jevbooks

← All projects

jev-trader

dnevado/jev-trader

Backtesting and paper trading US equities with typed AI decisions.

Finance & Trading0.91Runner-up: Agent DecisionsFunnel
Automated README summary

Automatically summarized from the README on 7 Oct 2026; not a run by jevbooks. Run instructions and author-reported outcomes still need verification.

What it is

An end-to-end quantitative research platform for US equities: data ingestion, pandas technical indicators, LLM-assisted fundamentals, typed AI decisions, a custom backtest engine with walk-forward validation, and scheduled AWS paper trading on Alpaca.

How it uses Jev

Jev (TypeSafe AI) returns typed, probabilistic answers (probabilities, scores, choices) instead of free text, used per ticker and per rebalance date on technical features (data ≤ t-1) and an OpenAI summary of fundamentals. Every paid call goes through a deterministic disk cache.

Primitives:choicescorenoul

Technique worth stealing

Treat look-ahead bias as a bug class: decisions see only data up to the previous close, fundamentals filtered by publication date, orders fill at next open.

Try it

uv pip install -r requirements.txt -e . then python -m jevbt backtest --strategy trend --direction long

View on GitHub

Start using Jev: API key and your first request →

Model judgments from README excerpts

Project signals use repository metadata, an existing summary and the first 700 README characters, not the full project. “Not found” means not detected in that material; it does not establish absence. These are the original judgments with recorded models and dates, not source audits or run results.

Models & evaluation dates

Inclusion gate
jev-1.13.0
Project signals
jev-1.13.0
Category
jev-1.13.0
Pattern tags
jev-1.13.0

Evidence

These signals use repository metadata, an existing summary and at most 700 cleaned README characters. ≥ 0.60 means reported in that excerpt; ≤ 0.40 means not found there. The middle band is inconclusive. None is a source-code audit or a test result. The runnable-tool question excludes research experiments; the recommendation question asks for a learning shortlist, not a quality verdict.

  • Jev is core to the projectunclear0.43
  • Shows a System One patternunclear0.55
  • Describes handling uncertaintynot found in the excerpt0.06
  • Reports measured numbersnot found in the excerpt0.06
  • Is a runnable toolFound in material0.68
  • Top-10 learning shortlist signalunclear0.43
  • Is a replica of the modelnot found in the excerpt0.11
  • Solves a common problem (0–2)score on a 0–2 scale0.98 / 2
  • About JevFound in material0.96
Signals
Jev is core to the project0.43Shows a System One pattern0.55Describes handling uncertainty0.06Reports measured numbers0.06Is a runnable tool0.68Top-10 learning shortlist signal0.43Is a replica of the model0.1100.51Solves a common problem (0–2)0.98 / 2012

no-judgment band (0.40–0.60)

Design patterns
Funnel0.82Check-up0.58Thermostat0.30Flight recorder0.30Inspection0.2800.51

no-judgment band (0.40–0.60)

The Jev model and date for each judgment stage are listed above. Card written by DeepSeek V4.1 Flash from the README on 7 Oct 2026.