Code covered by the BSD License
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BlackScholesCall(spot,K,r,vol...
Black-Scholes price of a European call
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ComputeCrossCorrelation(Y_F, ...
C = ComputeCrossCorrelation(Y_ZZ, Y_F, Corr_Y_F, exp_window_size)
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DisplayCumumlBars(C)
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EstimateUnitNormalCorr(Y_X, e...
C = EstimateUnitNormalCorr(Y_X, exp_window_size, shrink_factor)
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Goodness(Who,M)
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MvnRndMatchCrossCov(S, vararg...
X = MvnRndMatchCrossCov(S, J) simulates a panel of J scenarios of a
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SimulateFactorsResiduals(Corr...
[Y_F,U] = SimulateFactorsResiduals(Corr_Y_F, volU, J)
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X=MergeMargCop(W,F,U)
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[W,F,U]=SeparateMargCop(V)
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[Who, Num, G]=AcceptByS(OutOf...
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[Who, Num, G]=Naive(OutOfWho,...
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[Who, Num, G]=RejectByS(OutOf...
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[Who, g]=ExactNChooseK(OutOfW...
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interpne(V,Xi,nodelist,method)
interpne: Interpolates and extrapolates using n-linear interpolation (tensor product linear)
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S_Main.m
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S_Main.m
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S_Main.m
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View all files
Factors on Demand
by Attilio Meucci
05 Mar 2010
(Updated 09 May 2011)
Proper implementation of factor models: bottom-up estimation, top-down attribution
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| File Information |
| Description |
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 |
| MATLAB release |
MATLAB 7.8 (R2009a)
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| Updates |
| 23 Jun 2010 |
Added one case study, also detailed in the above article |
| 15 Jul 2010 |
Added case study |
| 09 May 2011 |
updated references |
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