RiskPortfolios: RiskPortfolios: Computation of risk-based portfolios in R

In ArdiaD/RiskPortfolios: Computation of Risk-Based Portfolios

Description

RiskPortfolios (Ardia et al., 2017) is an R package for constructing risk-based portfolios dedicated to portfolio managers and quantitative analysts. It provides a set of functionalities to build mean-variance, minimum variance, inverse-volatility weighted (Leote et al., 2012), equal-risk-contribution (Maillard et al. 2010), maximum diversification (Choueifaty and Coignard, 2008), and risk-efficient (Amenc et al., 2011) portfolios. Optimization is achieved with the R functions solve.QP and slsqp. Long or gross constraints can be added to the optimizer. As risk-based portfolios are mainly based on covariances, the package also provides a large set of covariance matrix estimators. A simulation study relying on the package is described in Ardia et al. (2017).

Functions

• optimalPortfolio: Optimization of portfolios.

• meanEstimation: Computation of expected returns.

• covEstimation: Computation of covariance matrix.

• semidevEstimation: Computation of semi-deviation.

Update

The latest version of the package is available at https://github.com/ArdiaD/RiskPortfolios.

Note

By using RiskPortfolios you agree to the following rules: (1) You must cite Ardia et al. (2017) in working papers and published papers that use RiskPortfolios (use citation("RiskPortfolios")), (2) you must place the URL https://CRAN.R-project.org/package=RiskPortfolios in a footnote to help others find RiskPortfolios, and (3) you assume all risk for the use of RiskPortfolios.

Author(s)

David Ardia, Kris Boudt and Jean-Philippe Gagnon-Fleury.

References

Amenc, N., Goltz, F., Martellini, L., Retowsky, P. (2011). Efficient indexation: An alternative to cap-weighted indices. Journal of Investment Management 9(4), pp.1-23.

Ardia, D., Boudt, K. (2015). Implied expected returns and the choice of a mean-variance efficient portfolio proxy. Journal of Portfolio Management 41(4), pp.66-81. doi: 10.3905/jpm.2015.41.4.068

Ardia, D., Bolliger, G., Boudt, K., Gagnon-Fleury, J.-P. (2017). The Impact of covariance misspecification in risk-based portfolios. Annals of Operations Research 254(1-2), pp.1-16. doi: 10.1007/s10479-017-2474-7

Ardia, D., Boudt, K., Gagnon-Fleury, J.-P. (2017). RiskPortfolios: Computation of risk-based portfolios in R. Journal of Open Source Software 10(2). doi: 10.21105/joss.00171

Choueifaty, Y., Coignard, Y. (2008). Toward maximum diversification. Journal of Portfolio Management 35(1), pp.40-51.

Choueifaty, Y., Froidure, T., Reynier, J. (2013). Properties of the most diversified portfolio. Journal of Investment Strategies 2(2), pp.49-70.

Das, S., Markowitz, H., Scheid, J., Statman, M. (2010). Portfolio optimization with mental accounts. Journal of Financial and Quantitative Analysis 45(2), pp.311-334.

DeMiguel, V., Garlappi, L., Uppal, R. (2009). Optimal versus naive diversification: How inefficient is the 1/n portfolio strategy. Review of Financial Studies 22(5), pp.1915-1953.

Fan, J., Zhang, J., Yu, K. (2012). Vast portfolio selection with gross-exposure constraints. Journal of the American Statistical Association 107(498), pp.592-606.

Maillard, S., Roncalli, T., Teiletche, J. (2010). The properties of equally weighted risk contribution portfolios. Journal of Portfolio Management 36(4), pp.60-70.

Martellini, L. (2008). Towards the design of better equity benchmarks. Journal of Portfolio Management 34(4), Summer,pp.34-41.

ArdiaD/RiskPortfolios documentation built on May 22, 2021, 4:35 a.m.