Article Detail

A Stochastic Programming Model to Minimize Volume Liquidity Risk in Commodity Trading

Journal 32: Applied Finance

Emmanuel Fragnière, Iliya Markov

The goal of this paper is to study a very important risk metric in commodity trading: volume liquidity risk. It begins by examining the statistical properties of volume and settlement price change of futures contracts of different maturities. The results are used in the construction of a model for the minimization of volume liquidity risk – the inability to cover an unprofitable position due to lack of trading volume. The model is embedded in a stochastic program designed to construct a portfolio of futures contracts of different maturities with the aim of minimizing price and volume liquidity risk. The results of the case study (grain market) show that the model predicts the best spread trade accurately in 75 percent of cases. In the remaining cases the inaccuracy is due to the market shock present in the year 2008. A tool has been coded in Excel VBA to make the model available to traders and risk managers. This contribution directly relates to Energy ETF recent issues (i.e., roll-over).

Liquidity risk is already an important factor in the management of financial risk. The current global economic crisis emphasized the need to include liquidity risk in risk management models. The financial meltdown of 2007-2008 saw the freezing of the markets for commercial paper, asset backed securities, and collateralized debt obligations among many others. Various risk models were proposed that try to deal with liquidity dryups in the financial markets in different ways – estimation of probability, pricing of liquidity risk, etc. [Pedersen (2008)]. Liquidity in the commodity sector, on the other hand, has not been given a proper academic treatment. The main trading products in the commodity sector are futures contracts. Traders usually hedge risk by entering into contracts of different maturity and opposing direction. Distant maturities, however, are associated with very low trading volume, which means that an already established position may not be closed or changed due to lack of trading volume. Thus, if an already established spread trade is found to be unprofitable, a trader may not be able to cover it because of what this paper refers to as volume liquidity risk, or simply volume risk.

This paper sets out to explore the patterns and relationships associated with volume and settlement price change and to build a stochastic program whose purpose is the construction of a portfolio where the risk of a volume liquidity trap is minimized or avoided. The use of stochastic programming is grounded on the uncertainty of the prices of distant maturities on the forward curve. The ultimate purpose of the paper is that the stochastic model should be applicable to real life situations. Consequently, it was developed in VBA in Excel, which is the most widely used software in the commodity sector. All data used in this paper is from the Kansas City Board of Trade [KCBT (2010)], the world’s largest exchange for hard red winter wheat.


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