Selecting The Best Forecasting-Implied Volatility Model Using Genetic Programming.pdf

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Preview of Selecting the Best Forecasting-Implied Volatility Model Using Genetic Programming
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📊 Size: 2.55 MB
📄 Pages: 20 pages
⬇️ Downloads: 66

Summary

The volatility smile is a crucial variable in option pricing and hedging strategies, and the Black-Scholes model has well-known deficiencies. Genetic programming is used to forecast Black and Scholes-implied volatility, and results show that the time series model is more accurate than moneyness-time to maturity models. The study uses real data from S&P500 index options and finds that genetic programming works well in solving financial problems, providing a systematic approach and a software tool for analysts to improve forecasting accuracy.

Description

The volatility smile is a crucial variable in option pricing and hedging strategies, and the Black-Scholes model has well-known deficiencies.

Technical Information

  • File Format: PDF
  • File Size: 2.55 MB
  • Pages: 20
  • Language: EN
  • Total Downloads: 66
  • Last Updated: 5 days ago

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This PDF document about Selecting the Best Forecasting-Implied Volatility Model Using Genetic Programming provides comprehensive information and guidance. Whether you're a beginner or advanced user, this resource offers valuable insights into Selecting the Best Forecasting-Implied Volatility Model Using Genetic Programming.

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