Skip to content

jev-trader

Trade Arena proof of concept comparing trading strategies on 13 US stock funds, grown out of a pre-registered Jev study.

Projectprototype

Overview

jev-trader (Trade Arena) is a site where you pick two well-known trading strategies and see, in plain words, what $1,000 became in each on the same 13 US stock funds. It is a proof of concept that grew out of a finished study of Jev, TypeSafe's decision model, against technical-analysis rules.

A research directory computes the results, a `jt export` command writes the Jev study's data, `jt arena` writes the arena data, and a static Next.js site reads only those files. The site currently lands on the Jev study's pre-registered holdout result, with the Pick two prototype on a preview page; the plan is to move the study to its own page and make the arena the home page. Product, implementation and design-decision documents are included and still changing. The README itself does not state the study's outcome.

What the decision model decides

TypeQuestionAnswers
ChoiceShould the strategy buy, sell or hold this fund? (Jev arm of the study)(inferred)—

How it works

  1. Research code computes strategy results on 13 funds
  2. Export study and arena data files
  3. Static site reads the files and presents plain-language comparisons

Strengths

  • Pre-registered holdout design for the Jev study
  • Static site reads only exported data, keeping numbers consistent

Caveats

  • Proof of concept; plans still changing
  • Study result not stated in the README

At a glance

Type
Project
Status
prototype
Language
Python
Runtime
CLI research + static Next.js site
Has code
yes

Use cases and integrations

How curated lists describe it

Frequently asked questions

What is Trade Arena?

A site comparing what $1,000 became under two chosen strategies on the same 13 US stock funds.

How does Jev fit in?

The project grew out of a pre-registered study of Jev against technical-analysis rules, shown on the site.

Is it finished?

No, it is a proof of concept with milestones still planned.

Related projects

  • PyTorch factor-research stack with 213 factors and cost-aware backtests, plus a preview typed portfolio-decision adapter.

    ProjectbetaPython
  • Reproducible test of viral Jev HFT claims: direction not calibrated, never under 100 ms, and no edge after trading fees.

    ServiceresearchPython
  • Point-in-time O'Neil momentum backtest where Jev picks entries and judges exits, with a jackknife showing no resolvable edge over rules.

    ProjectresearchPython
  • Decision Lab: sixty finance demos asking Jev, OpenAI Decisions and twelve other decision models the same questions, graded.

    ProjectresearchJavaScript
  • Backtest harness that tests Jev as a BUY/SELL/HOLD trader on NQ level-10 order-book data, with replay, viewer and paper-trading modes.

    ProjectresearchPython
  • Study of whether Jev's reading of financial news predicts stock returns: strong same-day signal, no tradeable alpha.

    BenchmarkresearchGo