# portfolio.turnover: Calculate Sub-Portfolio Turnover In portsort: Factor-Based Portfolio Sorts

## Description

Calculates sub-portfolio turnover between each rebalancing period.

## Usage

 `1` ```portfolio.turnover(sort.output) ```

## Arguments

 `sort.output` object returned from either the conditional.sort or unconditional.sort function.

## Details

This function calculates the turnover within each sub-portfolio over time and returns a list containing the turnover values and the mean turnover across time.

## Value

 `Turnover` xts object of turnovers for each rebalancing point. `Mean Turnover` mean turnover for each sub-portfolio averaged over time.

## Author(s)

Jonathan Spohnholtz and Alexander Dickerson

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25``` ```# Load the included data library(portsort) data(Factors) # Specifiy the sort dimension - in this case, a double-sort on lagged returns and Bitcoin volumes dimA = 0:3/3 dimB = 0:3/3 # Specify the factors # Lagged returns, lagged volumes are stored in the Factors list R.Forward = Factors[[1]]; R.Lag = Factors[[2]]; V.Lag = Factors[[3]] # Subset the data from late 2017 R.Forward = R.Forward["2017-12-01/"] R.Lag = R.Lag["2017-11-30/2018-09-05"] V.Lag = V.Lag["2017-11-30/2018-09-05"] Fa = R.Lag Fb = V.Lag # Conduct an unconditional sort (in this case) or a conditional sort sort.output = unconditional.sort(Fa = Fa, Fb = Fb , R.Forward = R.Forward, dimA = dimA, dimB = dimB) # Compute Turnover by passing the sort.output object to the turnover function sort.turnover = portfolio.turnover(sort.output) ```

portsort documentation built on May 2, 2019, 6:36 a.m.