Displaying 6 results from an estimated 6 matches for "mu_base".
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mc_base
2017 Nov 21
2
Do I need to transform backtest returns before using pbo (probability of backtest overfitting) package functions?
...#represents a trial and each trial has the same length T. This example
#is random data so the backtest should be overfit.`
set.seed(765)
n <- 100
t <- 2400
m <- data.frame(matrix(rnorm(n*t),nrow=t,ncol=n,
dimnames=list(1:t,1:n)), check.names=FALSE)
sr_base <- 0
mu_base <- sr_base/(252.0)
sigma_base <- 1.00/(252.0)**0.5
for ( i in 1:n ) {
m[,i] = m[,i] * sigma_base / sd(m[,i]) # re-scale
m[,i] = m[,i] + mu_base - mean(m[,i]) # re-center}
#We can use any performance evaluation function that can work with the
#reassembled sub-matrices during the cross vali...
2017 Nov 21
2
Do I need to transform backtest returns before using pbo (probability of backtest overfitting) package functions?
...mal.
Suppose he wanted to create random data from a distribution of returns with
ANNUAL mean MU_A and ANNUAL std deviation SIGMA_A, both stated in decimal.
The equivalent DAILY returns would have mean MU_D = MU_A / 252 and standard
deviation SIGMA_D = SIGMA_A/SQRT(252).
He calls MU_D by the name mu_base and SIGMA_D by the name sigma_base.
His loop now converts the random numbers in his matrix so that each column
has mean MU_D and std deviation SIGMA_D.
HTH,
Eric
On Tue, Nov 21, 2017 at 2:33 PM, Eric Berger <ericjberger at gmail.com> wrote:
> Hi Joe,
> The centering and re-scali...
2017 Nov 21
0
Do I need to transform backtest returns before using pbo (probability of backtest overfitting) package functions?
...tion SIGMA_A, both stated in decimal.
The equivalent DAILY
Then he does two steps: (1) generate a matrix of random values from the
N(0,1) distribution. (2) convert them to DAILY
After initializing the matrix with random values (from N(0,1)), he now
wants to create a series of DAILY
sr_base <- 0
mu_base <- sr_base/(252.0)
sigma_base <- 1.00/(252.0)**0.5
for ( i in 1:n ) {
m[,i] = m[,i] * sigma_base / sd(m[,i]) # re-scale
m[,i] = m[,i] + mu_base - mean(m[,i]) # re-center}
On Tue, Nov 21, 2017 at 2:10 PM, Bert Gunter <bgunter.4567 at gmail.com> wrote:
> Wrong list.
>
> Pos...
2017 Nov 21
0
Do I need to transform backtest returns before using pbo (probability of backtest overfitting) package functions?
...eate random data from a distribution of returns
> with ANNUAL mean MU_A and ANNUAL std deviation SIGMA_A, both stated in
> decimal.
> The equivalent DAILY returns would have mean MU_D = MU_A / 252 and
> standard deviation SIGMA_D = SIGMA_A/SQRT(252).
>
> He calls MU_D by the name mu_base and SIGMA_D by the name sigma_base.
>
> His loop now converts the random numbers in his matrix so that each column
> has mean MU_D and std deviation SIGMA_D.
>
> HTH,
> Eric
>
>
>
> On Tue, Nov 21, 2017 at 2:33 PM, Eric Berger <ericjberger at gmail.com>
> wr...
2017 Nov 21
1
Do I need to transform backtest returns before using pbo (probability of backtest overfitting) package functions?
...reate random data from a distribution of returns with ANNUAL mean MU_A and ANNUAL std deviation SIGMA_A, both stated in decimal.
>> The equivalent DAILY returns would have mean MU_D = MU_A / 252 and standard deviation SIGMA_D = SIGMA_A/SQRT(252).
>>
>> He calls MU_D by the name mu_base and SIGMA_D by the name sigma_base.
>>
>> His loop now converts the random numbers in his matrix so that each column has mean MU_D and std deviation SIGMA_D.
>>
>> HTH,
>> Eric
>>
>>
>>
>>> On Tue, Nov 21, 2017 at 2:33 PM, Eric Berger...
2017 Nov 21
0
Do I need to transform backtest returns before using pbo (probability of backtest overfitting) package functions?
...#represents a trial and each trial has the same length T. This example
#is random data so the backtest should be overfit.`
set.seed(765)
n <- 100
t <- 2400
m <- data.frame(matrix(rnorm(n*t),nrow=t,ncol=n,
dimnames=list(1:t,1:n)), check.names=FALSE)
sr_base <- 0
mu_base <- sr_base/(252.0)
sigma_base <- 1.00/(252.0)**0.5
for ( i in 1:n ) {
m[,i] = m[,i] * sigma_base / sd(m[,i]) # re-scale
m[,i] = m[,i] + mu_base - mean(m[,i]) # re-center}
#We can use any performance evaluation function that can work with the
#reassembled sub-matrices during the cross vali...