Founder & Ceo
• Designed UI to make complex-options trading as easy as trading stock with my IP (patent WO2013166415A1).• Rule-based expert system augmented with ML for complex options strategy composition and selection.• Feature engineering approach where each strategy has a weighted geometric structure related to an asset.• SMEs generated labelled data by selecting strategies in simulation for validation.• Model tuned with human-in-the-loop (HITL).• Attracted 500 B2C users and 4 contracts for B2B2C distribution in support of a B2B growth strategy.• Ran a business (venture capital, hiring, strategy, Agile, roadmap, vision, prioritized features, market research).Orca was a rule-based expert system augmented with ML techniques for complex options strategy composition and selection.It used a feature engineering approach where each strategy has a weighted geometric structure and relationship to an underlying asset. SMEs labelled data by selecting strategies in simulation. Market data snapshots are unpredictable and option chains (strikes, expirations, liquidity) are sparse, so labelling was for validation, not training. SMEs reinforced confidence in my strategy composition and financial engineering as I observed high precision against labelled data.To improve the model it traversed underlying forecast space bins (3 axis: time, price, implied volatility) to generate ranked output from millions of market snapshots. After every epoch, data visualizations with frequency statistics allowed human-in-the-loop evaluation, while the system tuned parameters.In production, a simple UI let users input their underlying forecast (the same info used to trade stock) and it presented 5 complex options strategies. Each strategy was distinct, and expertly composed for the underlying forecast. Users could quickly and confidently trade. Orca leveled the playing field, protecting people from professionals. Wall Street traders are “sharks”; killer whales are apex predators.
