Motivated by the energy domain, we examine a risk-averse buyer that has to purchase a fixed quantity of a continuous good. The buyer has two opportunities to buy: now or later. The buyer can spread the quantity over the two timeslots in any way, as long as the total quantity remains the same. The current price is known, but the future price is not. It is well known that risk neutral buyers purchase in whichever timeslot they expect to be the cheapest, regardless of the uncertainty of the future price. Research suggests, however, that most people may in fact be risk-averse. If the future price is expected to be lower than the current price, but very uncertain, then they may prefer to purchase in the present, or spread the quantity over both timeslots. We describe a formal model with a uniform price distribution and a piecewise linear risk aversion function.We provide a theorem that states the optimal behavior as a closed-form expression, and we give a proof of this theorem.

The Power TAC is a competition-based simulation of an electricity market. The goal of the competition is to test retailer (broker) strategies in a competitive environment. Participants create broker agents that trade electricity. In this paper we describe our broker, which we created as a participant of the 2014 Power TAC competition. We describe the strategies for two main components of the game: the tariff market and the wholesale market. We also discuss the performance of our broker in the competition, where we were second in the final ranking.

We examine retailers that maximize their relative profit, which is the (absolute) profit relative to the average profit of the other retailers. Customer behavior is modelled by a multinomial logit (MNL) demand model. Although retailers with low retail prices attract more customers than retailers high retail prices, the retailer with the lowest retail price, according to this model, does not attract all the customers. We provide first and second order derivatives, and show that the relative profit, as a function of the own price, has a unique local maximum. Our experiments show that relative profit maximizers "beat" absolute profit maximizers, i.e. They outperform absolute profit maximizers if the goal is to make a higher profit. These results provide insight into market simulation competitions, such as the Power TAC.

Motivated by the energy domain, we examine a risk-averse buyer that has to purchase a fixed quantity of a continuous good. The buyer has two opportunities to buy: now or later. The buyer can spread the quantity over the two timeslots in any way, as long as the total quantity remains the same. The current price is known, but the future price is not. It is well known that risk neutral buyers purchase in whichever timeslot they expect to be the cheapest, regardless of the uncertainty of the future price. Research suggests, however, that most people may in fact be risk-averse. If the expected future price is lower than the current price, but very uncertain, then they may purchase in the present, or spread the quantity over both timeslots. We describe a formal model with a uniform price distribution and a two-segment piecewise linear risk aversion function. We provide a theorem that states the optimal decision as a closed-form expression.