Bryan Thomas Whalen Launches AI Factor-Driven Stock Selection Model, Focusing on the Resonance Between Growth and Value
Winter in New York remained cold, yet the capital markets began the new year with strong momentum. After completing the previous phase of his multi-asset hedging framework, Bryan Thomas Whalen shifted his research focus from risk management to strategic offense. In February, he officially launched a new AI factor-driven stock selection model. This model was not designed merely to enhance trading efficiency or control drawdowns—it aimed to answer a more fundamental question: how should capital identify companies with genuine long-term compounding potential amid the duality of technological growth and traditional value?
Bryan introduced the concept of “growth and value resonance,” arguing that the post-pandemic market had entered an era of both profit recovery and industrial innovation. In such an environment, betting solely on one investment style risked missing deeper structural opportunities.
The model’s construction began in the third quarter of the previous year. At that time, the U.S. technology sector, after a period of sharp gains, entered a phase of volatility, while cyclical and financial sectors rebounded rapidly on vaccine optimism. Frequent style rotations caused many quantitative strategies to lose effectiveness. Bryan observed that traditional factor models lacked the ability to capture nonlinear market transitions, and in the fourth quarter, he led an initiative to rebuild the stock selection framework through artificial intelligence.
The new model incorporated over 70 core factors, including earnings growth, free cash flow, revenue sustainability, capital expenditure efficiency, corporate leverage, and intangible asset valuation metrics. Additionally, it integrated natural language processing (NLP) to analyze earnings call transcripts, management guidance, and industry research reports—extracting semantic sentiment signals to forecast future earnings quality.
Unlike conventional value strategies, Bryan’s approach did not rely solely on low valuation as a metric. Instead, it emphasized a company’s bargaining power within its supply chain and its capacity to generate sustainable cash flow. In the model’s logic, whether a technology company is worth holding depends not on its P/E ratio, but on whether its R&D investment consistently translates into product premium and market share growth. Following initial screening, the model prioritized sectors such as cloud infrastructure, semiconductor equipment, medical technology, and resurgent industrial automation firms—industries he viewed as combining both growth elasticity and tangible cash flow support, forming the strongest convergence of growth and value.
As 2021 began, rising U.S. Treasury yields and inflation expectations fueled market anxiety over highly valued tech stocks. Yet Bryan did not abandon the technology sector. Instead, he optimized portfolio composition through the model, removing companies with excessive leverage or fragile business models, and concentrated holdings in firms with profitability, healthy cash flow, and reasonable valuations. At the same time, he added exposure to traditional value sectors such as industrials, financials, and renewable energy equipment manufacturers, constructing a “diffused portfolio” designed to remain resilient amid style rotations. He emphasized, “True value lies not in low prices, but in high certainty; true growth is not about fast revenue, but about consistent conversion into cash flow.”
Though markets at the time remained dominated by policy stimulus and abundant liquidity, Bryan believed the next 12 months would mark a critical phase in the repricing of value and growth. Regardless of style shifts, capital would inevitably return to companies capable of generating real earnings and tangible cash flows. He chose to let the model identify firms that thrive not on market sentiment but on authentic business logic. In his view, the best way to face the future is not to guess how markets will fluctuate, but to build a system that continues to function through volatility.
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