Algorithmic Trading Bot on Python & Stock Market Analysis

Algorithmic Trading Bot on Python & Stock Market Analysis. Algorithmic Trading (a.k.a Black-box trading or quant trading) is a set of methods dedicated for financial trading engagements. In this lecture, we will tap upon the theoretical as well as implementation aspects of an algorithmic trading bot running the moving average crossover strategy to detect buy/sell stock signals on Python. The implementation is very simple, i.e. given the stock price data, all we need to do is compute long and short moving averages, then find the crossing points to alert buy/sell signals of the intended stock.

Algorithmic Trading (a.k.a Black-box trading or quant trading) is a set of methods dedicated for financial trading engagements. In this lecture, we will tap upon the theoretical as well as implementation aspects of an algorithmic trading bot running the moving average crossover strategy to detect buy/sell stock signals on Python. The implementation is very simple, i.e. given the stock price data, all we need to do is compute long and short moving averages, then find the crossing points to alert buy/sell signals of the intended stock. This lecture is outlined as follows:

⏲Outline⏲

• 00:00 Introduction
• 01:55 Time Series
• 03:54 Moving Average
• 07:45 Moving Average Crossover Method
• 10:59 Setting Jupyter Lab
• 11:31 Importing Modules
• 12:01 Start & End Dates
• 12:20 Reading Stocks
• 14:05 Defining Window Size
• 14:53 Short & Long Moving Averages
• 16:06 Visualizing the Moving Averages
• 17:34 Moving Average Crossover on Python
• 26:53 GameStop Stock Signals
• 29:02 Royal Caribbean Stock Price Signals
• 32:05 UNP Stock Signals
• 33:11 CEVA Stock Signals
• 33:40 Google Stock Signals
• 34:01 Tesla Stock Signals
• 34:34 Zomedica Stock Signals
• 36:30 Outro

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