Other packages > Find by keyword >

NFCP  

N-Factor Commodity Pricing Through Term Structure Estimation
View on CRAN: Click here


Download and install NFCP package within the R console
Install from CRAN:
install.packages("NFCP")

Install from Github:
library("remotes")
install_github("cran/NFCP")

Install by package version:
library("remotes")
install_version("NFCP", "1.2.2")



Attach the package and use:
library("NFCP")
Maintained by
Thomas Aspinall
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-01-13
Latest Update: 2025-06-16
Description:
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. 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. 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. 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.
How to cite:
Thomas Aspinall (2021). NFCP: N-Factor Commodity Pricing Through Term Structure Estimation. R package version 1.2.2, https://cran.r-project.org/web/packages/NFCP. Accessed 06 Mar. 2026.
Previous versions and publish date:
0.1.0 (2021-01-13 13:00), 0.2.0 (2021-02-25 12:40), 1.0.0 (2021-05-02 15:30), 1.0.1 (2021-05-06 13:50), 1.1.0 (2021-06-25 00:50), 1.2.0 (2021-08-07 10:40), 1.2.1 (2022-02-17 13:02)
Other packages that cited NFCP R package
View NFCP citation profile
Other R packages that NFCP depends, imports, suggests or enhances
Complete documentation for NFCP
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

solitude  
An Implementation of Isolation Forest
Isolation forest is anomaly detection method introduced by the paper Isolation based Anomaly Detecti ...
Download / Learn more Package Citations See dependency  
r2resize  
In-Text Resize for Images, Tables and Fancy Resize Containers in 'shiny', 'rmarkdown' and 'quarto' Documents
Automatic resizing toolbar for containers, images and tables. Various resizable or expandable contai ...
Download / Learn more Package Citations See dependency  
mlr3viz  
Visualizations for 'mlr3'
Visualization package of the 'mlr3' ecosystem. It features plots for mlr3 objects such as tasks, le ...
Download / Learn more Package Citations See dependency  
openxlsx  
Read, Write and Edit xlsx Files
Simplifies the creation of Excel .xlsx files by providing a high level interface to writing, stylin ...
Download / Learn more Package Citations See dependency  
EMVS  
The Expectation-Maximization Approach to Bayesian Variable Selection
An efficient expectation-maximization algorithm for fitting Bayesian spike-and-slab regularization p ...
Download / Learn more Package Citations See dependency  
lbfgs  
Limited-memory BFGS Optimization
A wrapper built around the libLBFGS optimization library by Naoaki Okazaki. The lbfgs package implem ...
Download / Learn more Package Citations See dependency  

26,264

R Packages

223,360

Dependencies

70,376

Author Associations

26,265

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA