How to generate random time series data with noise in python 3?

Question

This python 2 code generates random time series data with a certain noise:

from common import arbitrary_timeseries
from commonrandom import  generate_trendy_price
from matplotlib.pyplot import show

ans=arbitrary_timeseries(generate_trendy_price(Nlength=180, Tlength=30, Xamplitude=10.0, Volscale=0.1))
ans.plot()
show()

Output:

Does someone know how I can generate this data in python 3?

What happened when you tried to use the same code in Python 3? — mkrieger1, Jun 14 '21 at 21:09
Does this answer your question? [Generate random timeseries data with dates](https://stackoverflow.com/questions/56310849/generate-random-timeseries-data-with-dates) — crissal, Jun 14 '21 at 21:24
@mkrieger1 That the `common` and `commonrandom` modules aren't supported in Python 3. — poop, Jun 14 '21 at 21:24
@crissal Not really I can't generate noise using that method. But maybe I can add noise later hmmm. — poop, Jun 14 '21 at 21:27
@mkrieger1 I guess a library with common (random) functions for python 2. I've never used python2 to be fair. — poop, Jun 14 '21 at 21:28
@mkrieger1 Found this example in an [interesting article](https://qoppac.blogspot.com/2015/11/using-random-data.html) and I wanted to recreate it in python 3. — poop, Jun 14 '21 at 21:31
No but this [answer](https://stackoverflow.com/a/48359952/15673454) did help me out. Thanks to you guys I found this answer! — poop, Jun 14 '21 at 21:43

score 1 · Accepted Answer · answered Jun 14 '21 at 21:42

You can use simple Markov process like this one:

import random

def random_timeseries(initial_value: float, volatility: float, count: int) -> list:
    time_series = [initial_value, ]
    for _ in range(count):
        time_series.append(time_series[-1] + initial_value * random.gauss(0, 1) * volatility)
    return time_series

ts = random_timeseries(1.2, 0.15, 100)

Now you have list with random values which can be zipped with any timestamps.

How to generate random time series data with noise in python 3?

1 Answers1