pa (version 1.2-1)

regression-class: Class "regression"

Description

Class "regression" holds the results of an original portfolio, its benchmark, and the results of regression analysis of a single-period portfolio.

Slots

date.var:

Object of class "character" storing the name of the date column in the class object.

ret.var:

Object of class "character" storing the name of the return variable.

reg.var:

Object of class "character" storing the name of the regressors.

benchmark.weight:

Object of class "character" storing the name of the benchmark weight variable.

portfolio.weight:

Object of class "character" storing the name of the portfolio weight variable in the universe dataframe.

coefficients:

Object of class "numeric" storing the estimated coefficients of the regression model.

benchmark.ret:

Object of class "matrix" storing the benchmark return of the input portfolio.

portfolio.ret:

Object of class "matrix" storing the portfolio return of the input portfolio.

act.ret:

Object of class "matrix" storing the active return of the input portfolio.

act.expo:

Object of class "numeric" storing the active exposure according to the regressors.

contrib:

Object of class "numeric" storing the contribution of the regressors according to the input.

universe:

Object of class "data.frame" storing the entire input data frame.

Methods

exposure

signature(object = "regression"): Calculate and display the exposure of the input category of a portfolio.

plot

signature(x = "regression", y = "missing"): Plot the exposure or the return of a regression class object.

returns

signature(object = "regression"): Calculate the contribution of various effects based on the regression analysis.

show

signature(object = "regression"): Summarize the essential information about the portfolio.

summary

signature(object = "regression"): Summarize the portfolio and the regression-based attribution.

Examples

# NOT RUN {
## Single-period regression analysis

data(jan)

r1 <-regress(x = jan, date.var = "date", ret.var = "return", reg.var = c("sector",
"value", "growth"), benchmark.weight = "benchmark", portfolio.weight =
"portfolio")

summary(r1)

# }