NMOF (version 2.11-0)

PBO: Probability of Backtest Overfitting

Description

Estimate probability of backtest overfitting, as described in Bailey et al. 2017

Usage

PBO(M, s = 12, fun = colMeans,
    threshold = 0, ..., loop.fun = TRUE)

Value

A list:

pbo

probability

lambda

vector of logits

in.sample

numeric

out.of.sample

numeric

Arguments

M

a numeric matrix

s

number of submatrices

fun

a function

threshold

a scalar

...

additional arguments passed to fun

loop.fun

logical: if TRUE, fun is called separately for every column of M; if FALSE, fun will be passed the whole matrix M

Author

Enrico Schumann

Details

fun is called with M as its first argument.

References

Bailey, D. H. et al. (2017). The probability of backtest overfitting. Journal of Computational Finance 20 (4), 39--69. tools:::Rd_expr_doi("10.21314/JCF.2016.322")

Examples

# \donttest{
## might run a few seconds
N <- 5000
T <- 480
M <- array(rnorm(N*T, sd = 0.01), dim = c(T, N))
p <- PBO(M, s = 12, fun = colMeans, loop.fun = FALSE)
str(p)
# }