Systematic Trading, Fully Automated

Auroxyl Capital is a private, fully automated quantitative trading operation on U.S. equities and ETFs. One codebase runs everything: daily data pipeline, factor computation, portfolio construction, risk overlays, and order execution through Interactive Brokers — with no discretionary intervention.

Strategy Architecture

AUX-MOM

Residual-Momentum Industry Leaders

Buys large and mid-cap industry leaders whose momentum survives after stripping out market beta — the stock's own strength, not the market's. Quality confirms the move.

  • Core signal: 12-1 month residual momentum (Blitz-style, market-neutralised)
  • Quality gates: gross-margin trend, earnings surprise, forward EPS revisions, FCF
  • Path durability: consistency of gains beats magnitude of gains
  • 5 names, equal weight, monthly rebalance; broken-leader filter at entry
  • LLM evidence review holds veto power over every final book

AUX-VALUE

Quality Value with a Trap Guard

Buys the intersection of cheap and good: earnings/book yield crossed with durable margins and returns on capital — then interrogates whether the cheapness is credible.

  • Value leg: earnings + book yield, ranked within industry
  • Quality leg: operating margin, ROA, ROE — durable, not flashy
  • JunkGuard: penalises fake earnings, share dilution and structural decay
  • Hard exclusions: negative equity, heavy dilution, value-trap signatures
  • 5 names; sector blacklist on structurally cheap-forever industries

AUX-COMBINED

Regime-Weighted Flagship

The flagship book: AUX-MOM and AUX-VALUE blended by risk parity, then tilted by a momentum-regime probability model — leaning into whichever engine the market currently pays.

  • Anchor: inverse-volatility risk parity, shrunk toward long-run sleeve priors
  • Tilt: logistic momentum-regime probability (p_mom), refreshed daily, half-width ±0.40
  • Weight recomputed at every rebalance, clamped to [20%, 80%] — both sleeves always invested
  • Low cross-correlation (~0.5) between engines does the heavy lifting

AUX-SHIELD

All-Weather Capital Shield

The ballast: a CPPI-floored all-weather book across Treasuries, commodities, gold, the dollar and an equity engine — built to compound quietly and cap drawdowns in the single digits.

  • Inverse-volatility risk parity across macro diversifiers
  • Per-leg trend gates — no leg is held against its own downtrend
  • CPPI floor with volatility targeting and a drawdown brake
  • Deterministic vol-complex signals (VIX term structure, MOVE) — zero ML

Principles Over Predictions

The edge is not a secret signal — it is a research process that kills bad ideas faster than the market can punish them.

01

Literature-anchored factors. Every factor is a construction with a known economic mechanism and a decades-long public record — momentum, value, quality, issuance. Sign known before testing; no mined interactions.

02

Validation before deployment. Shuffle-null tests, walk-forward folds, multi-offset entry perturbation, parameter-flatness checks. Over 90% of researched ideas fail and are archived, not retried until they pass.

03

Hold, don't fiddle. Exit research converged on a hard result: no stop-loss or ML exit policy beat holding to the rebalance date. The system trades on schedule, not on emotion — because it has no emotions.

04

Risk lives at the portfolio layer. Entry gates and exit rules failed every test; volatility-complex overlays and regime weighting passed. Risk is managed where the statistics say it can be — above the stock picks, not inside them.

05

Honest expectations. Live performance is internally budgeted conservatively against research results — expectations are set below what the numbers show, never above.

About the Founder

Taocheng Qian
Taocheng Qian
Founder & Developer

Taocheng designed and built the entire Auroxyl platform from the ground up — from the daily data pipeline and alpha factor research to the C#/.NET execution engine and IBKR integration. Every component, from data ingestion to order routing, is his work.

His background in data science provides the quantitative foundation for the system's statistical approach: walk-forward validation, bootstrap significance testing, and rigorous overfitting diagnostics are core to the research process.

Bachelor of Science
Major in Data Science
University of Melbourne

Technology Stack

Python
Research & Data

Daily pipeline over Polygon market + fundamentals data; point-in-time factor panels; full research harness with parity-gated incremental rebuilds.

C# / .NET
Execution Engine

WPF production app: scheduling, umbrella rebalancer, risk overlays, broker truth reconciliation, circuit breakers, deploy verification.

IBKR
Brokerage & Data

Gateway with automated session management, API health probes and graceful restart — hands-free connectivity around the clock.

LLM
Evidence Review

Web-search-grounded LLM overlay reviews every final selection for disqualifying evidence — veto power only, never discretionary picks.

Collaboration Enquiries

Not accepting investors. Open to research collaboration and partnership.

[email protected]

Important Disclosure

Past performance is not indicative of future results. All performance data referenced is gross of fees. Live trading commenced in February 2026. The AUX series are internal sleeve designations, not registered funds or exchange-traded products, and are not available for investment.