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

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).