Mean-reverting additive energy forward curves in a Heath-Jarrow-Morton framework

被引:13
|
作者
Benth, Fred Espen [1 ]
Piccirilli, Marco [2 ]
Vargiolu, Tiziano [2 ]
机构
[1] Univ Oslo, Dept Math, POB 1053, N-0316 Oslo, Norway
[2] Univ Padua, Dept Math, Via Trieste 63, I-35121 Padua, Italy
关键词
Energy markets; Mean-reversion; Heath-Jarrow-Morton approach; Forwards; Martingale property; MARKET PRICE; RISK PREMIUM; ELECTRICITY; MODEL; POISSON; GAS;
D O I
10.1007/s11579-019-00237-x
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
In this paper, we make the traditional modeling approach of energy commodity forwards consistent with no-arbitrage. In fact, traditionally energy prices are modeled as mean-reverting processes under the real-world probability measure P, which is in apparent contradiction with the fact that they should be martingales under a risk-neutral measure Q. The key point here is that the two dynamics can coexist, provided a suitable change of measure is defined between P and Q. To this purpose, we design a Heath-Jarrow-Morton framework for an additive, mean-reverting, multicommodity market consisting of forward contracts of any delivery period. Even for relatively simple dynamics, we face the problem of finding a density between P and Q, such that the prices of traded assets like forward contracts are true martingales under Q and mean-reverting under P. Moreover, we are also able to treat the peculiar delivery mechanism of forward contracts in power and gas markets, where the seller of a forward contract commits to deliver, either physically or financially, over a certain period, while in other commodity, or stock, markets, a forward is usually settled on a maturity date. By assuming that forward prices can be represented as affine functions of a universal source of randomness, we can completely characterize the models which prevent arbitrage opportunities by formulating conditions under which the change of measure between P and Q is well defined. In this respect, we prove two results on the martingale property of stochastic exponentials. The first allows to validate measure changes made of two components: an Esscher-type density and a Girsanov transform with stochastic and unbounded kernel. The second uses a different approach and works for the case of continuous density. We show how this framework provides an explicit way to describe a variety of models by introducing, in particular, a generalized Lucia-Schwartz model and a cross-commodity cointegrated market.
引用
收藏
页码:543 / 577
页数:35
相关论文
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