what does this code do?
for(s in symbols) {
expected\_annreturn <- (1 - pnorm(0.075, performanceanalyticsqs\_moments(s)[,c("Mean")],performanceanalyticsqs\_moments(s)[,c("1Stdev")])) \* performanceanalyticsqs\_moments(s)[,c("Mean")] \* (365/as.numeric(mean(perTradeStats(Portfolio = portfolio.st, Symbol = s, includeOpenTrade = TRUE, tradeDef = "flat.to.flat", includeFlatPeriods = FALSE, combn.method = c("rbind", "list"), envir = .blotter, Dates = NULL)$End - perTradeStats(Portfolio = portfolio.st, Symbol = s, includeOpenTrade = TRUE, tradeDef = "flat.to.flat", includeFlatPeriods = FALSE, combn.method = c("rbind", "list"), envir = .blotter, Dates = NULL)$Start)))
print(cbind(s, expected\_annreturn))
}
  This code is a R function that takes a list of symbols as input and calculates the expected annual return for each symbol based on the mean and standard deviation of the returns of the symbol over a certain time period. Here is a step-by-step breakdown of what the code does:

1. `for(s in symbols)`: This line loops through each element in the `symbols` list.
2. `expected_annreturn <- (1 - pnorm(0.075, performanceanalyticsqs_moments(s)[,c("Mean")], performanceanalyticsqs_moments(s)[,c("1Stdev")])) * performanceanalyticsqs_moments(s)[,c("Mean")] * (365/as.numeric(mean(perTradeStats(Portfolio = portfolio.st, Symbol = s, includeOpenTrade = TRUE, tradeDef = "flat.to.flat", includeFlatPeriods = FALSE, combn.method = c("rbind", "list"), envir =.blotter, Dates = NULL)$End - perTradeStats(Portfolio = portfolio.st, Symbol = s, includeOpenTrade = TRUE, tradeDef = "flat.to.flat", includeFlatPeriods = FALSE, combn.method = c("rbind", "
 This code is written in R and it appears to be calculating and printing the expected annualized return for each symbol in the `symbols` vector.

Here's a breakdown of what the code does:

1. The `for` loop iterates through each symbol in the `symbols` vector.
2. For each symbol, it calculates the expected annualized return (`expected_annreturn`) based on the mean return, standard deviation, and mean trade duration.
3. Specifically, it calculates the probability of achieving a return greater than 7.5% using the `pnorm` function (which calculates the cumulative distribution function of the normal distribution).
4. It then multiplies this probability by the mean return, the number of trading days in a year (365), and the reciprocal of the mean trade duration.
5. Finally, it prints the symbol and the corresponding expected annualized return using the `print` and `cbind` functions.

The `performanceanalytics` and `blotter` packages are used for calculating the mean return, standard deviation, and mean trade duration for each symbol. The `portfolio.st` object is used to specify the portfolio for which the calculations should be made. The `perTradeStats` function is used to extract the trade statistics for each symbol, and the `performanceanalytics` functions are