Simulation of Forward Curve using PCA (principle component analysis)

Method of simulation forward curves
1,5K Downloads
Aktualisiert 6. Jan 2011

Lizenz anzeigen

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

Zitieren als

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. Abgerufen .

Kompatibilität der MATLAB-Version
Erstellt mit R2009b
Kompatibel mit allen Versionen
Plattform-Kompatibilität
Windows macOS Linux
Kategorien
Mehr zu Dimensionality Reduction and Feature Extraction finden Sie in Help Center und MATLAB Answers

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!
Version Veröffentlicht Versionshinweise
1.0.0.0