How to generate a pseudo random number based on previous number in Python

Am attempting to run a monte carlo simulation using numpy like so:

from numpy import random

btcpremiummean = -2.61
btcpremiumsd = 1.63
trialsize = 1000000

for x in range(trialsize):
    btcpremium = random.normal(btcpremiummean, btcpremiumsd)
    ...

I derived the mean and standard deviations from backtests and am using them to generate random figures.

However, though the data fits within this normal distribution, the real-life btcpremium is not truly random; rather it's usually equal to or close to the previous btcpremium.

I can't think of how to how to change my code so that btcpremium values fit within the normal distribution currently used while being affected by previous data.

Thanks in advance.