Tools (85)

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• assetsAnalysis.postAssetsAnalysisAbsorptionRatio

  Compute the absorption ratio associated to a universe of assets.

  References

  • Mark Kritzman, Yuanzhen Li, Sebastien Page and Roberto Rigobon, Principal Components as a Measure of Systemic Risk, The Journal of Portfolio Management Summer 2011, 37 (4) 112-126
• assetsAnalysis.postAssetsAnalysisTurbulenceIndex

  Compute the turbulence index associated to a universe of assets.

  References

  • M. Kritzman, Y. Li, Skulls, Financial Turbulence, and Risk Management,Financial Analysts Journal, Volume 66, Number 5, Pages 30-41, Year 2010
  • Kinlaw, W., Turkington, D. Correlation surprise. J Asset Manag 14, 385–399 (2013)
• assetsCorrelationMatrix.postAssetsCorrelationMatrix

  Compute the Pearson asset correlation matrix from either:

  • The asset returns
  • The asset covariance matrix

  References

  • Wikipedia, Correlation and Dependence
• assetsCorrelationMatrix.postAssetsCorrelationMatrixBounds

  Compute the lower bounds and the upper bounds of an asset correlation matrix associated to a given group of assets.

  References

  • Kawee Numpacharoen & Kornkanok Bunwong (2013) Boundaries of Correlation Adjustment with Applications to Financial Risk Management, Applied Mathematical Finance, 20:4, 403-414.
• assetsCorrelationMatrix.postAssetsCorrelationMatrixDenoised

  Compute a denoised asset correlation matrix, using one of the following methods:

  • The eigenvalues clipping method, described in the first reference, which is based on random matrix theory

  References

  • Laurent Laloux, Pierre Cizeau, Jean-Philippe Bouchaud, and Marc Potters, Noise Dressing of Financial Correlation Matrices, Phys. Rev. Lett. 83, 1467
• assetsCorrelationMatrix.postAssetsCorrelationMatrixDistance

  Compute the distance between an asset correlation matrix and a reference correlation matrix, using one of the following distance metrics:

  • Euclidean distance (default), which is the distance induced by the Frobenius norm
  • Correlation matrix distance, defined in the first reference, which corresponds to the cosine distance between the two vectorized asset correlation matrices
  • Bures distance, defined in the second reference

  References

  • M. Herdin, N. Czink, H. Ozcelik and E. Bonek, Correlation matrix distance, a meaningful measure for evaluation of non-stationary MIMO channels, 2005 IEEE 61st Vehicular Technology Conference, 2005, pp. 136-140 Vol. 1
  • Rajendra Bhatia, Tanvi Jain, Yongdo Lim, On the Bures–Wasserstein distance between positive definite matrices, Expositiones Mathematicae, Volume 37, Issue 2, 2019
• assetsCorrelationMatrix.postAssetsCorrelationMatrixEffectiveRank

  Compute the effective rank of an asset correlation matrix.

  References

  • Olivier Roy and Martin Vetterli, The effective rank: A measure of effective dimensionality, 15th European Signal Processing Conference, 2007
• assetsCorrelationMatrix.postAssetsCorrelationMatrixInformativeness

  Compute the informativeness of an asset correlation matrix, using one of the following distance metrics:

  • Euclidean distance (default), which is the distance induced by the Frobenius norm
  • Correlation matrix distance, defined in the second reference, which corresponds to the cosine distance between the two vectorized asset correlation matrices
  • Bures distance, defined in the third reference

  References

  • Austin J. Brockmeier and Tingting Mu and Sophia Ananiadou and John Y. Goulermas, Quantifying the Informativeness of Similarity Measurements, Journal of Machine Learning Research, 2017
  • M. Herdin, N. Czink, H. Ozcelik and E. Bonek, Correlation matrix distance, a meaningful measure for evaluation of non-stationary MIMO channels, 2005 IEEE 61st Vehicular Technology Conference, 2005, pp. 136-140 Vol. 1
  • Rajendra Bhatia, Tanvi Jain, Yongdo Lim, On the Bures–Wasserstein distance between positive definite matrices, Expositiones Mathematicae, Volume 37, Issue 2, 2019
• assetsCorrelationMatrix.postAssetsCorrelationMatrixNearest

  Compute the closest - in terms of the Frobenius norm - asset correlation matrix to an approximate asset correlation matrix, optionally keeping a selected number of correlations fixed.

  References

  • Nicholas J. Higham, Computing the Nearest Correlation Matrix—A Problem from Finance, IMA J. Numer. Anal. 22, 329–343, 2002.
• assetsCorrelationMatrix.postAssetsCorrelationMatrixRandom

  Generate an asset correlation matrix uniformly at random over the space of positive definite correlation matrices.

  References

  • Joe, H., Generating random correlation matrices based on partial correlations. Journal of Multivariate Analysis, 2006, 97, 2177-2189
• assetsCorrelationMatrix.postAssetsCorrelationMatrixShrinkage

  Compute an asset correlation matrix as a convex linear combination of an asset correlation matrix and a target correlation matrix, the target correlation matrix being either:

  • An equicorrelation matrix made of 1
  • An equicorrelation matrix made of 0
  • An equicorrelation matrix made of -1/(n-1), with n the number of assets
  • A provided correlation matrix

  References

  • Steiner, Andreas, Manipulating Valid Correlation Matrices
• assetsCorrelationMatrix.postAssetsCorrelationMatrixTheoryImplied

  Compute the theory-implied asset correlation matrix associated with:

  • A hierarchical classification of a universe of assets
  • An asset correlation matrix

  References

  • Lopez de Prado, Marcos Estimation of Theory-Implied Correlation Matrices (November 9, 2019)
• assetsCorrelationMatrix.postAssetsCorrelationMatrixValidation

  Validate whether a matrix is an asset correlation matrix.

  References

  • Wikipedia, Correlation and Dependence
• assetsCovarianceMatrix.postAssetsCovarianceMatrix

  Compute the covariance matrix of assets from either:

  • The asset correlation matrix and their volatilities (i.e., standard deviations)
  • The asset correlation matrix and their variances
  • The asset returns

  References

  • Wikipedia, Covariance Matrix
• assetsCovarianceMatrix.postAssetsCovarianceMatrixEffectiveRank

  Compute the effective rank of an asset covariance matrix.

  References

  • Olivier Roy and Martin Vetterli, The effective rank: A measure of effective dimensionality, 15th European Signal Processing Conference, 2007
• assetsCovarianceMatrix.postAssetsCovarianceMatrixExponentiallyWeighted

  Compute an exponentially weighted covariance matrix of assets returns.

  References

  • RiskMetrics Group. Longerstaey, J. (1996). RiskMetrics technical document, Technical Report fourth edition
• assetsCovarianceMatrix.postAssetsCovarianceMatrixValidation

  Validate whether a matrix is a covariance matrix.

  References

  • Wikipedia, Covariance Matrix
• assetsKurtosis.postAssetsKurtosis

  Compute the kurtosis of one or several asset(s), from the asset returns.

  References

  • Wikipedia, Kurtosis
• assetsPrices.postAssetsPricesAdjusted

  Compute the backward-adjusted prices of one or several asset(s) for one or several date(s) from:

  • Unadjusted prices
  • Capital distributions, like stock dividends
  • Splits, like stock splits

  The adjustment base date is chosen to be the last date for which unadjusted prices are available, which implies that:

  • The price on the last date for which unadjusted prices are available is left unadjusted
  • The price on any other date is adjusted based on the capital distributions and the splits which occurred between this date and the last date for which unadjusted prices are available

  References

  • Center for Research in Security Prices
• assetsPrices.postAssetsPricesAdjustedForward

  Compute the forward-adjusted prices of one or several asset(s) for one or several date(s) from:

  • Unadjusted prices
  • Capital distributions, like stock dividends
  • Splits, like stock splits

  The adjustment base date is chosen to be the first date for which unadjusted prices are available, which implies that:

  • The price on the first date for which unadjusted prices are available is left unadjusted
  • The price on any other date is adjusted based on the capital distributions and the splits which occurred between this date and the first date for which unadjusted prices are available

  References

  • Center for Research in Security Prices
• assetsReturns.postAssetsReturns

  Compute the arithmetic return(s) of one or several asset(s) for one or several time period(s).

  References

  • Wikipedia, Rate of Return
• assetsReturns.postAssetsReturnsAverage

  Compute the arithmetic average of the return(s) of one or several asset(s).

  References

  • Wikipedia, Arithmetic Average Rate of Return
• assetsReturnsSimulation.postAssetsReturnsSimulationBootstrap

  Simulate the return(s) of one or several asset(s) for one or several time period(s) using a bootstrap method.

  References

  • Efron, B. (1979), Bootstrap methods: Another look at the jackknife, The Annals of Statistics 7, 1-26
  • Politis, D. N. and Romano, J. P., A circular block resampling procedure for stationary data, in R. Lepage and L. Billard, eds, Exploring the Limits of Bootstrap, Wiley, New York, pp. 263-270
  • Politis, D. N. and Romano, J. P., The stationary bootstrap, Journal of the American Statistical Association 89, 1303-1313
• assetsSkewness.postAssetsSkewness

  Compute the skewness of one or several asset(s), from the asset returns.

  References

  • Wikipedia, Skewness
• assetsVariance.postAssetsVariance

  Compute the variance of one or several asset(s) from either:

  • The asset returns
  • The asset covariance matrix
  • The asset volatility(ies)

  References

  • Wikipedia, Variance
• assetsVolatility.postAssetsVolatility

  Compute the volatility (i.e., standard deviation) of one or several asset(s) from either:

  • The asset returns
  • The asset covariance matrix
  • The asset variance(s)

  References

  • Wikipedia, Standard Deviation
• factors.postFactorsResidualization

  Compute the residuals of a factor against a set of factors, using a returns-based linear regression analysis.

  References

  • Factor Research, Factor Exposure Analysis: Exploring Residualization
  • Catalina B. Garcia, Román Salmeron, Claudia Garcia & Jose Garcia (2019): Residualization: justification, properties and application, Journal of Applied Statistics
• portfolioAnalysis.postPortfolioAnalysisAlpha

  Compute the Jensen’s alpha of one or several portfolio(s) in the Capital Asset Pricing Model (CAPM).

  References

  • Carl R. Bacon, Practical Portfolio Performance Measurement and Attribution
• portfolioAnalysis.postPortfolioAnalysisBeta

  Compute the beta of one or several portfolio(s) in the Capital Asset Pricing Model (CAPM).

  References

  • Carl R. Bacon, Practical Portfolio Performance Measurement and Attribution
• portfolioAnalysis.postPortfolioAnalysisConditionalValueAtRisk

  Compute the conditional value at risk of one or several portfolio(s) from portfolio values.

  References

  • Wikipedia, Value at risk
  • Acerbi, C. and Tasche, D. (2002), Expected Shortfall: A Natural Coherent Alternative to Value at Risk. Economic Notes, 31: 379-388
• portfolioAnalysis.postPortfolioAnalysisContributionsReturn

  Perform a return contribution analysis of one or several portfolio(s), optionally using groups of assets.

  References

  • Carl R. Bacon, Practical Portfolio Performance Measurement and Attribution
• portfolioAnalysis.postPortfolioAnalysisContributionsRisk

  Perform a risk contribution analysis of one or several portfolio(s), optionally using groups of assets.

  References

  • Carl R. Bacon, Practical Portfolio Performance Measurement and Attribution
• portfolioAnalysis.postPortfolioAnalysisCorrelationSpectrum

  Compute the correlation spectrum of one or several portfolio(s).

  References

  • Tristan Froidure, Khalid Jalalzai and Yves Choueifaty, Portfolio Rho-Representativity, International Journal of Theoretical and Applied FinanceVol. 22, No. 07, 1950034 (2019)
• portfolioAnalysis.postPortfolioAnalysisDiversificationRatio

  Compute the diversification ratio of one or several portfolio(s).

  References

  • Yves Choueifaty and Yves Coignard, Toward Maximum Diversification, The Journal of Portfolio Management Fall 2008, 35 (1) 40-51
  • Tristan Froidure, Khalid Jalalzai and Yves Choueifaty, Portfolio Rho-Representativity, International Journal of Theoretical and Applied FinanceVol. 22, No. 07, 1950034 (2019)
• portfolioAnalysis.postPortfolioAnalysisDrawdowns

  Compute the drawdown function - also called the underwater equity curve -, as well as the worst 10 drawdowns of one or several portfolio(s).

  References

  • Wikipedia, Drawdown
• portfolioAnalysis.postPortfolioAnalysisEffectiveNumberOfBets

  Compute the effective number of bets of one or several portfolio(s).

  References

  • Meucci, Attilio and Santangelo, Alberto and Deguest, Romain, Risk Budgeting and Diversification Based on Optimized Uncorrelated Factors (November 10, 2015)
• portfolioAnalysis.postPortfolioAnalysisFactorsExposures

  Compute the exposures of one or several portfolio(s) to a set of factors, using a returns-based linear regression analysis.

  References

  • Measuring Factor Exposures: Uses and Abuses, Ronen Israel and Adrienne Ross, The Journal of Alternative Investments Summer 2017, 20 (1) 10-25
• portfolioAnalysis.postPortfolioAnalysisMeanVarianceEfficientFrontier

  Compute the discretized mean-variance efficient frontier associated to a list of assets, optionally subject to:

  • Minimum and maximum weights constraints
  • Maximum group weights constraints
  • Minimum and maximum portfolio exposure constraint

  References

  • Harry M. Markowitz, Portfolio Selection, Efficient Diversification of Investments, Second edition, Blackwell Publishers Inc.
• portfolioAnalysis.postPortfolioAnalysisMeanVarianceMinimumVarianceFrontier

  Compute the discretized mean-variance minimum variance frontier associated to a list of assets, optionally subject to:

  • Minimum and maximum weights constraints
  • Maximum group weights constraints
  • Minimum and maximum portfolio exposure constraint

  This endpoint is similar to the endpoint /portfolio/analysis/mean-variance/efficient-frontier, because the mean-variance efficient frontier is the "top" portion of the mean-variance minimum variance frontier.

  References

  • Harry M. Markowitz, Portfolio Selection, Efficient Diversification of Investments, Second edition, Blackwell Publishers Inc.
• portfolioAnalysis.postPortfolioAnalysisReturn

  Compute the arithmetic return of one or several portfolio(s) from either:

  • Portfolio assets arithmetic returns
  • Portfolio values

  References

  • Wikipedia, Rate of Return
  • Harry M. Markowitz, Portfolio Selection, Efficient Diversification of Investments, Second edition, Blackwell Publishers Inc.
• portfolioAnalysis.postPortfolioAnalysisReturnsAverage

  Compute the arithmetic average of the arithmetic return(s) of one or several portfolio(s).

  References

  • Wikipedia, Arithmetic Average Rate of Return
• portfolioAnalysis.postPortfolioAnalysisTrackingError

  Compute the tracking error between a benchmark and one or several portfolio(s).

  References

  • Wikipedia, Tracking error
  • Carl R. Bacon, Practical Portfolio Performance Measurement and Attribution
• portfolioAnalysis.postPortfolioAnalysisUlcerIndex

  Compute the Ulcer Index of one or several portfolio(s).

  References

  • Carl R. Bacon, Practical Portfolio Performance Measurement and Attribution
  • Peter G. Martin, Ulcer Index, An Alternative Approach to the Measurement of Investment Risk & Risk-Adjusted Performance
• portfolioAnalysis.postPortfolioAnalysisUlcerPerformanceIndex

  Compute the Ulcer Performance Index of one or several portfolio(s).

  References

  • Carl R. Bacon, Practical Portfolio Performance Measurement and Attribution
  • Peter G. Martin, Ulcer Index, An Alternative Approach to the Measurement of Investment Risk & Risk-Adjusted Performance
• portfolioAnalysis.postPortfolioAnalysisValueAtRisk

  Compute the value at risk of one or several portfolio(s) from portfolio values.

  References

  • Wikipedia, Value at risk
  • Acerbi, C. and Tasche, D. (2002), Expected Shortfall: A Natural Coherent Alternative to Value at Risk. Economic Notes, 31: 379-388
• portfolioAnalysis.postPortfolioAnalysisVolatility

  Compute the volatility (i.e., standard deviation) of one or several portfolio(s) from either:

  • Portfolio assets covariance matrix
  • Portfolio values

  References

  • Wikipedia, Standard Deviation
  • Carl R. Bacon, Practical Portfolio Performance Measurement and Attribution
  • Harry M. Markowitz, Portfolio Selection, Efficient Diversification of Investments, Second edition, Blackwell Publishers Inc.
• portfolioAnalysisSharpeRatio.postPortfolioAnalysisSharpeRatio

  Compute the Sharpe ratio of one or several portfolio(s) from either:

  • Portfolio assets arithmetic returns and assets covariance matrix
  • Portfolio values

  References

  • Carl R. Bacon, Practical Portfolio Performance Measurement and Attribution
  • Harry M. Markowitz, Portfolio Selection, Efficient Diversification of Investments, Second edition, Blackwell Publishers Inc.
• portfolioAnalysisSharpeRatio.postPortfolioAnalysisSharpeRatioBiasAdjusted

  Compute the Sharpe ratio of one or several portfolio(s), adjusted for small sample bias.

  References

  • Opdyke, J., Comparing Sharpe ratios: So where are the p-values?. J Asset Manag 8, 308–336 (2007)
• portfolioAnalysisSharpeRatio.postPortfolioAnalysisSharpeRatioConfidenceInterval

  Build a confidence interval for the Sharpe ratio of one or several portfolio(s).

  References

  • Opdyke, J.D., Comparing Sharpe ratios: So where are the p-values?. J Asset Manag 8, 308–336 (2007)
• portfolioAnalysisSharpeRatio.postPortfolioAnalysisSharpeRatioProbabilistic

  Compute the probabilistic Sharpe ratio of one or several portfolio(s).

  References

  • Opdyke, J.D., Comparing Sharpe ratios: So where are the p-values?. J Asset Manag 8, 308–336 (2007)
  • Bailey, David H. and Lopez de Prado, Marcos, The Sharpe Ratio Efficient Frontier (April 1, 2012). Journal of Risk, Vol. 15, No. 2, Winter 2012/13
• portfolioAnalysisSharpeRatio.postPortfolioAnalysisSharpeRatioProbabilisticMinimumTrackRecordLength

  Compute the minimum track record length of one or several portfolio(s).

  References

  • Bailey, David H. and Lopez de Prado, Marcos, The Sharpe Ratio Efficient Frontier (April 1, 2012). Journal of Risk, Vol. 15, No. 2, Winter 2012/13
• portfolioConstruction.postPortfolioConstructionInvestable

  Compute an investable portfolio as close as possible, in terms of assets weights, to a desired portfolio, taking into account:

  • The desired assets weights
  • The desired assets groups weights
  • The desired maximum assets groups weights
  • The prices of the assets
  • The portfolio value
  • The requirement to purchase some assets by round lots or by odd lots
  • The possibility to purchase some assets by a fractional quantity of shares
  • The requirement to purchase a minimum number of shares, or a minimum monetary value, for some assets

  References

  • Steiner, Andreas, Accuracy and Rounding in Portfolio Construction
• portfolioConstruction.postPortfolioConstructionMimicking

  Construct a portfolio as close as possible, in terms of returns, to a benchmark, optionally subject to:

  • Minimum and maximum weights constraints
  • Maximum group weights constraints
  • Minimum and maximum portfolio exposure constraints

  References

  • Konstantinos Benidis, Yiyong Feng, Daniel P. Palomar, Optimization Methods for Financial Index Tracking: From Theory to Practice, now publishers Inc (7 juin 2018)
• portfolioConstruction.postPortfolioConstructionRandom

  Construct one or several random portfolio(s), optionally subject to:

  • Minimum and maximum weights constraints
  • Minimum and maximum portfolio exposure constraints

  Because of the nature of the endpoint, subsequent calls with the same input data will result in different output data.

  References

  • William Thornton Shaw, Monte Carlo Portfolio Optimization for General Investor Risk-Return Objectives and Arbitrary Return Distributions: A Solution for Long-Only Portfolios
• portfolioOptimization.postPortfolioOptimizationEqualRiskContributions

  Compute the asset weights of the equal risk contributions portfolio, optionally subject to:

  • Minimum and maximum weights constraints

  References

  • Richard, Jean-Charles and Roncalli, Thierry, Constrained Risk Budgeting Portfolios: Theory, Algorithms, Applications & Puzzles
• portfolioOptimization.postPortfolioOptimizationEqualSharpeRatioContributions

  Compute the asset weights of the equal Sharpe Ratio contributions portfolio.

  References

  • Andreas Steiner, Sharpe Ratio Contribution and Attribution Analysis
• portfolioOptimization.postPortfolioOptimizationEqualVolatilityWeighted

  Compute the asset weights of the equal volatility-weighted portfolio.

  References

  • Tristan Froidure, Khalid Jalalzai and Yves Choueifaty, Portfolio Rho-Representativity, International Journal of Theoretical and Applied FinanceVol. 22, No. 07, 1950034 (2019)
• portfolioOptimization.postPortfolioOptimizationEqualWeighted

  Compute the asset weights of the equal-weighted portfolio.

  References

  • Victor DeMiguel and al., Optimal Versus Naive Diversification: How Inefficient is the 1/N Portfolio Strategy?
• portfolioOptimization.postPortfolioOptimizationHierarchicalRiskParity

  Compute the asset weights of the hierarchical risk parity portfolio, optionally subject to:

  • Minimum and maximum weights constraints
  • Minimum and maximum portfolio exposure constraints

  References

  • Lopez de Prado, M. (2016). Building diversified portfolios that outperform out-of-sample. Journal of Portfolio Management, 42(4), 59–69
  • Johann Pfitzinger & Nico Katzke, 2019. A constrained hierarchical risk parity algorithm with cluster-based capital allocation. Working Papers 14/2019, Stellenbosch University, Department of Economics
• portfolioOptimization.postPortfolioOptimizationHierarchicalRiskParityClusteringBased

  Compute the asset weights of the hierarchical clustering-based risk parity portfolio, optionally subject to:

  • Minimum and maximum weights constraints
  • Minimum and maximum portfolio exposure constraints

  References

  • Machine Learning for Asset Management: New Developments and Financial Applications, Emmanuel Jurczenko, Chapter 9, Harald Lohre,Carsten Rother,Kilian Axel Schäfer, Hierarchical Risk Parity: Accounting for Tail Dependencies in Multi-asset Multi-factor Allocations
  • Thomas Raffinot, Hierarchical Clustering-Based Asset Allocation, The Journal of Portfolio Management Multi-Asset Special Issue 2018, 44 (2) 89-99
  • Raffinot, Thomas, The Hierarchical Equal Risk Contribution Portfolio
  • Johann Pfitzinger & Nico Katzke, 2019. A constrained hierarchical risk parity algorithm with cluster-based capital allocation. Working Papers 14/2019, Stellenbosch University, Department of Economics
• portfolioOptimization.postPortfolioOptimizationInverseVarianceWeighted

  Compute the asset weights of the inverse variance-weighted portfolio.

  References

  • Raul Leote de Carvalho and al., Demystifying Equity Risk-Based Strategies: A Simple Alpha Plus Beta Description
• portfolioOptimization.postPortfolioOptimizationInverseVolatilityWeighted

  Compute the asset weights of the inverse volatility-weighted portfolio.

  References

  • Raul Leote de Carvalho and al., Demystifying Equity Risk-Based Strategies: A Simple Alpha Plus Beta Description
• portfolioOptimization.postPortfolioOptimizationMarketCapitalizationWeighted

  Compute the asset weights of the market capitalization-weighted portfolio.

  References

  • Wikipedia, Capitalization-weighted Index
• portfolioOptimization.postPortfolioOptimizationMaximumDecorrelation

  Compute the asset weights of the maximum decorrelation portfolio, optionally subject to:

  • Minimum and maximum weights constraints
  • Maximum group weights constraints
  • Minimum and maximum portfolio exposure constraints

  References

  • F. Goltz, S. Sivasubramanian, Scientific Beta Maximum Decorrelation Indices
• portfolioOptimization.postPortfolioOptimizationMaximumUlcerPerformanceIndex

  Compute the asset weights of the maximum Ulcer Performance Index portfolio, optionally subject to:

  • Minimum and maximum weights constraints
  • Maximum group weights constraints
  • Minimum and maximum portfolio exposure constraints

  Notes:

  • This endpoint will return an error if the maximum Ulcer Performance Index portfolio has a negative Ulcer Performance Index

  References

  • Peter G. Martin, Ulcer Index, An Alternative Approach to the Measurement of Investment Risk & Risk-Adjusted Performance
  • A. Chekhlov, S. Uryasev, M. Zabarankin, Portfolio Optimization with Drawdown Constraints, Supply Chain and Finance, p 209-228
  • A. Chekhlov, S. Uryasev, M. Zabarankin, Drawdown Measure in Portfolio Optimization, International Journal of Theoretical and Applied FinanceVol. 08, No. 01, pp. 13-58 (2005)
• portfolioOptimization.postPortfolioOptimizationMinimumCorrelation

  Compute the asset weights of the (heuristic) minimum correlation portfolio, which is a portfolio built using the Minimum Correlation Algorithm discovered by David Varadi.

  References

  • CSSA, Minimum Correlation Algorithm Paper Release
• portfolioOptimization.postPortfolioOptimizationMinimumUlcerIndex

  Compute the asset weights of the minimum Ulcer Index portfolio, optionally subject to:

  • Minimum and maximum weights constraints
  • Maximum group weights constraints
  • Minimum and maximum portfolio exposure constraints

  References

  • Peter G. Martin, Ulcer Index, An Alternative Approach to the Measurement of Investment Risk & Risk-Adjusted Performance
  • A. Chekhlov, S. Uryasev, M. Zabarankin, Portfolio Optimization with Drawdown Constraints, Supply Chain and Finance, p 209-228
  • A. Chekhlov, S. Uryasev, M. Zabarankin, Drawdown Measure in Portfolio Optimization, International Journal of Theoretical and Applied FinanceVol. 08, No. 01, pp. 13-58 (2005)
• portfolioOptimization.postPortfolioOptimizationMostDiversified

  Compute the asset weights of the most diversified portfolio, optionally subject to:

  • Minimum and maximum weights constraints
  • Maximum group weights constraints
  • Minimum and maximum portfolio exposure constraints

  References

  • Yves Choueifaty and Yves Coignard, Toward Maximum Diversification, The Journal of Portfolio Management Fall 2008, 35 (1) 40-51
• portfolioOptimizationMeanVariance.postPortfolioOptimizationMaximumReturn

  Compute the asset weights of the maximum return portfolio, optionally subject to:

  • Minimum and maximum weights constraints
  • Maximum group weights constraints
  • Minimum and maximum portfolio exposure constraints

  References

  • Harry M. Markowitz, Portfolio Selection, Efficient Diversification of Investments, Second edition, Blackwell Publishers Inc.
• portfolioOptimizationMeanVariance.postPortfolioOptimizationMaximumReturnDiversified

  Compute the asset weights of the diversified maximum return portfolio, as defined in the first reference, optionally subject to:

  • Minimum and maximum weights constraints
  • Maximum group weights constraints
  • Minimum and maximum portfolio exposure constraints

  The diversification measure used in the optimization procedure is the Herfindahl-Hirschman Index of the assets weights.

  References

  • Alejandro Corvalan, 2005. Well Diversified Efficient Portfolios, Working Papers Central Bank of Chile 336, Central Bank of Chile
  • Bouchaud, Jean-Philippe and Potters, Marc and Aguilar, Jean-Pierre, Missing Information and Asset Allocation, arXiv, 1997
  • Harry M. Markowitz, Portfolio Selection, Efficient Diversification of Investments, Second edition, Blackwell Publishers Inc.
• portfolioOptimizationMeanVariance.postPortfolioOptimizationMaximumReturnSubsetResamplingBased

  Compute the asset weights of the subset resampling-based maximum return portfolio, following the methodology described in the first and the second references, optionally subject to:

  • Minimum and maximum weights constraints
  • Maximum group weights constraints
  • Minimum and maximum portfolio exposure constraints

  References

  • CSSA, Random Subspace Optimization (RSO)
  • Subset Optimization for Asset Allocation,Benjamin J. Gillen
  • Harry M. Markowitz, Portfolio Selection, Efficient Diversification of Investments, Second edition, Blackwell Publishers Inc.
• portfolioOptimizationMeanVariance.postPortfolioOptimizationMaximumSharpeRatio

  Compute the asset weights of the maximum Sharpe ratio portfolio, optionally subject to:

  • Minimum and maximum weights constraints
  • Maximum group weights constraints
  • Minimum and maximum portfolio exposure constraints

  References

  • Harry M. Markowitz, Portfolio Selection, Efficient Diversification of Investments, Second edition, Blackwell Publishers Inc.
• portfolioOptimizationMeanVariance.postPortfolioOptimizationMaximumSharpeRatioDiversified

  Compute the asset weights of the diversified maximum Sharpe ratio portfolio, as defined in the first reference, optionally subject to:

  • Minimum and maximum weights constraints
  • Maximum group weights constraints
  • Minimum and maximum portfolio exposure constraints

  The diversification measure used in the optimization procedure is the Herfindahl-Hirschman Index of the assets weights.

  References

  • Alejandro Corvalan, 2005. Well Diversified Efficient Portfolios, Working Papers Central Bank of Chile 336, Central Bank of Chile
  • Bouchaud, Jean-Philippe and Potters, Marc and Aguilar, Jean-Pierre, Missing Information and Asset Allocation, arXiv, 1997
  • Harry M. Markowitz, Portfolio Selection, Efficient Diversification of Investments, Second edition, Blackwell Publishers Inc.
• portfolioOptimizationMeanVariance.postPortfolioOptimizationMaximumSharpeRatioSubsetResamplingBased

  Compute the asset weights of the susbet resampling-based maximum Sharpe ratio portfolio, following the methodology described in the first and the second references, optionally subject to:

  • Minimum and maximum weights constraints
  • Maximum group weights constraints
  • Minimum and maximum portfolio exposure constraints

  References

  • CSSA, Random Subspace Optimization (RSO)
  • Subset Optimization for Asset Allocation,Benjamin J. Gillen
  • Harry M. Markowitz, Portfolio Selection, Efficient Diversification of Investments, Second edition, Blackwell Publishers Inc.
• portfolioOptimizationMeanVariance.postPortfolioOptimizationMeanVarianceEfficient

  Compute the asset weights of a mean-variance efficient portfolio, optionally subject to:

  • Minimum and maximum weights constraints
  • Maximum group weights constraints
  • Minimum and maximum portfolio exposure constraints

  A mean-variance efficient portfolio is a portfolio belonging to the mean-variance efficient frontier.

  References

  • Harry M. Markowitz, Portfolio Selection, Efficient Diversification of Investments, Second edition, Blackwell Publishers Inc.
• portfolioOptimizationMeanVariance.postPortfolioOptimizationMeanVarianceEfficientDiversified

  Compute the asset weights of a diversified mean-variance efficient portfolio, as defined in the first reference, optionally subject to:

  • Minimum and maximum weights constraints
  • Maximum group weights constraints
  • Minimum and maximum portfolio exposure constraints

  The diversification measure used in the optimization procedure is the Herfindahl-Hirschman Index of the assets weights.

  A diversified mean-variance efficient portfolio does NOT belong to the mean-variance efficient frontier, but is close to this frontier.

  References

  • Alejandro Corvalan, 2005. Well Diversified Efficient Portfolios, Working Papers Central Bank of Chile 336, Central Bank of Chile
  • Bouchaud, Jean-Philippe and Potters, Marc and Aguilar, Jean-Pierre, Missing Information and Asset Allocation, arXiv, 1997
  • Harry M. Markowitz, Portfolio Selection, Efficient Diversification of Investments, Second edition, Blackwell Publishers Inc.
• portfolioOptimizationMeanVariance.postPortfolioOptimizationMeanVarianceEfficientSubsetResamplingBased

  Compute the asset weights of a subset resampling-based mean-variance efficient portfolio, following the methodology described in the first and the second references, optionally subject to:

  • Minimum and maximum weights constraints
  • Maximum group weights constraints
  • Minimum and maximum portfolio exposure constraints

  References

  • CSSA, Random Subspace Optimization (RSO)
  • Subset Optimization for Asset Allocation,Benjamin J. Gillen
  • Harry M. Markowitz, Portfolio Selection, Efficient Diversification of Investments, Second edition, Blackwell Publishers Inc.
• portfolioOptimizationMeanVariance.postPortfolioOptimizationMinimumVariance

  Compute the asset weights of the minimum variance portfolio, optionally subject to:

  • Minimum and maximum weights constraints
  • Maximum group weights constraints
  • Minimum and maximum portfolio exposure constraints

  References

  • Harry M. Markowitz, Portfolio Selection, Efficient Diversification of Investments, Second edition, Blackwell Publishers Inc.
• portfolioOptimizationMeanVariance.postPortfolioOptimizationMinimumVarianceDiversified

  Compute the asset weights of the diversified minimum variance portfolio, as defined in the first reference, optionally subject to:

  • Minimum and maximum weights constraints
  • Maximum group weights constraints
  • Minimum and maximum portfolio exposure constraints

  The diversification measure used in the optimization procedure is the Herfindahl-Hirschman Index of the assets weights.

  References

  • Alejandro Corvalan, 2005. Well Diversified Efficient Portfolios, Working Papers Central Bank of Chile 336, Central Bank of Chile
  • Bouchaud, Jean-Philippe and Potters, Marc and Aguilar, Jean-Pierre, Missing Information and Asset Allocation, arXiv, 1997
  • Harry M. Markowitz, Portfolio Selection, Efficient Diversification of Investments, Second edition, Blackwell Publishers Inc.
• portfolioOptimizationMeanVariance.postPortfolioOptimizationMinimumVarianceSubsetResamplingBased

  Compute the asset weights of the subset resampling-based minimum variance portfolio, following the methodology described in the first and the second references, optionally subject to:

  • Minimum and maximum weights constraints
  • Maximum group weights constraints
  • Minimum and maximum portfolio exposure constraints

  References

  • CSSA, Random Subspace Optimization (RSO)
  • Subset Optimization for Asset Allocation,Benjamin J. Gillen
  • Harry M. Markowitz, Portfolio Selection, Efficient Diversification of Investments, Second edition, Blackwell Publishers Inc.
• portfolioSimulation.postPortfolioSimulationRebalancingDriftWeight

  Simulate the evolution of one or several portfolio(s) over one or several time period(s), the portfolio(s) being never rebalanced (a.k.a. buy and hold).

  References

  • Hillion, Pierre, The Ex-Ante Rebalancing Premium (March 11, 2016). INSEAD Working Paper No. 2016/15/FIN
• portfolioSimulation.postPortfolioSimulationRebalancingFixedWeight

  Simulate the evolution of one or several portfolio(s) over one or several time period(s), the portfolio(s) being rebalanced toward fixed weights at the beginning of each time period.

  References

  • Hillion, Pierre, The Ex-Ante Rebalancing Premium (March 11, 2016). INSEAD Working Paper No. 2016/15/FIN
• portfolioSimulation.postPortfolioSimulationRebalancingRandomWeight

  Simulate the evolution of one or several portfolio(s) over one or several time period(s), the portfolio(s) being rebalanced toward random weights at the beginning of each time period.

  References

  • R Stein, Not fooled by randomness: Using random portfolios to analyse investment funds, Investment Analysts Journal, 43:79, 1-15, DOI: 10.1080/10293523.2014.11082564
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