Best AI tools for< Quantitative-analyst >

Three Sigma is a quantitative hedge fund that uses advanced artificial intelligence and machine learning techniques to identify and exploit trading opportunities in global financial markets.

Quant Prep AI is an AI Chrome extension designed for GRE & GMAT quantitative preparation. It assists users in identifying and practicing strategies for solving quantitative questions. The extension provides tips and detailed solutions for quant problems, helping users enhance their quantitative skills efficiently.

Fintwit is an AI-powered stock market analysis tool that provides users with stock market quotes, free screener, AI top picks, AI stock analysis, market news, and trading signals. The platform leverages artificial intelligence to offer valuable insights and recommendations to investors and traders. With Fintwit, users can access real-time data, make informed investment decisions, and stay updated on the latest market trends.

Dark Pools is a leading provider of AI-powered solutions for the financial industry. Our mission is to empower our clients with the tools and insights they need to make better decisions, improve their performance, and stay ahead of the competition. We offer a range of products and services that leverage AI to automate tasks, optimize workflows, and generate actionable insights. Our solutions are used by a wide range of financial institutions, including hedge funds, asset managers, and banks.

Bloomberg is a leading global provider of financial data, news, and analytics. The company is known for its innovative technology solutions, including the Bloomberg Terminal, which revolutionized the industry by delivering critical insights and actionable information to financial decision-makers. Bloomberg is at the forefront of artificial intelligence, machine learning, and natural language processing, offering tools and automated workflows to help clients navigate the vast amount of data available in the financial markets. With a focus on engineering value for customers and keeping humans in the loop, Bloomberg continues to drive innovation and provide cutting-edge technology solutions for over 325,000 financial professionals worldwide.

Tradytics is a platform that bridges the gap between Wall Street and Retail Traders by simplifying complex trading data, making it accessible and actionable for every trader. The platform offers a comprehensive toolkit for all types of traders, providing data that only Wall Street professionals have access to. Tradytics combines news for every stock and summarizes them with AI to keep traders up to date. With a focus on transparency and expertise in AI, Tradytics aims to become a one-stop shop for retail traders.

AI Signals is an AI trading application that provides cutting-edge AI trading tools and signals for a diverse range of crypto pairs. The platform offers advanced AI algorithms that ensure precise and timely signals for trading, enhancing trading performance and delivering consistent long-term success. With a focus on accuracy, reliability, and user satisfaction, AI Signals stands out as the ultimate choice for traders seeking to maximize gains and minimize risks in the cryptocurrency market.

Trade Ideas is an AI-driven stock scanning and charting platform that provides unmatched precision in finding the biggest movers first. It offers AI-powered Buy/Sell signals, real-time market scanning, customizable alerts, advanced charting capabilities, and time-saving data visualization. Users can access the platform on any device, empowering them to make smarter trading decisions and stay ahead of the game. Trade Ideas also features a live trading room with expert market commentary and a simulator for practicing new trading strategies under actual market conditions. The platform is trusted by leading brokers and trading platforms, offering users a competitive edge in the market.

Dotbee.ai is a private AI analyst tool designed for traders in the financial markets, offering analysis on CFD, Forex, Crypto, and Stocks Exchange. The tool provides over 35,000 indexes, 150 indicators, pattern and candle analysis, support and resistance levels, as well as fundamental, technical, and sentimental analysis. Powered by AI, Dotbee.ai delivers real-time insights to help users make informed decisions in the dynamic and complex markets.

Ailtra's AI Crypto Bot is a revolutionary trading tool that leverages artificial intelligence to maximize profits and minimize losses in the cryptocurrency market. With its advanced algorithms, smart fund management, and risk-free trading experience, Ailtra empowers traders of all levels to achieve consistent profitability. The AI Crypto Bot's 13 levels of holding capacity and intelligent trading strategies ensure that your investments are in capable hands, guiding you through the complexities of the crypto market.

TradeUI is a comprehensive trading platform that provides advanced tools and resources for stock and options traders. It offers a range of features powered by artificial intelligence (AI), including AI sentiment analysis, option flow analysis, and AI pattern recognition. These tools help traders make informed decisions and identify potential trading opportunities. TradeUI also provides educational videos, a vibrant community, and a unified ecosystem for traders to connect and share knowledge.

Web3 Summary is an AI-powered platform that simplifies on-chain research across multiple chains and protocols, helping users find trading alpha in the DeFi and NFT space. It offers a range of products including a trading terminal, wallet study tool, Discord bot, mobile app, and Chrome extension. The platform aims to streamline the process of understanding complex crypto projects and tokenomics using AI and ChatGPT technology.

Stockpulse is an AI-powered platform that analyzes financial news and communities using Artificial Intelligence. It provides decision support for operations by collecting, filtering, and converting unstructured data into processable information. With extensive coverage of financial media sources globally, Stockpulse offers unique historical data, sentiment analysis, and AI-driven insights for various sectors in the financial markets.

Capital Companion is an AI-powered trading and investing platform designed to provide users with a competitive edge in the markets. The platform offers a range of features including 24/7 AI assistant support, intelligent trading recommendations, risk analysis tools, real-time stock analytics, market sentiment analysis, and pattern recognition for technical analysis. By leveraging artificial intelligence, Capital Companion aims to help traders make well-informed decisions and protect their investments in a dynamic market environment.

NITG Inc is the world's leading AI quantitative trading platform that combines innovative technologies such as AI, blockchain, and big data analysis to provide intelligent quantitative services. The platform offers efficient and secure trading solutions, automated intelligent trading system, excellent customer support, professional guidance, and top technical team to ensure a stable and reliable trading environment. NITG's AI quantitative trading strategies enable emotion-free decision-making, efficient execution, enhanced risk control capabilities, and adaptability to different market environments. The platform is committed to safeguarding users' funds and data through high-security measures and transparent trading practices.

Quadrature is an AI-powered automated trading business founded by programmers in 2010. The company utilizes sophisticated data and powerful technology to trade securities globally based on predictions made by statistical models. Their long-term vision is to trade all liquid electronically tradeable asset classes across all horizons to generate consistent, significant returns on their proprietary capital. Quadrature Climate Foundation (QCF) was established in 2019 as an independent foundation dedicated to addressing climate change through science-led philanthropy and high-impact solutions.

AskJimmy is a platform for AI agents focused on finance and trading. It offers exposure to a diverse range of strategies managed by top-notch AI Agents. The platform allows users to compose autonomous agents and trading strategies with extreme customization. It aims to create a decentralized multi-strategy collaborative hedge-fund powered by AI agents. AskJimmy is designed to aggregate non-correlated autonomous agent strategies into a diversified subnet, shaping the future of multi-strategies decentralized hedge-fund.

Composer is an AI-powered platform designed for investing, offering users the ability to build trading algorithms with AI, backtest them, and execute trades all in one place. The platform does not require coding skills and provides a user-friendly experience for creating and managing investment strategies. Composer aims to make sophisticated quant investing accessible to all users, regardless of their level of expertise.

Finance Wizard is an AI-powered financial analytics tool that provides users with advanced stock predictions and market insights. By leveraging cutting-edge AI technology, Finance Wizard automates data analysis, allowing investors to focus on strategic decision-making rather than spending hours on market research. The tool is designed to empower users with accurate predictions and real-time insights to optimize trading strategies and enhance market understanding.

Toggle Terminal is an AI-powered platform that brings data to life with natural language. It offers a suite of award-winning analytic tools wrapped in an accessible, natural language-based user experience. Users can ask questions in plain language and receive immediate, data-backed answers without the need for coding or spreadsheet manipulation. Toggle Terminal provides institutional-grade analytical tools for scenario testing, asset intelligence, chart exploration, and idea discovery. It helps users connect data, test market hypotheses, screen securities, and explore hidden relationships between organizations. Additionally, Toggle AI offers customized AI solutions and integrations for institutional investors in asset management and capital markets.

2025-AI-College-Jobs is a repository containing a comprehensive list of AI/ML & Data Science jobs suitable for college students seeking internships or new graduate positions. The repository is regularly updated with positions posted within the last 120 days, featuring opportunities from various companies in the USA and internationally. The list includes positions in areas such as research scientist internships, quantitative research analyst roles, and other data science-related positions. The repository aims to provide a valuable resource for students looking to kickstart their careers in the field of artificial intelligence and machine learning.

This repository contains a collection of articles and tutorials on quantitative finance, including topics such as machine learning, statistical arbitrage, and risk management. The articles are written in a clear and concise style, and they are suitable for both beginners and experienced practitioners. The repository also includes a number of Jupyter notebooks that demonstrate how to use Python for quantitative finance.

AData is a free and open-source A-share database that focuses on transaction-related data. It provides comprehensive data on stocks, including basic information, market data, and sentiment analysis. AData is designed to be easy to use and integrate with other applications, making it a valuable tool for quantitative trading and AI training.

Qlib is an open-source, AI-oriented quantitative investment platform that supports diverse machine learning modeling paradigms, including supervised learning, market dynamics modeling, and reinforcement learning. It covers the entire chain of quantitative investment, from alpha seeking to order execution. The platform empowers researchers to explore ideas and implement productions using AI technologies in quantitative investment. Qlib collaboratively solves key challenges in quantitative investment by releasing state-of-the-art research works in various paradigms. It provides a full ML pipeline for data processing, model training, and back-testing, enabling users to perform tasks such as forecasting market patterns, adapting to market dynamics, and modeling continuous investment decisions.

Jupyter Quant is a dockerized environment tailored for quantitative research, equipped with essential tools like statsmodels, pymc, arch, py_vollib, zipline-reloaded, PyPortfolioOpt, numpy, pandas, sci-py, scikit-learn, yellowbricks, shap, optuna, ib_insync, Cython, Numba, bottleneck, numexpr, jedi language server, jupyterlab-lsp, black, isort, and more. It does not include conda/mamba and relies on pip for package installation. The image is optimized for size, includes common command line utilities, supports apt cache, and allows for the installation of additional packages. It is designed for ephemeral containers, ensuring data persistence, and offers volumes for data, configuration, and notebooks. Common tasks include setting up the server, managing configurations, setting passwords, listing installed packages, passing parameters to jupyter-lab, running commands in the container, building wheels outside the container, installing dotfiles and SSH keys, and creating SSH tunnels.

Jupyter Quant is a dockerized environment tailored for quantitative research, equipped with essential tools like statsmodels, pymc, arch, py_vollib, zipline-reloaded, PyPortfolioOpt, numpy, pandas, sci-py, scikit-learn, yellowbricks, shap, optuna, and more. It provides Interactive Broker connectivity via ib_async and includes major Python packages for statistical and time series analysis. The image is optimized for size, includes jedi language server, jupyterlab-lsp, and common command line utilities. Users can install new packages with sudo, leverage apt cache, and bring their own dot files and SSH keys. The tool is designed for ephemeral containers, ensuring data persistence and flexibility for quantitative analysis tasks.

Qbot is an AI-oriented automated quantitative investment platform that supports diverse machine learning modeling paradigms, including supervised learning, market dynamics modeling, and reinforcement learning. It provides a full closed-loop process from data acquisition, strategy development, backtesting, simulation trading to live trading. The platform emphasizes AI strategies such as machine learning, reinforcement learning, and deep learning, combined with multi-factor models to enhance returns. Users with some Python knowledge and trading experience can easily utilize the platform to address trading pain points and gaps in the market.

RD-Agent is a tool designed to automate critical aspects of industrial R&D processes, focusing on data-driven scenarios to streamline model and data development. It aims to propose new ideas ('R') and implement them ('D') automatically, leading to solutions of significant industrial value. The tool supports scenarios like Automated Quantitative Trading, Data Mining Agent, Research Copilot, and more, with a framework to push the boundaries of research in data science. Users can create a Conda environment, install the RDAgent package from PyPI, configure GPT model, and run various applications for tasks like quantitative trading, model evolution, medical prediction, and more. The tool is intended to enhance R&D processes and boost productivity in industrial settings.

This repository provides a comprehensive collection of resources, open-source tools, and knowledge related to quantitative analysis. It serves as a valuable knowledge base and navigation guide for individuals interested in various aspects of quantitative investing, including platforms, programming languages, mathematical foundations, machine learning, deep learning, and practical applications. The repository is well-structured and organized, with clear sections covering different topics. It includes resources on system platforms, programming codes, mathematical foundations, algorithm principles, machine learning, deep learning, reinforcement learning, graph networks, model deployment, and practical applications. Additionally, there are dedicated sections on quantitative trading and investment, as well as large models. The repository is actively maintained and updated, ensuring that users have access to the latest information and resources.

The ai_quant_trade repository is a comprehensive platform for stock AI trading, offering learning, simulation, and live trading capabilities. It includes features such as factor mining, traditional strategies, machine learning, deep learning, reinforcement learning, graph networks, and high-frequency trading. The repository provides tools for monitoring stocks, stock recommendations, and deployment tools for live trading. It also features new functionalities like sentiment analysis using StructBERT, reinforcement learning for multi-stock trading with a 53% annual return, automatic factor mining with 5000 factors, customized stock monitoring software, and local deep reinforcement learning strategies.

Polymarket Agents is a developer framework and set of utilities for building AI agents to trade autonomously on Polymarket. It integrates with Polymarket API, provides AI agent utilities for prediction markets, supports local and remote RAG, sources data from various services, and offers comprehensive LLM tools for prompt engineering. The architecture features modular components like APIs and scripts for managing local environments, server set-up, and CLI for end-user commands.

The Universal Numbers Library is a header-only C++ template library designed for universal number arithmetic, offering alternatives to native integer and floating-point for mixed-precision algorithm development and optimization. It tailors arithmetic types to the application's precision and dynamic range, enabling improved application performance and energy efficiency. The library provides fast implementations of special IEEE-754 formats like quarter precision, half-precision, and quad precision, as well as vendor-specific extensions. It supports static and elastic integers, decimals, fixed-points, rationals, linear floats, tapered floats, logarithmic, interval, and adaptive-precision integers, rationals, and floats. The library is suitable for AI, DSP, HPC, and HFT algorithms.

Numerapi is a Python client to the Numerai API that allows users to automatically download and upload data for the Numerai machine learning competition. It provides functionalities for downloading training data, uploading predictions, and accessing user, submission, and competitions information for both the main competition and Numerai Signals competition. Users can interact with the API using Python modules or command line interface. Tokens are required for certain actions like uploading predictions or staking, which can be obtained from Numer.ai account settings. The tool also supports features like checking new rounds, getting leaderboards, and managing stakes.

The `mystic` framework provides a collection of optimization algorithms and tools that allow the user to robustly solve hard optimization problems. It offers fine-grained power to monitor and steer optimizations during the fit processes. Optimizers can advance one iteration or run to completion, with customizable stop conditions. `mystic` optimizers share a common interface for easy swapping without writing new code. The framework supports parameter constraints, including soft and hard constraints, and provides tools for scientific machine learning, uncertainty quantification, adaptive sampling, nonlinear interpolation, and artificial intelligence. `mystic` is actively developed and welcomes user feedback and contributions.

AutoRound is an advanced weight-only quantization algorithm for low-bits LLM inference. It competes impressively against recent methods without introducing any additional inference overhead. The method adopts sign gradient descent to fine-tune rounding values and minmax values of weights in just 200 steps, often significantly outperforming SignRound with the cost of more tuning time for quantization. AutoRound is tailored for a wide range of models and consistently delivers noticeable improvements.

Time-LLM is a reprogramming framework that repurposes large language models (LLMs) for time series forecasting. It allows users to treat time series analysis as a 'language task' and effectively leverage pre-trained LLMs for forecasting. The framework involves reprogramming time series data into text representations and providing declarative prompts to guide the LLM reasoning process. Time-LLM supports various backbone models such as Llama-7B, GPT-2, and BERT, offering flexibility in model selection. The tool provides a general framework for repurposing language models for time series forecasting tasks.

SciML.ai is an open source software organization dedicated to unifying packages for scientific machine learning. It focuses on developing modular scientific simulation support software, including differential equation solvers, inverse problems methodologies, and automated model discovery. The organization aims to provide a diverse set of tools with a common interface, creating a modular, easily-extendable, and highly performant ecosystem for scientific simulations. The website serves as a platform to showcase SciML organization's packages and share news within the ecosystem. Pull requests are encouraged for contributions.

Endia is a dynamic Array library for Scientific Computing, offering automatic differentiation of arbitrary order, complex number support, dual API with PyTorch-like imperative or JAX-like functional interface, and JIT Compilation for speeding up training and inference. It can handle complex valued functions, perform both forward and reverse-mode automatic differentiation, and has a builtin JIT compiler. Endia aims to advance AI & Scientific Computing by pushing boundaries with clear algorithms, providing high-performance open-source code that remains readable and pythonic, and prioritizing clarity and educational value over exhaustive features.

FLUTE (Flexible Lookup Table Engine for LUT-quantized LLMs) is a tool designed for uniform quantization and lookup table quantization of weights in lower-precision intervals. It offers flexibility in mapping intervals to arbitrary values through a lookup table. FLUTE supports various quantization formats such as int4, int3, int2, fp4, fp3, fp2, nf4, nf3, nf2, and even custom tables. The tool also introduces new quantization algorithms like Learned Normal Float (NFL) for improved performance and calibration data learning. FLUTE provides benchmarks, model zoo, and integration with frameworks like vLLM and HuggingFace for easy deployment and usage.

Transformers_And_LLM_Are_What_You_Dont_Need is a repository that explores the limitations of transformers in time series forecasting. It contains a collection of papers, articles, and theses discussing the effectiveness of transformers and LLMs in this domain. The repository aims to provide insights into why transformers may not be the best choice for time series forecasting tasks.

The essence of Quantitative Investing

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OCamlは至高の言語