03 / Projects Xinyue Zhang

Projects

AlphaRefinery: LLM-assisted alpha-factor research

Independent development · 2026 · Code

I built AlphaRefinery, an LLM-assisted platform for structured alpha-factor research that generates economically interpretable candidates by recombining market features and operators across economic themes. I designed the factor registry, staged search, and experiment memory to support iterative generation, evaluation, and refinement. UCB-style exploration and MMR reranking balance candidate quality and diversity, while evaluation considers predictive power, transaction costs, robustness, and redundancy with existing factors.

Inside AlphaRefinery

A research loop, step by step.

Explore how a factor family moves from an initial idea to evaluation and continued refinement. This architecture demonstration follows the public project design; it does not display measured factor performance.

01 / SEED

Start with a factor family.

A seed family defines the economic idea, its initial factors, and the boundary of the search. The family retains its search history so each round can build on what is already known.

Research artifact Seed definition + family state

02 / EXPLORE

Generate candidates with context.

Broad search opens the space of possible expressions. Anchor selection identifies promising parents for focused refinement, while multiple branches preserve alternatives beyond the current highest-scoring candidate.

Research artifact Candidate expressions + parent branches

03 / EVALUATE

Let evidence guide the next step.

Evaluation feedback informs candidate selection and continuation. The chosen objective changes the emphasis: standalone alpha, practical deployability, or complementarity with existing factors.

Research artifact Evaluation feedback + family report

04 / REFINE

Decide how the family should evolve.

The continuation policy can deepen focused search, reopen broad exploration, switch objectives, confirm results, or stop. Selected candidates can be promoted into the formal factor library, with reports preserving the research trail.

Research artifact Continuation decision + selected factors

Workflow guide · Read the architecture and code ↗

A page outside the notebook

Beyond research

I love traveling and exploring the world. Meeting people from different backgrounds and hearing their stories gives me fresh perspectives, inspires new ideas, and encourages me to reflect on my own life.

Postcards from my days away 07 photographs · tap to explore

At a time when AI agents and vibe coding are rapidly changing how ideas become reality, I hope to use these tools thoughtfully to build projects and pursue research that are both interesting and meaningful.

My ideal life is to keep coding, exploring quantitative strategies, and following questions that genuinely excite me—all while experiencing different coastlines and new corners of the world.

Celina

Beyond research

Travel photograph

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