Factors on Demand
version 1.6.0.0 (4.08 MB) by
Attilio Meucci
Proper implementation of factor models: bottom-up estimation, top-down attribution
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 athttp://symmys.com/node/164
Cite As
Attilio Meucci (2021).Factors on Demand(//www.tianjin-qmedu.com/matlabcentral/fileexchange/26853-factors-on-demand), MATLAB Central File Exchange. Retrieved.
MATLAB Release Compatibility
Created with R2009a
Compatible with any release
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