Power purchase agreements (PPAs) have become an important corporate procurement vehicle for renewable power, especially among companies that have committed to targets requiring a certain fraction of their power demand be met by renewables. PPAs are long-term contracts that provide renewable...

We model the interaction between a slow institutional investor and a high-frequency trader as a stochastic multiperiod Stackelberg game. The high-frequency trader exploits price information more frequently and is subject to periodic inventory constraints. We first derive the optimal strategy of...

This article introduces a very flexible framework for causal and predictive market views and stress-testing. The framework elegantly combines Bayesian networks (BNs) and Entropy Pooling (EP). In the new framework, BNs are used to generate a finite set of joint causal views / stress-tests for the...

We consider the strategic interaction of traders in a continuous-time financial market with Epstein-Zin-type recursive intertemporal preferences and performance concerns. We derive explicitly an equilibrium for the finite player and the mean-field version of the game, based on a study of...

The proliferation of factor investing strategies in recent years has highlighted the idea that a portfolio can harvest improved risk-adjusted returns through timed exposure to risk factors during times of elevated risk premia. While there is a large body of research on such risk factors and risk...

In this paper, we present an innovative electricity spot price model, wherein the prices explicitly depend on outdoor temperature. The proposed arithmetic multi-factor approach captures numerous stylized facts of empirical electricity price behavior like seasonal variations, time-dependent...

We consider a class of learning problems in which an agent liquidates a risky asset while creating both transient price impact driven by an unknown convolution propagator and linear temporary price impact with an unknown parameter. We characterize the trader's performance as maximization of a...

We study merchant energy production modeled as a compound switching and timing option. The resulting Markov decision process is intractable. Least squares Monte Carlo combined with information relaxation and duality is a state-of-the-art reinforcement learning methodology to obtain operating...

Amid the controversies around the optimisation criteria and the objective functions when applying mathematical methods in economics, we proposed a method of quantifying a multi-criteria optimum, called critical distance method. The demonstration of this method is exemplified by assessing the...

One method of isolating the useful signal from the noise is by using a soft- processor Kalman filter. There are many applications of how one could use a Kalman filter: using navigation systems, such as satellite or radio, and sonar tracking systems. The guidance systems in military applications...