OPEN-SOURCE SCRIPT
Khaled Tamim's Avellaneda-Stoikov Strategy

Description:
This strategy applies the Avellaneda-Stoikov (A-S) model to generate buy and sell signals for underlying assets based on option pricing theory. The A-S model estimates bid and ask quotes for options contracts considering factors like volatility (sigma), time to expiration (T), and risk aversion (gamma).
Key Concepts:
Avellaneda-Stoikov Model: A mathematical framework for option pricing that incorporates volatility, time decay, and risk tolerance.
Bid-Ask Quotes: The theoretical buy and sell prices for an option contract.
Inventory Management: The strategy tracks its long or short position based on signals.
How it Works:
A-S Model Calculation: The avellanedaStoikov function calculates bid and ask quotes using the underlying asset's closing price, user-defined parameters (gamma, sigma, T, k, and M), and a small fee (adjustable).
Signal Generation: The strategy generates long signals when the closing price falls below the adjusted bid quote and short signals when it exceeds the adjusted ask quote.
Trade Execution: Buy and sell orders are triggered based on the generated signals (long for buy, short for sell).
Inventory Tracking: The strategy's net profit reflects the current inventory level (long or short position).
Customization:
Gamma (γ): Controls risk aversion in the A-S model (higher values imply lower risk tolerance).
Sigma (σ): Represents the underlying asset's expected volatility.
T: Time to expiration for the hypothetical option (defaults to a short-term option).
k: A constant factor in the A-S model calculations.
M: Minimum price buffer for buy/sell signals (prevents excessive churn).
Important Note:
This strategy simulates option pricing behavior for a theoretical option and does not directly trade options contracts. Backtesting results may not reflect actual market conditions.
Further Considerations:
The 0.1% fee is a placeholder and may need adjustment based on real-world trading costs.
Consider using realistic timeframes for T (e.g., expiry for a real option)
Disclaimer: This strategy is for educational purposes only and does not constitute financial advice.
This strategy applies the Avellaneda-Stoikov (A-S) model to generate buy and sell signals for underlying assets based on option pricing theory. The A-S model estimates bid and ask quotes for options contracts considering factors like volatility (sigma), time to expiration (T), and risk aversion (gamma).
Key Concepts:
Avellaneda-Stoikov Model: A mathematical framework for option pricing that incorporates volatility, time decay, and risk tolerance.
Bid-Ask Quotes: The theoretical buy and sell prices for an option contract.
Inventory Management: The strategy tracks its long or short position based on signals.
How it Works:
A-S Model Calculation: The avellanedaStoikov function calculates bid and ask quotes using the underlying asset's closing price, user-defined parameters (gamma, sigma, T, k, and M), and a small fee (adjustable).
Signal Generation: The strategy generates long signals when the closing price falls below the adjusted bid quote and short signals when it exceeds the adjusted ask quote.
Trade Execution: Buy and sell orders are triggered based on the generated signals (long for buy, short for sell).
Inventory Tracking: The strategy's net profit reflects the current inventory level (long or short position).
Customization:
Gamma (γ): Controls risk aversion in the A-S model (higher values imply lower risk tolerance).
Sigma (σ): Represents the underlying asset's expected volatility.
T: Time to expiration for the hypothetical option (defaults to a short-term option).
k: A constant factor in the A-S model calculations.
M: Minimum price buffer for buy/sell signals (prevents excessive churn).
Important Note:
This strategy simulates option pricing behavior for a theoretical option and does not directly trade options contracts. Backtesting results may not reflect actual market conditions.
Further Considerations:
The 0.1% fee is a placeholder and may need adjustment based on real-world trading costs.
Consider using realistic timeframes for T (e.g., expiry for a real option)
Disclaimer: This strategy is for educational purposes only and does not constitute financial advice.
오픈 소스 스크립트
진정한 트레이딩뷰 정신에 따라 이 스크립트 작성자는 트레이더가 기능을 검토하고 검증할 수 있도록 오픈소스로 공개했습니다. 작성자에게 찬사를 보냅니다! 무료로 사용할 수 있지만 코드를 다시 게시할 경우 하우스 룰이 적용된다는 점을 기억하세요.
면책사항
이 정보와 게시물은 TradingView에서 제공하거나 보증하는 금융, 투자, 거래 또는 기타 유형의 조언이나 권고 사항을 의미하거나 구성하지 않습니다. 자세한 내용은 이용 약관을 참고하세요.
오픈 소스 스크립트
진정한 트레이딩뷰 정신에 따라 이 스크립트 작성자는 트레이더가 기능을 검토하고 검증할 수 있도록 오픈소스로 공개했습니다. 작성자에게 찬사를 보냅니다! 무료로 사용할 수 있지만 코드를 다시 게시할 경우 하우스 룰이 적용된다는 점을 기억하세요.
면책사항
이 정보와 게시물은 TradingView에서 제공하거나 보증하는 금융, 투자, 거래 또는 기타 유형의 조언이나 권고 사항을 의미하거나 구성하지 않습니다. 자세한 내용은 이용 약관을 참고하세요.