Home > Energy Derivatives > Time and Product Basis Risks on Illiquid Commodity Forwards

Time and Product Basis Risks on Illiquid Commodity Forwards

A common problem in commodities markets is the lack of a forward market. This is especially so for products further down the supply chain as the number of producers and consumers dwindle, causing both alike to have liquidity issues in hedging their forward price exposure.

Many banks have stepped in as market makers for commodities further down the time horizon. Aside from the smaller market, several illiquid commodities are marked off published spot indices having no forward markets. These include the Japan Crude Cocktail, JCC and the Zeebrugge gas index, which are popular gas indices in Asia and Europe tied to crude oil prices. These historical linkages are not likely to change anytime soon, due to the long term contracts for the natural gas markets. See article in the NYT.

In creating a market for these illiquid commodity forwards, traders normally infer their prices from upstream products or substitutes through statistical regressions on the spot. Doing so produce both product and time basis risks. Product basis risks result from the production economics of the downstream illiquid product from the precursors while time basis risks originate from the projection of spot to forward relationships and the non-stationarity of the relationships. A case in point is petrochemicals which are made from either naphtha or natural gas. Petrochemicals like polyethylene are derived from naphtha cracking and compose of varied products like benzene and other aromatics derivatives. These derived products are frequently ‘proxied’ by upstream naphtha or more liquid substitutes like gasoline.

A plausible solution to time risks is the use of stochastic parameter regression. This allows capture of time risks compared to an ordinary least square regression. In a stochastic parameter regression, the hedging ratios are themselves updated in a regression to fit existing market conditions whereas hedging ratios are ‘averaged out’ over a fixed window in an ordinary regression.

To mitigate product risks, fundamental projections of demand and supply are used as explanatory factors in the regression. These allow for better prediction as they make up the idiosyncratic risks in the proxy production economics. However, being economic and not market variables they cannot be hedged.

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