Exercise

# Generate a Random Walk

Whereas stock *returns* are often modeled as white noise, stock *prices* closely follow a random walk. In other words, today's price is yesterday's price plus some random noise.

You will simulate the price of a stock over time that has a starting price of 100 and every day goes up or down by a random amount. Then, plot the simulated stock price. If you hit the "Run Code" code button multiple times, you'll see several realizations.

Instructions

**100 XP**

- Generate 500 random normal "steps" with mean=0 and standard deviation=1 using
`np.random.normal()`

, where the argument for the mean is`loc`

and the argument for the standard deviation is`scale`

. - Simulate stock prices
`P`

:- Cumulate the random
`steps`

using the numpy`.cumsum()`

method - Add 100 to
`P`

to get a starting stock price of 100.

- Cumulate the random
- Plot the simulated random walk