pbo (version 1.3.5)

pbo: Probability of backtest overfitting

Description

Performs the probability of backtest overfitting computations.

Usage

pbo(m, s = 4, f = NA, threshold = 0, inf_sub = 6, allow_parallel = FALSE)

Arguments

m

a \(TxN\) data frame of returns, where \(T\) is the samples per study and \(N\) is the number of studies.

s

the number of subsets of m for CSCV combinations; must evenly divide m

f

the function to evaluate a study's performance; required

threshold

the performance metric threshold (e.g. 0 for Sharpe, 1 for Omega)

inf_sub

infinity substitution value for reasonable plotting

allow_parallel

whether to enable parallel processing, default FALSE

Value

object of class pbo containing list of PBO calculation results and settings

Details

This function performs the probability of backtest overfitting calculation using a combinatorially-symmetric cross validation (CSCV) approach.

References

Baily et al., "The Probability of Backtest Overfitting," https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2326253

Examples

# NOT RUN {
require(pbo)
require(PerformanceAnalytics)
n <- 100
t <- 1000
s <- 8
m <- data.frame(matrix(rnorm(n*t,mean=0,sd=1),
  nrow=t,ncol=n,byrow=TRUE,
  dimnames=list(1:t,1:n)),
  check.names=FALSE)
p <- pbo(m,s,f=Omega,threshold=1)
# }