Option Chain Analysis

This project retrieves option chain data using yfinance and calculates margin requirements and premium earned.

Usage

1. Install required libraries: pip install yfinance pandas
2. Run the script: python main.py

Functions

• get_option_chain_data(instrument, expiry_date,side): Retrieves option chain data for a given instrument and expiry date.

  Args: instrument_name: Name of the instrument (e.g., NIFTY or BANKNIFTY). expiry_date: The expiration date of the options, in YYYY-MM-DD format. side: Type of option to retrieve. Use "PE" for Put and "CE" for Call.

  Returns: A Pandas DataFrame containing the option chain data. The function returns the highest bid price for put options (PE) or the highest ask price for call options (CE) for each strike price.

• calculate_margin_and_premium(option_data): Calculates margin requirement and premium earned for a given option chain DataFrame.

  Args: option_data (pd.DataFrame): DataFrame returned by get_option_chain_data.

  Returns: pd.DataFrame: DataFrame with additional columns: - margin: Margin requirement for each option contract - premium: Premium earned for each option contract

Challenges

• Initially, I had issues with accessing real-time option chain data. I overcame this by using yfinance, which provides delayed data.

Insights

• Using yfinance simplified the data retrieval process compared to other APIs.

AI Tools

• I used Gemini to:
  • Find alternative APIs for option chain data.
  • Understand the yfinance library and generate code for data retrieval and processing.