First steps to get into algorithmic trading quickly! with Python
Published in · 5 min read · Mar 2, 2023
--
Algorithmic Trading is actually a really opaque industry and there is not that much quality knowledge freely available or at least easily accessible. All the online courses I’ve bumped into are actually rudimentary and are not answering the most important question: How to really make money? 🤔 I remember when I was starting and wanted to get into the industry and how hard I had to dig to understand how things work.
And there is always the possibility that one will never figure it out!
However, when you think about it… It is about buying an asset at some point in time and then selling it at a future point in time and hopefully banking a profit, or the reverse, selling short and then buying back. (But that would involve paying interest, so it’s a bit more complicated) So, algo trading is at the same time difficult and easy, it is difficult because you have to learn programming, mathematics, and finance, but it is easy because it is about going into a position and then getting out of a position.
Today we will go through information from the difficult part 🤓(programming, maths and finance). I am sharing what I think are the essential python/pandas functions and maths you need to know to be able to research and find a profitable strategy. Let’s get into it!
1. Downloading Daily Data.
import matplotlib.pyplot as plt
import datetime as dt
import yfinance as yf
import pandas as pd
import numpy as np
import pandas_taend_date = dt.date.today()
start_date = end_date - pd.DateOffset(365*3)
symbol = 'NVDA'
prices_df = yf.download(tickers=symbol,
start=start_date,
end=end_date)
prices_df
2. Calculate Technical Indicators And Rolling Functions.
prices_df['stoch_k'] = pandas_ta.stochrsi(close=prices_df['Adj…