Quota markets are increasingly used to ration power market and environmental goods, including capacity, emissions permits and renewable subsidies. The obvious and most international of these markets is the EU ETS; however there are many more including the Swedish-Nordic El-Cert market, and the increasing number of capacity auctions and certificate markets popping up in Europe and elsewhere.
One characteristic of these markets is that the good that is traded is “artificial” - and typically the demand for it has been legislated by government. This means that the demand for the good is defined by rules, not by want or need, and thus behaves quite differently to "normal" markets. Quota markets are often either long (there are too many quotas or certificates) to meet the legislated demand, or short (there are not enough). If long, the price is zero. If short, then the price is set by a legislated penalty for not having enough quotas. Pricing in between is due to uncertainty - you don't know whether the market is long or short. This dynamic results in behaviour like big swings in prices, or - often - price hikes, then price collapses as the market looks long, followed by rule changes to support price levels.
This means that such markets are not able to be analysed that effectively by traditional economic models that are based on the idea of equilibrium. Quota markets are not in equilibrium, so should not be analysed as if they were.
Instead, at Optimeering we attack this problem via the use of intelligent agent-based models, that combine AI techniques with modelling of actual market actors to simulate market behaviour under realistic market conditions. Together with Thema Consulting Group, we developed the MARC model for the Swedish-Norwegian El-cert market, that has been used by a range of developers, regulators and operators to better understand and predict future market outturns. To learn more how we can use agent modelling to help you better understand the quota markets that drive your bottom line, contact us here.