There is a portion of the Introduction to Numpy that I don't really understand the mechanics of. In the 'Return to Returns' section:
"...In this case we draw N=100 random samples from a normal distribution with mean 1.01 and standard deviation 0.03 . We treat these as the daily percentage returns of our asset and take the cumulative product of these samples to get the current price."
Q1: Each randomly drawn number is going to be about 1.01. Does this represent a daily percentage return of 1% or 101%?
Q2: Why does the cumulative product of the 100 random samples reflect the current price? Is this just an arbitrary assignment? Also the current price of what? It looks like we are setting up 10 stocks in our universe, the cumulative product should just return a single scalar, correct? Which stock does this scalar represent the current value?
"The way we have generated our universe, the the individual Ri vectors are each 1-dimensional arrays and the returns and assets variables contain 2-dimensional arrays. Above, we set the initial row of both returns and assets to be the first Ri vector and the cumulative asset price based on those returns, respectively."
Q3: What is meant by Ri vectors? Each i in R_1 is a scalar, right?
