GPT4 Generated Code Summary

This code is for processing financial data and backtesting a trading strategy using a grid system. Here's a summary of its components and functionality:

1. Data Processing:

   • Reads data from 'VIX_History.csv', extracting the last field from each line (presumably closing prices) and storing it in data_close.

   • Applies settings from an external 'settings' module to determine the subset of data to use.

2. Utility Functions:

   • wholenums: Returns a list of whole numbers between two given numbers.

   • affordable_shares: Calculates the number of shares that can be bought within an acceptable risk limit.

3. Trading Strategy Implementation:

   • Defines lists for buy signals, sell signals, and combined buy/sell signals.

   • Uses settings from the 'settings' module to create a range of price limits (limit) for triggering buy/sell orders.

   • The limits_hit function detects when the price crosses these limits and records corresponding buy or sell signals.

4. Backtesting and Profit Calculation:

   • print_backtest_results: Calculates and prints the grid profit, unrealized profit/loss, and total profit from the trading strategy.

   • Buys and sells are tracked, and profit is calculated based on the difference between buy and sell prices, adjusted for the number of shares.

5. Plotting:

   • Visualizes the trading strategy by plotting the closing price data, buy/sell signals, and price limits.

   • Uses Matplotlib to create the plot, with buy signals in green, sell signals in red, and price limits in orange.

6. Execution:

   • The script executes the trading strategy over the data, plots the results, and then prints the backtest results.

The code is structured to backtest a grid trading strategy where buy and sell orders are triggered when the price crosses predefined limits. It then visualizes the strategy's performance and calculates the profitability.