rlongshort.test: Generate random long short portfolios
In rportfolios: Random Portfolio Generation

Description Usage Arguments Details Value Author(s) References See Also Examples

This function generates m random long short portfolios with n investments that satisfy the given gross and net notional exposure requirements. There are k non-zero positions in each portfolio. The function is used to evaluate the performance of the portfolio generation algorithm.

1 2	rlongshort.test(m, n = 2, k = n, segments=NULL, x.t.long = 1, x.t.short = x.t.long, max.iter = 2000, eps = 0.001)

`m`	A positive integer value for the number of portfolios generated
`n`	A positive integer value for the number of investments in the portfolio
`k`	A positive integer value for the number of non zero weights
`segments`	A vector or list of vectors that defines the portfolio segments
`x.t.long`	A positive real value for the sum of the long exposures
`x.t.short`	A positive real value for the sum of the absolute value of the short exposures
`max.iter`	A positive integer value for the maximum iterations in the acceptance rejection method
`eps`	A small positive real value for the convergence criteria for the gross notional exposure

The function executes the function random.longshort.test using the R function lapply. The result which is a list contains the investment weight vectors and number of iterations. Thse data are stored in a matrix of investment weights and a vector of iterations. These arrays are returned as a list. Gross notional exposure for each portfolio is x.t.long + x.t.short and net notional exposure is x.t.long - x.t.short. The argument eps is the tolerance applied towards the the gross notional exposure of each portfolio.

A list with two named components.

`xmatrix`	A numerical m \times n matrix of investment weights
`iters`	An m \times 1 integer vector for the number of iterations used to obtain the investment weights

Frederick Novomestky fn334@nyu.edu

Jacobs, B. I. and K. N. Levy, 1997. The Long and Short of Long-Short Investing, Journal of Investing, Spring 1997, 73-86.

Jacobs, B. I., K. N. Levy and H. M. Markowitz, 2005. Portfolio Optimization with Factors, Scenarios and Realistic Short Positions, Operations Research, July/August 2005, 586-599.

random.longshort.test

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### 100 long short portfolios with 30 investments and 30 non-zero positions
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x.result <- rlongshort.test( 100, 30 )
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### 100 long short portfolios with 30 investments and 20 non-zero positions
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y.result <- rlongshort.test( 100, 30, 20 )