Founder-engineer, quantitative research Evidence first, narratives second

Afshin Moshrefi

Afshin Moshrefi is a founder-engineer and quantitative researcher behind Tara Data Research LLC, a company that builds market analytics and research products. Its products include TradeWave.ai, a quantitative seasonality and regime research platform, and Seasonal Market News, an institutional-style market news channel that produces data-backed articles for professionals and retail traders. Seasonal Market News is available today at tradewave.ai/news, with a dedicated standalone site planned at SeasonalMarketNews.com.

Scope
Multi-decade pattern research designed for repeatability, not one-off backtests.
Scale
Built to run continuously, from indexing and UI workflows to publishing pipelines.
Focus
Seasonality, regime behavior, and election-cycle context framed as measurable patterns.
Afshin Moshrefi
Now
Operating TradeWave research and publishing Seasonal Market News for data-backed market context.
tradewave.ai/news
Core product
TradeWave.ai surfaces historical seasonal windows and regime behavior, including election-cycle context where relevant.
tradewave.ai
Company
Tara Data Research LLC is the umbrella for the products and the quantitative pipeline that powers them.
taradataresearch.com

What I build

Moshrefi approaches markets as an engineer. Define the behavior, measure it across time, then ship tooling that makes decisions easier to evaluate. He is not a traditional finance-industry insider, and that constraint is intentional. The work is oriented around clarity, reproducible research, and systems that can be improved through usage and evidence.

Data systems

  • Market data ingestion and normalization across long time horizons.
  • Seasonality and regime analysis, including election-cycle behavior where relevant.
  • Metadata indexing and research workflows built for speed and repeatability.

AI applied to real workflows

  • Publishing pipelines grounded in measurable history, not opinions.
  • Explanations that separate strong signals from weak signals.
  • Deterministic processes where outputs can be reproduced and audited.

Background

Moshrefi’s work has consistently centered on building practical systems before the category names existed. His background spans software engineering, invention work, and applied machine learning in regulated environments.

  • Built an early medical image management platform adopted across multiple clinical specialties, including gastroenterology, dermatology, and dentistry.
  • Created InstantWeb in the late 1990s, a website generator that let users publish a web presence in minutes, years before mainstream blog-based site builders became common.
  • At Verizon, authored 16 invention disclosures, including work related to video communication concepts over conventional telephony infrastructure.
  • Began focused work in machine learning in 2013 and completed formal training by 2017.
  • Worked as an AI researcher in medical coding, developing applied ML systems for real-world production use.
  • TradeWave began as a personal research project and evolved into a platform after the results proved unusually consistent and useful.

Projects

Selected products operated by Tara Data Research LLC.

Parent company

Tara Data Research LLC

Applied research and product development focused on market behavior, analytics infrastructure, and production publishing systems.

SaaS platform

TradeWave.ai

A quantitative seasonality and regime research platform designed to surface historically consistent windows and provide testable context around market moves.

Media engine

Seasonal Market News

An institutional-style market news channel producing data-backed articles grounded in measurable history. Available at tradewave.ai/news, with a dedicated standalone experience planned for SeasonalMarketNews.com.

Book

The 100-Year Pattern

A research-driven book documenting a long-horizon seasonal market pattern and the framework used to test it across regimes. It serves as a public explanation of the thesis behind TradeWave’s seasonality and election-cycle research.

The 100-Year Pattern book cover

Approach

Operating principles prioritize shipping useful systems: tight feedback loops, measurable outputs, and clarity over complexity.

What you can expect

  • Clear definitions and measurable claims.
  • Fast iteration driven by real usage.
  • Production-first engineering with visible failure modes.

What I avoid

  • Vague narratives that are not testable.
  • Black-box outputs without context.
  • Overconfident conclusions when evidence is mixed.

Contact

For product, quantitative research tooling, data systems, or partnership discussions, email is best.