Factors on Demand

Proper implementation of factor models: bottom-up estimation, top-down attribution
Updated 9 May 2011

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Three case studies: random matrix theory for estimation vs. cross-sectional model for attribution; hedging based on full-repricing instead of Black-Scholes deltas; heuristcs for best K attribution/hedging factors out N

To walk through the code and for a thorough description, see
Meucci A., "Factors on Demand",

Latest version of article and code available at http://symmys.com/node/164

Cite As

Attilio Meucci (2024). Factors on Demand (https://www.mathworks.com/matlabcentral/fileexchange/26853-factors-on-demand), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2009a
Compatible with any release
Platform Compatibility
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Version Published Release Notes

updated references

Added case study

Added one case study, also detailed in the above article