Profile Overview

Richard Schmidt

Richard Schmidt
Richard Schmidt

Chicago-born quantitative investor and educator, Richard Schmidt blends CME trading roots, LBS and Johns Hopkins training, and decades of experience at Citibank, Bridgewater, Two Sigma and GenesisEdge AI to build crisis-tested, AI-enhanced multi-asset strategies and practical investor education programs.

Quantitative Futures AI Trading Systems Multi-Asset Portfolios Investor Education
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Overview

Richard Schmidt is a futures-focused quantitative investor and professor whose career began with a small family-funded trading account and early exposure to the Turtle Trading rules. After earning his BSc and PhD in Financial Economics from LBS and an EMBA from Johns Hopkins, he progressed through research and portfolio roles at Citibank, Bridgewater and Two Sigma. There he refined crisis-resilient, systematic multi-asset portfolios anchored on his π-Pivot mean reversion framework. In 2012 he co-founded GenesisEdge AI Holdings Inc., using proprietary capital and AI-enhanced strategies to build a strong track record in futures and equities, and later launched the Σclipse AI system and GenesisEdge Society to bring institutional methods to over one hundred thousand learners worldwide.

  • Strength: Integrating fundamental research, macro data and AI-based signals into robust, risk-controlled multi-asset trading architectures.
  • Focus: Futures and index strategies, emerging markets, and practical translation of institutional research into tools for individual investors.
  • Responsibility: Designing Σclipse AI, guiding GenesisEdge Society curricula, and mentoring cohorts of investors on structured, evidence-based decision making.

Practical Highlights

Experience
30+ yrs
From early CME futures trades to global macro and AI-driven portfolios at leading institutions.
Crisis Performance
150%+ return
Generated standout performance by buying Nasdaq index futures near the 2008–2009 market bottom with disciplined risk controls.
Education Reach
100K+ learners
Twelve completed GenesisEdge Society cohorts across stocks, futures, FX, funds, bonds, commodities and crypto, now entering the Σclipse AI V5.0 beta phase.

Career Highlights

  • Early Futures Trading & Citibank Research

    Begins trading futures with a US$1,000 stake from his father, profits from U.S. agricultural options reforms, and joins Citibank as an Equity/Fixed Income Research Analyst, learning rigorous data-driven market investigation.

  • PhD at LBS & Bridgewater Pure Alpha

    Completes a PhD in Financial Economics at LBS and joins Bridgewater, contributing to the development of Pure Alpha and portable alpha strategies that blend macro research, systematic signals and risk-budgeted positioning.

  • Two Sigma Quant & Portfolio Manager

    Joins Two Sigma as Quant Researcher II, develops the π-Pivot Mean Reversion strategy, and later becomes Portfolio Manager for multi-billion-dollar emerging-market and multi-asset mandates with standout 2008–2009 crisis performance.

  • GenesisEdge AI Holdings & Capital Growth

    Co-founds GenesisEdge AI Holdings Inc. with core members from Jump Trading, achieving over 200% futures returns in 2012 and building substantial early positions in AAPL and GOOG that financed future AI research.

  • Σclipse AI & GenesisEdge Society

    Launches Σclipse AI, integrating AI and big data into trading, and leads GenesisEdge Society in running 12 investor training cohorts across global markets, now entering the Σclipse AI V5.0 pre-listing beta phase and 13th cohort.

π-Pivot Mean Reversion Framework

Studies how price oscillations around structural pivots, volatility regimes and liquidity conditions can be captured through disciplined mean reversion, position scaling and risk-budget overlays in futures and index markets.

AI-Enhanced Multi-Asset Allocation

Explores Σclipse AI models that combine macro indicators, market microstructure features and sentiment-driven signals to allocate across equities, commodities, FX, bonds and digital assets with dynamic risk management.

Applied Investor Education Design

Focuses on curriculum structures that bring institutional-grade research methods to retail learners through case-based exercises, stepwise strategy building and feedback loops grounded in real market conditions.

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