Financial volatility trading using a self-organising neural-fuzzy semantic network and option straddle-based approach

Area of Science:

• Computational Finance
• Financial Market Analysis
• Algorithmic Trading

Background:

• Financial volatility, the degree of fluctuation in asset pricing, necessitates accurate modeling and forecasting for effective trading strategies.
• Volatility trading capitalizes on market uncertainties across various market conditions.
• Existing methods for financial volatility forecasting often suffer from time-delayed signals.

Purpose of the Study:

• To propose an intelligent straddle trading system (framework) for financial volatility trading in the Hong Kong stock market.
• To enhance trading decision-making by integrating a volatility projection module (VPM) with a trade decision module (TDM).
• To address the limitations of traditional trading signals by incorporating future volatility projections.

Main Methods:

• Employed historical volatility (HV), implied volatility (IV), and model-based volatility (MV) for the Hang Seng Index (HSI).
• Developed a volatility projection module (VPM) using the evolving fuzzy semantic memory (eFSM) model for future volatility forecasting.
• Integrated the VPM with a trade decision module (TDM) that utilizes the moving-averages convergence/divergence (MACD) principle.

Main Results:

• The eFSM model demonstrated superior performance in volatility modeling and forecasting compared to established techniques.
• The proposed straddle trading system, leveraging eFSM-driven volatility projections, yielded encouraging trading returns.
• The eFSM model's evolvable knowledge base and transparent fuzzy rules effectively handled the non-stationary nature of the Hong Kong stock market.

Conclusions:

• The intelligent straddle trading system effectively capitalizes on Hong Kong stock market uncertainties.
• The eFSM model provides accurate and interpretable volatility projections, outperforming traditional methods.
• The framework offers a robust approach to financial volatility trading, enhancing decision-making for investors.