交易與金融

TradingAgents 結合基本面、情緒、新聞及技術分析，並加入多空研究討論、交易員與風險管理角色。 設定 TYPESAFE_API_KEY 後，Jev 會移除無關的 StockTwits 和 Reddit 貼文並判斷立場；未設定時則直接傳入貼文。

這套自架交易系統涵蓋 Python 策略、回測、模擬交易、實盤執行與監控。 Jev 評估訂單、策略、曝險、部位及預算資訊，為進場篩選傳回具型別的選擇與機率。

機器人隨 Monad 區塊更新只掛單限價報價，並把委託簿、訂單及成交事件串流至儀表板。 設定 MODEL=jev 和 TYPESAFE_AI_API_KEY 後，由 Jev 選擇買或賣；預設 mock 模型僅是動量啟發式。

AI Stock 彙整行情、新聞與 AI 分析，用於股票研究、篩選及模擬交易。 選用的 JEV Decisions only 回傳買入、賣出、持有及機率、信心值；研究聊天與選股範圍仍需 LLM。 設定模型與資料源，選擇股票，再檢查已儲存報告的證據、日期及風險。

Live Jev trader on Hyperliquid

AI-driven intraday trading bot for Indian stocks. Jev ranks the Nifty 50 every 15s; code sizes each trade and places the stop; orders go live through Zerodha Kite or Kotak Neo. Day replay, kill switch, daily loss halt, terminal dashboard.

5m BTC Up/Down Polymarket trading agent using Typesafe Jev as the decision layer & TUI

Trading bot with the all new TypeSafe AI's first system one model named as Jev

24/7 market-making system around Jev (TypeSafe System One) decisions: deterministic state, calibrated judgments, hard risk vetoes.

Read-only trading journal and review harness: Jev typed judgments, agent integration, and a reproducible finance benchmark. No orders, no advice.

Unofficial study: Jev-style parallel typed decisions on stock 1.5B-8B models on an Apple Silicon laptop. Benchmarks, research notes, and a Hugging Face Space demo.

An experimental JEV-powered framework for forecasting short-term stock price direction from structured market data.

Polymarket trading bot driven by Jev (TypeSafe AI) via OpenRouter

Modular trading framework for Mid-Frequency Trading

Backtest Jev (TypeSafe) as a BUY/SELL/HOLD trader on NQ L10 order-book data

JEV-powered market decision bot for stocks, crypto and memes. State in, BUY/SELL/HOLD/AVOID out, paper by default

Live Moomoo trading dashboard with TypeSafe Jev market reviews

Desktop app for paper-trading stocks and crypto on live prices, with TypeSafe's Jev making the calls and your stops, targets and limits enforced in code. Windows and macOS; never touches real money.

Experimental multi-horizon BTC signal generator using TypeSafe Jev probabilities and Binance market data.

Hands-on LangChain examples of Jev, TypeSafe AI's decision model: support ticket triage, model routing, reply guardrails, tool selection and finance-inbox fraud checks. An LLM writes; Jev decides.

Self-hosted AI trading intelligence platform - scoring engine, two-model AI analyst (Claude + TypeSafe Jev), risk engine, discipline guardian, backtester, React dashboard

Options trading bot (backtest + Alpaca paper only) with TypeSafe Jev as the decision core

Typed System-1 decisions (Laya/Jev) as the judgment layer of a quant research stack, with Claude as System 2. Requirements → design → code → experiments.

目前沒有專案說明。