "Power and Bipower Variation with Stochastic Volatility and Jumps," Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 1-37.
    27. Sévi, Benoît, 2015. "Explaining the convenience yield in the WTI crude oil market using realized volatility and jumps," Economic Modelling, Elsevier, vol. 44(C), pages 243-251.
    28. Parkinson, Michael, 1980. "The Extreme Value Method for Estimating the Variance of the Rate of Return," The Journal of Business, University of Chicago Press, vol. 53(1), pages 61-65, January.
    29. William Lin & Chang-Wen Duan, 2007. "Oil convenience yields estimated under demand/supply shock," Review of Quantitative Finance and Accounting, Springer, vol. 28(2), pages 203-225, February.
    30. Alexandra Dwyer & George Gardner & Thomas Williams, 2011. "Global Commodity Markets - Price Volatility and Financialisation," RBA Bulletin (Print copy discontinued), Reserve Bank of Australia, pages 49-58, June.
    31. Benjamin Yibin Zhang & Hao Zhou & Haibin Zhu, 2009. "Explaining Credit Default Swap Spreads with the Equity Volatility and Jump Risks of Individual Firms," Review of Financial Studies, Society for Financial Studies, vol. 22(12), pages 5099-5131, December.
    32. Jayawardena, Nirodha I. & Todorova, Neda & Li, Bin & Su, Jen-Je, 2016. "Forecasting stock volatility using after-hour information: Evidence from the Australian Stock Exchange," Economic Modelling, Elsevier, vol. 52(PB), pages 592-608.
    33. Andersen, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Ebens, Heiko, 2001. "The distribution of realized stock return volatility," Journal of Financial Economics, Elsevier, vol. 61(1), pages 43-76, July.
    34. Holbrook Working, 1948. "Theory of the Inverse Carrying Charge in Futures Markets," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 30(1), pages 1-28.
    35. Robert S. Pindyck, 2004. "Volatility and commodity price dynamics," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 24(11), pages 1029-1047, November.
    36. Gary B. Gorton & Fumio Hayashi & K. Geert Rouwenhorst, 2013. "The Fundamentals of Commodity Futures Returns," Review of Finance, European Finance Association, vol. 17(1), pages 35-105.
    37. Fang, Yan & Ielpo, Florian & Sévi, Benoît, 2012. "Empirical bias in intraday volatility measures," Finance Research Letters, Elsevier, vol. 9(4), pages 231-237.
    38. Ahmet E. Kocagil, 2004. "Optionality and Daily Dynamics of Convenience Yield Behavior: An Empirical Analysis," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 27(1), pages 143-158, March.
    39. Nikolaos T. Milonas & Stavros B. Thomadakis, 1997. "Convenience yields as call options: An empirical analysis," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 17(1), pages 1-15, February.
    40. Nicholas Kaldor, 1939. "Speculation and Economic Stability," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 7(1), pages 1-27.
    41. Nolte, Ingmar & Xu, Qi, 2015. "The economic value of volatility timing with realized jumps," Journal of Empirical Finance, Elsevier, vol. 34(C), pages 45-59.
    42. Akihiro Omura & Jason West, 2015. "Convenience yield and the theory of storage: applying an option-based approach," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 59(3), pages 355-374, July.
    43. Fama, Eugene F & French, Kenneth R, 1988. " Business Cycles and the Behavior of Metals Prices," Journal of Finance, American Finance Association, vol. 43(5), pages 1075-1093, December.
    44. Omura, Akihiro & Todorova, Neda & Li, Bin & Chung, Richard, 2015. "Convenience yield and inventory accessibility: Impact of regional market conditions," Resources Policy, Elsevier, vol. 44(C), pages 1-11.
    45. Hansen, Peter R. & Lunde, Asger, 2006. "Realized Variance and Market Microstructure Noise," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 127-161, April.
    46. Kaul, Gautam & Nimalendran, M., 1990. "Price reversals *1: Bid-ask errors or market overreaction?," Journal of Financial Economics, Elsevier, vol. 28(1-2), pages 67-93.
    47. Akihiro Omura & Richard Chung & Neda Todorova & Bin Li, 2016. "Relative scarcity and convenience yield: evidence from non-ferrous metals," Applied Economics, Taylor & Francis Journals, vol. 48(57), pages 5605-5624, December.
    48. Robert Heinkel & Maureen E. Howe & John S. Hughes, 1990. "Commodity convenience yields as an option profit," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 10(5), pages 519-533, October.
    49. Tauchen, George & Zhou, Hao, 2011. "Realized jumps on financial markets and predicting credit spreads," Journal of Econometrics, Elsevier, vol. 160(1), pages 102-118, January.
    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. Erdemlioglu, Deniz & Petitjean, Mikael & Vargas, Nicolas, 2021. "Market instability and technical trading at high frequency: Evidence from NASDAQ stocks," Economic Modelling, Elsevier, vol. 102(C).
    2. Borkowski, Bolesław & Krawiec, Monika & Karwański, Marek & Szczesny, Wiesław & Shachmurove, Yochanan, 2021. "Modeling garch processes in base metals returns using panel data," Resources Policy, Elsevier, vol. 74(C).
    3. Jia, Jian & Kang, Sang Baum, 2022. "Do the basis and other predictors of futures return also predict spot return with the same signs and magnitudes? Evidence from the LME," Journal of Commodity Markets, Elsevier, vol. 25(C).
    4. Ciner, Cetin & Lucey, Brian & Yarovaya, Larisa, 2020. "Spillovers, integration and causality in LME non-ferrous metal markets," Journal of Commodity Markets, Elsevier, vol. 17(C).

    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. Omura, Akihiro & Todorova, Neda & Li, Bin & Chung, Richard, 2015. "Convenience yield and inventory accessibility: Impact of regional market conditions," Resources Policy, Elsevier, vol. 44(C), pages 1-11.
    2. Sévi, Benoît, 2014. "Forecasting the volatility of crude oil futures using intraday data," European Journal of Operational Research, Elsevier, vol. 235(3), pages 643-659.
    3. Sévi, Benoît, 2015. "Explaining the convenience yield in the WTI crude oil market using realized volatility and jumps," Economic Modelling, Elsevier, vol. 44(C), pages 243-251.
    4. Kim, Soohyeon & Kim, Jihyo & Heo, Eunnyeong, 2017. "Convenience yield of accessible inventories and imports: A case study of the Chinese copper market," Resources Policy, Elsevier, vol. 52(C), pages 277-283.
    5. Maneesoonthorn, Worapree & Martin, Gael M. & Forbes, Catherine S., 2020. "High-frequency jump tests: Which test should we use?," Journal of Econometrics, Elsevier, vol. 219(2), pages 478-487.
    6. Akihiro Omura & Neda Todorova, 2019. "The quantile dependence of commodity futures markets on news sentiment," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(7), pages 818-837, July.
    7. Chen, Yixiang & Ma, Feng & Zhang, Yaojie, 2019. "Good, bad cojumps and volatility forecasting: New evidence from crude oil and the U.S. stock markets," Energy Economics, Elsevier, vol. 81(C), pages 52-62.
    8. Bu, Ruijun & Hizmeri, Rodrigo & Izzeldin, Marwan & Murphy, Anthony & Tsionas, Mike, 2023. "The contribution of jump signs and activity to forecasting stock price volatility," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 144-164.
    9. Worapree Maneesoonthorn & Gael M. Martin & Catherine S. Forbes, 2017. "Dynamic asset price jumps and the performance of high frequency tests and measures," Monash Econometrics and Business Statistics Working Papers 14/17, Monash University, Department of Econometrics and Business Statistics.
    10. Lyócsa, Štefan & Plíhal, Tomáš & Výrost, Tomáš, 2021. "FX market volatility modelling: Can we use low-frequency data?," Finance Research Letters, Elsevier, vol. 40(C).
    11. Worapree Maneesoonthorn & Gael M Martin & Catherine S Forbes, 2018. "Dynamic price jumps: The performance of high frequency tests and measures, and the robustness of inference," Monash Econometrics and Business Statistics Working Papers 17/18, Monash University, Department of Econometrics and Business Statistics.
    12. repec:ipg:wpaper:2014-053 is not listed on IDEAS
    13. Chen, Wang & Ma, Feng & Wei, Yu & Liu, Jing, 2020. "Forecasting oil price volatility using high-frequency data: New evidence," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 1-12.
    14. Liu, Yi & Liu, Huifang & Zhang, Lei, 2019. "Modeling and forecasting return jumps using realized variation measures," Economic Modelling, Elsevier, vol. 76(C), pages 63-80.
    15. Chorro, Christophe & Ielpo, Florian & Sévi, Benoît, 2020. "The contribution of intraday jumps to forecasting the density of returns," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    16. Dehua Shen & Andrew Urquhart & Pengfei Wang, 2020. "Forecasting the volatility of Bitcoin: The importance of jumps and structural breaks," European Financial Management, European Financial Management Association, vol. 26(5), pages 1294-1323, November.
    17. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Post-Print halshs-01442618, HAL.
    18. Lyócsa, Štefan & Molnár, Peter & Todorova, Neda, 2017. "Volatility forecasting of non-ferrous metal futures: Covariances, covariates or combinations?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 51(C), pages 228-247.
    19. Christensen, Kim & Oomen, Roel C.A. & Podolskij, Mark, 2014. "Fact or friction: Jumps at ultra high frequency," Journal of Financial Economics, Elsevier, vol. 114(3), pages 576-599.
    20. Ole E. Barndorff-Nielsen & Neil Shephard, 2005. "Variation, jumps, market frictions and high frequency data in financial econometrics," OFRC Working Papers Series 2005fe08, Oxford Financial Research Centre.
    21. Andersen, Torben G. & Bollerslev, Tim & Huang, Xin, 2011. "A reduced form framework for modeling volatility of speculative prices based on realized variation measures," Journal of Econometrics, Elsevier, vol. 160(1), pages 176-189, January.

    More about this item

    Keywords

    Commodity markets; Options; Realised volatility; Futures jump; Convenience yield; The theory of storage;
    All these keywords.

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market
    • Q31 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Demand and Supply; Prices
    • D51 - Microeconomics - - General Equilibrium and Disequilibrium - - - Exchange and Production Economies
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • E20 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - General (includes Measurement and Data)

    Statistics

    Access and download statistics

    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:eee:ecmode:v:70:y:2018:i:c:p:496-510. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/30411 .

    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.