portfolio.optimization1.0-0 package

Contemporary Portfolio Optimization

active.extension

Enable active extension portfolios

alpha

Set new alpha of a portfolio.model

aux_portfolio.default

Set portfolio.model default values

aux_risk.alias

Convert risk alias names to internal names

aux_simulate.scenarios

Simulate a multivariate-normal scenario.set

linear.constraint.eq

Create or update a vector-based linear equality constraint set

linear.constraint.iq

Create or update a vector-based linear inequality constraint set

long.only

Disable active extension portfolios

lower.bound

Set lower bounds on assets

momentum

Set momentum parameters for a portfolio.model

objective

Set new objective of a portfolio.model

optimal.portfolio.1overN

1 over N portfolio

optimal.portfolio.expected.shortfall.long.short

Portfolio Optimization minimizing Conditional Value at Risk (CVaR) wit...

optimal.portfolio.expected.shortfall

Portfolio Optimization minimizing Conditional Value at Risk (CVaR)

optimal.portfolio.mad.long.short

Portfolio Optimization minimizing MAD (Active Extension)

optimal.portfolio.mad

Portfolio Optimization minimizing MAD

optimal.portfolio.markowitz

Portfolio Optimization minimizing Standard Deviation

optimal.portfolio.momentum

Momentum portfolio including momentum for active extensions

optimal.portfolio

Meta-function to optimize portfolios given a portfolio.model instance

optimal.portfolio.reward

Compute maximum/minimum return portfolio given the constraints

po.tutorial

Open a specific portfolio.optimization package tutorial

portfolio.loss

Return the loss distribution of the portfolio.model

portfolio.model

Create a portfolio.model instance (or fix an existing one)

portfolio.optimization-package

Contemporary Portfolio Optimization

portfolio.weights

Return the portfolio weights of a portfolio.model

print.portfolio.model

Overload print() for portfolio.model

sp100w17av

S&P 100 average trading volume over the whole year 2017

upper.bound

Set upper bounds on assets

Simplify your portfolio optimization process by applying a contemporary modeling way to model and solve your portfolio problems. While most approaches and packages are rather complicated this one tries to simplify things and is agnostic regarding risk measures as well as optimization solvers. Some of the methods implemented are described by Konno and Yamazaki (1991) <doi:10.1287/mnsc.37.5.519>, Rockafellar and Uryasev (2001) <doi:10.21314/JOR.2000.038> and Markowitz (1952) <doi:10.1111/j.1540-6261.1952.tb01525.x>.