Code covered by the BSD License
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covered_engine(X, T, mu, sigm...
covered_engine - Generate scenarios for a covered-call strategy with expiration.
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gbm_calibration(t0, X, t)
gbm_calibration - Calibrate a multivariate geometric Brownian motion process.
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gbm_call_price(X0, K, r0, T, ...
gbm_call_price - Black-Scholes call option pricing model for geometric Brownian motion prices.
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gbm_upcrossing_prob(X0, K, T,...
gbm_upcrossing_prob - Compute probability of an upcrossing of a geometric Brownian motion.
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uncovered_engine(X, T, ...
uncovered_engine - Generate scenarios for an uncovered and a covered buy-write strategy.
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cvarwebinar.m
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cvarwebinar_calibration.m
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cvarwebinar_normality.m
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cvarwebinar_optimization.m
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cvarwebinar_reality.m
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cvarwebinar_scenarios.m
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cvarwebinar_theory.m
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setlocalpaths.m
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View all files
Analyzing Investment Strategies with CVaR Portfolio Optimization
by Bob Taylor
18 Dec 2012
(Updated 18 Dec 2012)
Scripts and data to demonstrate the new PortfolioCVaR object in Financial Toolbox.
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Watch this File
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| File Information |
| Description |
A .zip file contains a series of scripts that were used in the MathWorks webinar "Analyzing Investment Strategies with CVaR Portfolio Optimization in MATLAB." The scripts demonstrate features of the PortfolioCVaR and Portfolio objects for normative analysis of a covered-call strategy. A readme.txt. file in the .zip folder describes how to use the scripts. |
| Required Products |
Financial Toolbox
Optimization Toolbox
Statistics Toolbox
MATLAB
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| MATLAB release |
MATLAB 8.0 (R2012b)
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| Other requirements |
Requires 64-bit processor and at least 2 GB RAM. |
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| Updates |
| 18 Dec 2012 |
Final corrections. |
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