Author(s): Oduor D Brian

Abstract: Models that can describe strike prices of energy commodities that might seem costly to store are best modeled by mean – reversion and jump diffusion processes. Physical characteristics of energy commodities makes it very difficult to store due to their salient features hence there is need to incorporate jumps and mean – reversion to some stochastic volatility models and particularly in this paper, we forecast on logistic Brownian motion. I construct a real option model to predict prices of energy commodities. This study also examines some implications on assumptions that can be portrayed by mean – reverting logistic Brownian motion with jump diffusion process. This study uses Heave – side cover up method, logistic Brownian motion, jump diffusion models and mean – reverting models to derive a pricing process that can be used to predict prices of energy commodities.

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