Project Summary:
Integrated Approaches for Managing Risk in Energy Markets
Xin Guo & Phil Kaminsky
Dept of Industrial Engineering and Operations Research
{xinguo, kaminsky@ieor.berkeley.edu}
We consider two closely related problems that arise in resource extraction and power generation.
The first, the producer problem, concerns the problem of reversible investment/capacity level
determination. Facing the risk of market uncertainty, companies extract resources (such as oil or
gas) and modify the extracted capacity level in response to the random fluctuations in the market
price for the extracted resources, subject to some capacity constraints, as well as the associated
costs for capacity expansion and contraction. The goal of these companies is to maximize longterm profit, subject to these constraints.
Related to this is a problem we call the distributor problem, which concerns firms that distribute
the resources discussed above. Such a firm faces random end-user demand for the resource after
some random length of time. At any time until this demand is experienced, the firm can either
increase or decrease its stored level of the resource by buying or selling on a spot market where
price fluctuates randomly over time. The firm meets the end-user demand when it arrives, and
its sales revenue is a function of the spot market price at the time that the demand is met.
Although these two problems reflect different aspects of risk management in energy markets,
they consider firms whose businesses are fundamentally linked, and both, surprisingly, can be
formulated and analyzed using closely related mathematical tools.
Our research agenda
In the context of resource distribution, we propose continuous time models for spot market price
evolution, and determine how the firm can acquire and sell resources in the spot market
repeatedly in order to guard against cost uncertainty, demand quantity uncertainty, and demand
price uncertainty.
Based on some preliminary results for the basic model proposed above, we propose extending
our model and continuing our analysis in the following ways over the next several years:
• We will add non-linear ordering costs and analyze the more difficult impulse control
problem
• We will study more realistic price processes such as mean-reverting processes
• We will incorporate capacity constraints
• We will consider multi-period models.