Commodity price risk management: Valuation of large trading portfolios under adverse and illiquid market settings

Mazin A.M. Al Janabi

    Research output: Contribution to journalArticlepeer-review

    13 Citations (Scopus)


    Given the rising need for measuring and controlling commodity price risk exposure, trading risk prediction under illiquid and adverse market conditions plays an increasing role in commodity and financial markets. The aim of this paper is to close the void in commodity trading risk management literature, particularly from the perspective of large trading portfolios, by illustrating how the modified Value-at-Risk (VaR) method can be used by a commodity trading unit in reporting risk exposure, assessing risk reduction alternatives and setting optimised risk limits. In this study we put forward a re-engineered VaR model relevant for commodity trading units that have long- and short-selling trading positions and suggest potential applications of VaR in the context of commodity risk management. To the best of our knowledge, this is the first research paper that addresses the issue of liquidity trading risk management in commodity markets with direct applications to a larger portfolio of distinctive assets. This paper provides real-world techniques and realistic asset allocation strategies that can be applied to commodity trading portfolios in illiquid markets and under adverse market conditions. The modelling technique is based on the renowned concept of liquidity-adjusted VaR (L-VaR), along with the creation of a software tool utilising matrix-algebra techniques. As such, our comprehensive risk model can simultaneously handle market risk analysis under normal and severe market settings as well as take into account the effects of illiquidity of traded commodities. In order to illustrate the proper use of L-VaR under stressed and illiquid market conditions, real-world examples and feasible reports of liquidity trading risk management are presented for a portfolio of 25 distinct commodities, within a multivariate context and under the notion of several correlation factors along with different liquidity horizons. The example and discussions are widely applicable to any commodity end-user, providing potential applications to practitioners and research ideas to academics.

    Original languageEnglish
    Pages (from-to)15-50
    Number of pages36
    JournalJournal of Derivatives and Hedge Funds
    Issue number1
    Publication statusPublished - May 2009


    • Commodity
    • Financial engineering
    • Financial risk management
    • Liquidity-adjusted Value-at-Risk (L-VaR)
    • Portfolio management
    • Stress-testing

    ASJC Scopus subject areas

    • Finance
    • Economics and Econometrics


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