Simulation of Forward Curve using PCA (principle component analysis)

Version 1.0.0.0 (691 KB) by Moeti Ncube
Method of simulation forward curves
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Updated 6 Jan 2011

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This program replicates the theory given in paper "Multi-Factor Models of the Forward Price Curve" by CARLOS BLANCO, DAVID SORONOW & PAUL STEFISZYN
Run simfwrdcurve.m first and then simfwrdcurv2.m.

simfwrdcurve.m computes the volatility functions to calculate the principal components for each month of the year by loading the historical daily forward curve data associated with each month. Each month has 48 forward contracts starting with prompt month and every month has differenct principle components (to account for seasonality)

simfwrdcurve2.m loads the volatility functions associated with each month calculated in simfwrdcurv.m and simulates the forward curve m months into the future starting from month (datesim) selected by user. It uses principle components associated with each month

Cite As

Moeti Ncube (2024). Simulation of Forward Curve using PCA (principle component analysis) (https://www.mathworks.com/matlabcentral/fileexchange/29940-simulation-of-forward-curve-using-pca-principle-component-analysis), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2009b
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes
1.0.0.0