# NFCP

N-Factor Commodity Pricing Through Term Structure Estimation

Commodity pricing models are (systems of) stochastic differential
equations that are utilized for the valuation and hedging of commodity
contingent claims (i.e. derivative products on the commodity) and other
commodity related investments. Parameters of commodity pricing models
are estimated through maximum likelihood estimation, using available
term structure futures data of a commodity. ‘NFCP’ (n-factor commodity
pricing) provides a framework for the modeling, parameter estimation,
probabilistic forecasting, option valuation and simulation of commodity
prices through state space and Monte Carlo methods, risk-neutral
valuation and Kalman filtering. ‘NFCP’ allows the commodity pricing
model to consist of n correlated factors, with both random walk and
mean-reverting elements. Commodity pricing models that capture market
dynamics are of great importance to commodity market participants in
order to exercise sound investment and risk-management strategies. The
n-factor commodity pricing model framework was first presented in the
work of Cortazar and Naranjo (2006). Examples presented in ‘NFCP’
replicate the two-factor crude oil commodity pricing model presented in
the prolific work of Schwartz and Smith (2000) with the approximate term
structure futures data applied within this study provided in the ‘NFCP’
package. Kalman filtering in ‘NFCP’ is performed using sequential
processing through the ‘FKF.SP’ package to optimise computational
efficiency. Parameter estimation of n-factor models is performed using
genetic algorithms through the ‘rGenoud’ package to maximise the
likelihood that a global maximum is reached during maximum likelihood
estimation.

Primary features of ‘NFCP’ include:

Parameter estimation of n-factor commodity pricing models through
state space methods, Kalman filtering and maximum likelihood
estimation.

Analytic pricing of European call and put options under estimated
n-factor commodity pricing models

Numeric pricing of American options under estimated n-factor
commodity pricing models

Probabilistic forecasting and Monte Carlo simulation of future
commodity price paths.

## Installation

You can install the released version of NFCP from CRAN with:

`install.packages("NFCP")`

And the development version from GitHub with:

`devtools::install_github("TomAspinall/NFCP")`

which contains source code for the package starting with version
0.1.0.