PortfolioAnalytics (version 2.0.0)

Portfolio Analysis, Including Numerical Methods for Optimization of Portfolios

Description

Portfolio optimization and analysis routines and graphics.

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install.packages('PortfolioAnalytics')

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2,274

Version

2.0.0

License

GPL-3

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Repository

https://github.com/braverock/PortfolioAnalytics

Maintainer

Brian G Peterson

Last Published

July 3rd, 2024

Functions in PortfolioAnalytics (2.0.0)

HHI

Concentration of weights

MycovRobMcd

Control settings for custom.covRob.Mcd

MycovRobTSGS

Control settings for custom.covRob.TSGS

ac.ranking

Asset Ranking

PortfolioAnalytics-package

Numeric methods for optimization of portfolios

add.sub.portfolio

Add sub-portfolio

barplotGroupWeights

barplot of group weights by group or category

center

Center

centroid.complete.mc

Complete Cases Centroid

backtest.plot

generate plots of the cumulative returns and drawdown for back-testing

centroid.sectors

Multiple Sectors Centroid

black.litterman

Black Litterman Estimates

box_constraint

constructor for box_constraint.

applyFUN

Apply a risk or return function to a set of weights

centroid.buckets

Buckets Centroid

chart.EfficientFrontierCompare

Overlay the efficient frontiers of different minRisk portfolio objects on a single plot.

chart.EfficientFrontierOverlay

Plot multiple efficient frontiers

chart.Weights

boxplot of the weights of the optimal portfolios

chart.RiskReward

classic risk reward scatter

chart.RiskBudget

Generic method to chart risk contribution

chart.GroupWeights

Chart weights by group or category

cokurtosisMF

Cokurtosis Matrix Estimate

check_constraints

check if a set of weights satisfies the constraints

centroid.sign

Positive and Negative View Centroid

chart.Concentration

Classic risk reward scatter and concentration

combine.optimizations

Combine objects created by optimize.portfolio

cokurtosisSF

Cokurtosis Matrix Estimate

constrained_objective

calculate a numeric return value for a portfolio based on a set of constraints and objectives

combine.portfolios

Combine a list of portfolio objects

custom.covRob.TSGS

Compute returns mean vector and covariance matrix with custom.covRob.TSGS

custom.covRob.Mcd

Compute returns mean vector and covariance matrix with custom.covRob.Mcd

custom.covRob.MM

Compute returns mean vector and covariance matrix with custom.covRob.MM

create.EfficientFrontier

create an efficient frontier

coskewnessMF

Coskewness Matrix Estimate

coskewnessSF

Coskewness Matrix Estimate

diversification

Function to compute diversification as a constraint

covarianceSF

Covariance Matrix Estimate

covarianceMF

Covariance Matrix Estimate

etl_milp_opt

Minimum ETL MILP Optimization

custom.covRob.Rocke

Compute returns mean vector and covariance matrix with custom.covRob.Rocke

etl_opt

Minimum ETL LP Optimization

chart.EF.Weights

Chart weights along an efficient frontier

constraint_v1

constructors for class constraint

diversification_constraint

constructor for diversification_constraint

chart.EfficientFrontier

Chart the efficient frontier and risk-return scatter

constraint_ROI

constructor for class constraint_ROI

extractStats

extract some stats and weights from a portfolio run via optimize.portfolio

equal.weight

Create an equal weight portfolio

gmv_opt_leverage

GMV/QU QP Optimization with Turnover Constraint

gmv_opt_ptc

GMV/QU QP Optimization with Proportional Transaction Cost Constraint

extractCovariance

Covariance Estimate

leverage_exposure_constraint

constructor for leverage_exposure_constraint

get_constraints

Helper function to get the enabled constraints out of the portfolio object When the v1_constraint object is instantiated via constraint, the arguments min_sum, max_sum, min, and max are either specified by the user or default values are assigned. These are required by other functions such as optimize.portfolio and constrained_objective . This function will check that these variables are in the portfolio object in the constraints list. We will default to min_sum=1 and max_sum=1 if leverage constraints are not specified. We will default to min=-Inf and max=Inf if box constraints are not specified. This function is used at the beginning of optimize.portfolio and other functions to extract the constraints from the portfolio object. We Use the same naming as the v1_constraint object.

gmv_opt

GMV/QU QP Optimization

maxret_milp_opt

Maximum Return MILP Optimization

extractEfficientFrontier

Extract the efficient frontier data points

extractCokurtosis

Cokurtosis Estimate

mult.portfolio.spec

Multple Layer Portfolio Specification

extractWeights

Extract weights from a portfolio run via optimize.portfolio or optimize.portfolio.rebalancing

extractCoskewness

Coskewness Estimate

fn_map

mapping function to transform or penalize weights that violate constraints

generatesequence

create a sequence of possible weights for random or brute force portfolios

is.constraint

check function for constraints

inverse.volatility.weight

Create an inverse volatility weighted portfolio

meanvar.efficient.frontier

Generate the efficient frontier for a mean-variance portfolio

factor_exposure_constraint

Constructor for factor exposure constraint

group_fail

Test if group constraints have been violated

gmv_opt_toc

GMV/QU QP Optimization with Turnover Constraint

extract_risk

extract the risk value when knowing the weights

indexes

Six Major Economic Indexes

extractGroups

Extract the group and/or category weights

group_constraint

constructor for group_constraint

pHist

Generates histogram

name.replace

utility function to replace awkward named from unlist

optimize.portfolio.rebalancing

Portfolio Optimization with Rebalancing Periods

portfolio.spec

constructor for class portfolio

optimize.portfolio

Constrained optimization of portfolios

print.portfolio

Printing Portfolio Specification Objects

minmax_objective

constructor for class tmp_minmax_objective

optimize.portfolio.parallel

Execute multiple optimize.portfolio calls, presumably in parallel

extractObjectiveMeasures

Extract the objective measures

meucci.ranking

Asset Ranking

insert_objectives

Insert a list of objectives into the objectives slot of a portfolio object

insert_constraints

Insert a list of constraints into the constraints slot of a portfolio object

maxret_opt

Maximum Return LP Optimization

is.objective

check class of an objective object

is.portfolio

check function for portfolio

print.summary.optimize.portfolio.rebalancing

Printing summary output of optimize.portfolio.rebalancing

portfolio_risk_objective

constructor for class portfolio_risk_objective

meucci.moments

Compute moments

plot.optimize.portfolio.DEoptim

plot method for objects of class optimize.portfolio

print.summary.optimize.portfolio

Printing summary output of optimize.portfolio

quadratic_utility_objective

constructor for quadratic utility objective

plotFrontiers

Generate efficient frontiers plot by providing frontiers.

meanetl.efficient.frontier

Generate the efficient frontier for a mean-etl portfolio

meaneqs.efficient.frontier

Generate the efficient frontier for a mean-EQS portfolio

portfolio.moments.bl

Portfolio Moments

set.portfolio.moments

Portfolio Moments

print.constraint

print method for constraint objects

portfolio.moments.boudt

Portfolio Moments

random_walk_portfolios

deprecated random portfolios wrapper until we write a random trades function

print.optimize.portfolio.ROI

Printing output of optimize.portfolio

risk_budget_objective

constructor for class risk_budget_objective

randomize_portfolio

version 2 generate random permutations of a portfolio seed meeting your constraints on the weights of each asset

print.optimize.portfolio.rebalancing

Printing output of optimize.portfolio.rebalancing

return_constraint

constructor for return_constraint

objective

constructor for class 'objective'

print.efficient.frontier

Print an efficient frontier object

meanrisk.efficient.frontier

Generate multiple efficient frontiers for the same portfolio

opt.outputMvo

Optimal Portfolio Weights and Performance Values

pos_limit_fail

function to check for violation of position limits constraints

regime.portfolios

Regime Portfolios

randomize_portfolio_v1

Random portfolio sample method

rp_grid

Generate random portfolios based on grid search method

transaction_cost_constraint

constructor for transaction_cost_constraint

weight_sum_constraint

constructor for weight_sum_constraint

turnover

Calculates turnover given two vectors of weights. This is used as an objective function and is called when the user adds an objective of type turnover with add.objective

statistical.factor.model

Statistical Factor Model

position_limit_constraint

constructor for filter_constraint

random_portfolios_v1

generate an arbitary number of constrained random portfolios

scatterFUN

Apply a risk or return function to asset returns

random_portfolios

version 2 generate an arbitary number of constrained random portfolios

rp_transform

Transform a weights vector to satisfy constraints

rp_sample

Generate random portfolios using the sample method

turnover_objective

constructor for class turnover_objective

return_objective

constructor for class return_objective

rp_simplex

Generate random portfolios using the simplex method

turnover_constraint

constructor for turnover_constraint

trailingFUN

apply a function over a configurable trailing period

summary.portfolio

Summarize Portfolio Specification Objects

update_constraint_v1tov2

Helper function to update v1_constraint objects to v2 specification in the portfolio object

summary.efficient.frontier

Summarize an efficient frontier object

update.constraint

function for updating constrints, not well tested, may be broken

set.portfolio.moments_v1

set portfolio moments for use by lower level optimization functions

summary.optimize.portfolio

Summarizing output of optimize.portfolio

summary.optimize.portfolio.rebalancing

summary method for optimize.portfolio.rebalancing

var.portfolio

Calculate portfolio variance

weight_concentration_objective

Constructor for weight concentration objective

BlackLittermanFormula

Computes the Black-Litterman formula for the moments of the posterior normal.

add.constraint

General interface for adding and/or updating optimization constraints.

add.objective

General interface for adding optimization objectives, including risk, return, and risk budget

CCCgarch.MM

compute comoments for use by lower level optimization functions when the conditional covariance matrix is a CCC GARCH model

EntropyProg

Entropy pooling program for blending views on scenarios with a prior scenario-probability distribution