Exercise 2. Bank earnings Monte Carlo

Run a Monte Carlo simulation with 10,000 outcomes for \(S\), the sum of losses over 10,000 loans. Make a histogram of the results.

This exercise is part of the course

HarvardX Data Science - Probability (PH125.3x)

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Exercise instructions

Within a replicate loop with 10,000 iterations, use sample to generate a list of 10,000 loan outcomes: payment (0) or default (1). Use the outcome order c(0,1) and probability of default p_default.
Still within the loop, use the function sum to count the number of foreclosures multiplied by loss_per_foreclosure to return the sum of all losses across the 10,000 loans. If you do not take the sum inside the replicate loop, DataCamp may crash with a "Session Expired" error.
Plot the histogram of values using the function hist.

Hands-on interactive exercise

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

# Assign the number of loans to the variable `n`
n <- 10000

# Assign the loss per foreclosure to the variable `loss_per_foreclosure`
loss_per_foreclosure <- -200000

# Assign the probability of default to the variable `p_default`
p_default <- 0.03

# Use the `set.seed` function to make sure your answer matches the expected result after random sampling
set.seed(1)

# The variable `B` specifies the number of times we want the simulation to run
B <- 10000

# Generate a list of summed losses 'S'. Replicate the code from the previous exercise over 'B' iterations to generate a list of summed losses for 'n' loans.  Ignore any warnings for now.





# Plot a histogram of 'S'.  Ignore any warnings for now.

Edit and Run Code