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Synapse Quant

Paper simulation AI / Finance

Synapse Quant is an experimental paper-trading system running on a dedicated Mac mini. Real money is outside its scope. The recorded trial ended without any paper orders or positions.

My role. I built a simulated trading workflow with safeguards and logs so I could inspect what the system decided during a trial.

See the trial

What the recorded trial showed

A paper-only trial produced logs for review. The result below describes the recorded trial.

  1. Collect and analyze

    Recorded trialNine eligible analyses

    The Core analyzed BTC, ETH and SOL under the configured conditions.

  2. Evaluate the signal

    Recorded resultNo signal

    All nine eligible analyses ended without a trading signal.

  3. Review the outcome

    Paper ordersZero orders or positions

    The run produced no paper orders. Native buy/sell execution and autonomous operation remain unproven.

Design decision I kept the trial in paper mode and retained the logs so the observed outcome can be reviewed without claiming trading performance.

The problem

The experiment explores data collection, analysis and execution safeguards in a simulated trading environment.

How it works

  1. Collect Gather market data.
  2. Analyze Evaluate the configured conditions.
  3. Guard Keep execution within the paper-only safety rules.
  4. Review Inspect logs and recorded test evidence.

What it includes

  • Paper simulation only
  • Python and SQLite
  • Recorded trial logs
  • Execution safeguards under development

Project status

No paper orders were executed in the recorded trial. Native buy/sell execution and autonomous operation remain unproven.

Technical details

Python and SQLite on a dedicated Mac mini. Architecture diagrams describe components, not proof of trading performance.

  • Python 3
  • SQLite
  • Healthchecks.io
  • Telegram Bot API
  • Mac mini 2018
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