Invest: Investing in a Toy Market
In RelValAnalysis: Relative Value Analysis

Description Usage Arguments Details Value See Also Examples

Given the portfolio weights and a toy market, the function Invest simulates the growth of $1 of the corresponding portfolio and that of the benchmark.

1	Invest(market, weight, plot = TRUE)

`market`	a `toymkt` object.
`weight`	the portfolio weights. The portfolio weights must be non-negative and sum to one (full investment with no short sales). It can be a `zoo` object or matrix/dataframe whose number of rows is at least as large as that of `market$R`. If the number of rows of `weight` is larger than required, only the initial rows will be used. `weight` can also be a numeric vector whose length is equal to the number of columns of `market$R` (the number of assets). In the latter case the portfolio is assumed to be constant-weighted through out.
`plot`	`TRUE` or `FALSE`. If `TRUE`, the growth of $1 of the portfolio will be plotted together with the growth of $1 of the market portfolio. The default value is `TRUE`.

The relative value in the second plot is the ratio of the growth of $1 of the portfolio to that of the benchmark. It is called relative because the value is normalized by the value of the benchmark portfolio.

A list containing the following components.

`growth`	a `zoo` object representing the growth of $1 of the portfolio and the benchmark.
`R`	a `zoo` object of simple returns of the two portfolios.
`r`	a `zoo` object of log returns of the two portfolios.

toymkt

# Performance of the equal-weighted portfolio
data(applestarbucks)
market <- toymkt(applestarbucks)
weight <- c(0.5, 0.5)  # equal-weighted portfolio
result <- Invest(market, weight, plot = TRUE)

Loading required package: zoo

Attaching package: 'zoo'

The following objects are masked from 'package:base':

    as.Date, as.Date.numeric

Warning message:
In toymkt(applestarbucks) :
  Since initial.weight is not given, the benchmark is assumed to be equal-weighted initially.
Warning message:
In Invest(market, weight, plot = TRUE) :
  Since only one weight vector is supplied, the portfolio is assumed to be constant-weighted.