Colin Wirz

03 / SYSTEMResearch + execution platform

Tradingplatform

A full path from an interesting market idea to monitored paper trading. Every strategy has to survive evidence before it gets trust.

research01
backtest02
paper + monitor03

Ideas face data before capital

01 / The rule

Most strategies should die in research.

A good-looking backtest is easy to manufacture by accident. The platform treats that as a starting point, then checks out-of-sample behaviour, parameter stability, market regimes, fees and slippage.

Weak ideas stop there. Survivors move forward with their limitations written down instead of hidden behind one headline return.

02 / The pipeline

Research. Backtest. Paper. Monitor.

Vectorized research makes broad experiments cheap. Walk-forward validation tests whether an edge transfers beyond the data that found it. The same strategy then runs against real exchange data in paper mode.

That last step catches the operational failures a notebook cannot: stale feeds, reconnects, order state, position sizing and what happens after a process restarts.

03 / The goal

Many small edges, fewer heroic bets.

I would rather combine simple strategies that behave differently than search forever for one perfect system. Monitoring keeps the evidence current and makes it possible to retire an edge when the market changes.

04 / Research + runtime

  • Python
  • VectorBT Pro
  • Jesse
  • Django / DRF
  • PostgreSQL
  • Redis
  • Docker
  • GitLab CI/CD

Working on systematic trading or research infrastructure?

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