Column operations with trading volumes

The number of shares traded (sold or bought) in a given time period is the volume. You work for a stock brokerage as a Business Analyst. A matrix of daily changes in volume, mat_stocks, is available for you. Each column contains the change in volume for a stock from the previous day. You want to find out whether the traded volume for these stocks increases consistently for a given period.

The function calculate_runs() is available for you. This function takes two arguments: 1) the daily changes in volume, 2) a single-value of the period (number of days) for which to calculate the run.

You need to apply calculate_runs() to every column of mat_stocks in parallel, specifying five days as the period. The parallel package has been loaded for you.

This exercise is part of the course

Parallel Programming in R

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Exercise instructions

Export n_days to the cluster.
Apply calculate_runs to each column of matrix mat_stocks.
Specify the value for the period argument with n_days.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

n_days <- 5
cl <- makeCluster(4)

# Export n_days to cluster
clusterExport(cl, "___", envir = environment())
# Apply calculate_runs to each column of mat_stocks
volume_runs <- ___(___, ___, ___,
                   # Specify value for period argument
                   ___ = ___)

stopCluster(cl)

print(paste0("Number of ", n_days, "-day increasing runs: ", sum(volume_runs)))

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