FinEval
github.comThe FinEval financial domain evaluation benchmark, based on quantitative fundamental methods and developed through long-term objective research, summarization
- GitHub stars
- 288
- Language
- Python
- Code license
- Apache-2.0
DUCKQUANT / THE QUANT & AI DIRECTORY
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The FinEval financial domain evaluation benchmark, based on quantitative fundamental methods and developed through long-term objective research, summarization
R - The premier open source software solution for teaching and training quantitative finance. fAsianOptions - EBM and Asian Option Valuation. fAssets -...
Proprietary local backtesting and optimization CLI with a permanent free plan requiring no registration, limited to historical data through 2023-12-31; Pine…
Python - REST API analyzing Reddit and X/Twitter for stock mentions and sentiment, providing buzz scores, trending stocks, and AI-generated trend explanations.
The most simple, flexible, and comprehensive OpenAI Gym trading environment (Approved by OpenAI Gym).
Chinese financial chat LLM from Du Xiaoman Financial. Hundreds of billions of parameters, fine-tuned on financial domain data
Fin-R1 is a large language model for complex financial reasoning developed and open-sourced with the joint efforts of the SUFE-AIFLM-Lab at the School of.
Search, social, commerce, and news-sentiment data for alternative-data research, with a permanent free tier of 100 requests/month, 90 days of history, and top-1
No-code crypto backtesting platform with 100+ indicators, AI sentiment signals, and 5+ years of historical data across 1,000+ trading pairs.
Cryptocurrency market alerts, screeners, and funding-rate, liquidation, and chart-pattern boards, with a permanent free tier of five active alerts and ten notif
Data - Free Korean equity settled closes with 250 trading days of per-stock history, DART filings and earnings as JSON/CSV, without signup, an API…
Real-time RSI signals, price action, and volume spikes dashboard across multiple exchanges. Free, no sign-up required.
AI-driven real-time stock scanning, backtesting and alerting platform for day traders.
"Agent-native trading platform"; any AI agent (OpenClaw / nanobot / Claude Code / Codex / Cursor) registers via SKILL.md and trades live on AI4trade.ai…
Community finance workspace with research, strategy, and news agents; connects to Binance, OKX, and Hyperliquid; includes macOS and Windows desktop apps
Quantitative Financial Modelling Framework R · 0
LLM - Multi-agent financial research framework combining fundamental, technical, news, and sentiment analysis with structured investment debates and risk…
Natural-language multi-agent finance research agent with 29 swarm presets, 70 skills, and 28 auto-discovered tools; 7 backtest engines covering…
This repository introduces PIXIU, an open-source resource featuring the first financial large language models (LLMs), instruction tuning data, and evaluation…
TimeGPT-2.1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series…
Agent-driven A-share factor research engine with 8 MCP tools covering hypothesis design, backtesting, scoring, and anti-overfit detection
Note: is not listed yet because its terminal has not launched. It can be added once the project is publicly usable
Multi-agent trading system where agents compete internally before one view is selected for the final decision
TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting.
Salesforce's masked encoder-based universal forecasting transformer, pre-trained on LOTSA (27B observations, 9 domains); handles any frequency and any number…
First open-source decoder-only foundation model for probabilistic time series forecasting; developed by Morgan Stanley, ServiceNow, and Mila
Amazon's pretrained time series models; Chronos-2 (120M params) handles univariate, multivariate, and covariate-informed zero-shot forecasting
Live AI-agent competition and research platform; uses real-market conditions to improve agents
Python-based stock analysis tool that combines traditional technical analysis with AI prediction capabilities. Providing comprehensive stock analysis and
Multi-agent fund-investment benchmark; LLM analysts evaluate stocks in a unified trading arena with leaderboard
"Deep Thinking Trading System" tutorial implementation; beginner-friendly multi-agent example design
Self-improving AI trading system with 25 agents, Karpathy-style autoresearch, Darwinian selection, autonomous agent spawning, and multi-cohort meta-weighting
Decoder-only foundation model pre-trained on OHLCV candlestick sequences from 45+ exchanges, with a tokenizer that quantizes K-lines into hierarchical discrete…
Find company insights, market data and research across 500M+ documents instantly. Make faster, confident decisions with AlphaSense's AI-powered platform.
AtlasYield Atlas Score daily snapshots - timestamped ex-ante scoring history, published automatically.