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| tawny-package | Provides various portfolio optimization strategies including random matrix theory and shrinkage estimators |
| classify | Optimize a portfolio using the specified correlation filter |
| clean.bouchaud | Filter noise from a correlation matrix using RMT to identify the noise |
| compare.EqualWeighted | Calculate some portfolio statistics and compare with other portfolios or benchmarks |
| compare.Market | Calculate some portfolio statistics and compare with other portfolios or benchmarks |
| cor.empirical | Filter noise from a correlation matrix using RMT to identify the noise |
| cor.mean | Shrink the covariance matrix towards some global mean |
| cov.prior.cc | Shrink the covariance matrix towards some global mean |
| cov.prior.identity | Shrink the covariance matrix towards some global mean |
| cov.sample | Shrink the covariance matrix towards some global mean |
| cov.shrink | Shrink the covariance matrix towards some global mean |
| denoise | Filter noise from a correlation matrix using RMT to identify the noise |
| divergence | Measure the divergence and stability between two correlation matrices |
| divergenceLimit.kl | Measure the divergence and stability between two correlation matrices |
| ensure | Utility functions for creating portfolios of returns and other functions |
| filter.RMT | Filter noise from a correlation matrix using RMT to identify the noise |
| getCorFilter.Raw | Optimize a portfolio using the specified correlation filter |
| getCorFilter.RMT | Optimize a portfolio using the specified correlation filter |
| getCorFilter.Sample | Optimize a portfolio using the specified correlation filter |
| getCorFilter.Shrinkage | Optimize a portfolio using the specified correlation filter |
| getCorFilter.ShrinkageM | Optimize a portfolio using the specified correlation filter |
| getIndexComposition | Utility functions for creating portfolios of returns and other functions |
| getPortfolioReturns | Utility functions for creating portfolios of returns and other functions |
| getRandomMatrix | Filter noise from a correlation matrix using RMT to identify the noise |
| mp.density.hist | Filter noise from a correlation matrix using RMT to identify the noise |
| mp.density.kernel | Filter noise from a correlation matrix using RMT to identify the noise |
| mp.eigen.max | Filter noise from a correlation matrix using RMT to identify the noise |
| mp.eigen.min | Filter noise from a correlation matrix using RMT to identify the noise |
| mp.fit.hist | Filter noise from a correlation matrix using RMT to identify the noise |
| mp.fit.kernel | Filter noise from a correlation matrix using RMT to identify the noise |
| mp.lambdas | Filter noise from a correlation matrix using RMT to identify the noise |
| mp.rho | Filter noise from a correlation matrix using RMT to identify the noise |
| mp.theory | Filter noise from a correlation matrix using RMT to identify the noise |
| optimizePortfolio | Optimize a portfolio using the specified correlation filter |
| p.optimize | Optimize a portfolio using the specified correlation filter |
| plotDivergenceLimit.kl | Measure the divergence and stability between two correlation matrices |
| plotPerformance | Calculate some portfolio statistics and compare with other portfolios or benchmarks |
| portfolioPerformance | Calculate some portfolio statistics and compare with other portfolios or benchmarks |
| portfolioReturns | Calculate some portfolio statistics and compare with other portfolios or benchmarks |
| r.normalize | Filter noise from a correlation matrix using RMT to identify the noise |
| shrinkage.c | Shrink the covariance matrix towards some global mean |
| shrinkage.intensity | Shrink the covariance matrix towards some global mean |
| shrinkage.p | Shrink the covariance matrix towards some global mean |
| shrinkage.r | Shrink the covariance matrix towards some global mean |
| sp500 | A (mostly complete) subset of the SP500 with 250 data points |
| sp500.subset | A subset of the SP500 with 200 data points |
| stabilityLimit.kl | Measure the divergence and stability between two correlation matrices |
| tawny | Provides various portfolio optimization strategies including random matrix theory and shrinkage estimators |