04. Building a Trading Program Using Python

Building an Algorithmic Trading Program

This guide focuses on the initial steps to develop a trading algorithm program, emphasizing essential packages and database setup.

Key Steps and Packages:

• Importing Packages:
  • Numpy: For numerical calculations.
  • Scipy.stats.norm: For normal distribution calculations.
  • CSV Module: Handles CSV file operations.
  • Contextlib.closing: Manages resources like database connections.
  • SQLite3: Used for a lightweight local database setup.

Database Management:

• SQLite3 Benefits:
  • Local database reduces server workload and network traffic.
  • Doesn't have a server running in the background, stores data in a single file.
  • Quiet performance boost even on the same computer.

Setup Process:

• Global Variables:

  • Conn: Connection to SQLite3 database stored in SP 500.db.
  • CS: Cursor for database connection.

• Resource Management:

  • Utilize with closing to ensure resources are released.

Functions Overview:

• Prepare: Sets up the initial database.
• Main: Core loop for the trading algorithm.

Further detailed components and functions will be covered later.