Best AI tools for< Quantitative Researcher >

8VDX is an AI application that offers fine-tuned AI models for credit funds, empowering users to make data-driven decisions in the realm of credit investing. The platform enhances speed, accuracy, and strategic depth across various financial instruments like bonds, private credit, and CLOs. By leveraging AI technology, 8VDX streamlines the investment analysis process, automates bond screening, and provides continuous learning from surveillance to optimize investment strategies.

Kahuna AI is an AI-powered platform designed to provide superpowers for event-driven investing. It caters to top hedge funds and selectively onboards users daily. The platform is made with love in NYC by Kahuna AI, Inc.

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.

STRATxAI is an AI-driven investment strategy platform that offers customized alpha-generating portfolios for modern investors. The platform, developed by a team of quantitative hedge fund professionals and machine-learning engineers, leverages advanced AI and proprietary quantitative technology to streamline the creation, implementation, and management of bespoke, data-driven investment strategies. With a focus on innovation and adaptability, STRATxAI model portfolios harness extensive data to deliver client-centric customization and risk-adjusted returns. The Alana Investor Platform provides an intuitive design catering to both no-code and know-code professional users, offering portfolio optimization, data-driven insights, and smart rebalancing for optimal asset allocation and effective risk management.

The website offers a precision workflow solution for enterprises in the finance industry, combining AI technology with human oversight to empower financial decisions. It provides features such as accurate search citations, multilingual models, and complex human-in-loop automation. The application integrates seamlessly with existing platforms, uses advanced AI models, and offers meaningful time savings. Users can benefit from the application's ability to ingest unstructured data, improve over time, and avoid hallucinations.

EquBot is an AI tool designed for investment and wealth management. It offers non-advisory institutional solutions powered by IBM Watson. The tool can be accessed at www.QuantumStreetAI.com. EquBot is based in San Francisco, California, and provides advanced AI-driven services to optimize investment decisions and wealth management strategies.

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.

Quantum AI is an advanced AI-powered trading platform that revolutionizes the trading experience by empowering users to make intelligent and strategic decisions. The platform offers a user-friendly interface, automated trading system, expert-designed strategies, risk-free demo mode, and top-level security. With round-the-clock expert assistance, exceptional satisfaction levels, and multilingual support, Quantum AI ensures a seamless trading experience for users worldwide.

The Trading AI is a generative AI financial platform that revolutionizes investment decisions. It offers an all-in-one solution for portfolio management, AI-assisted strategies, backtesting, and algorithmic trading. The platform features an intuitive user-friendly interface, lightning-fast backtesting, advanced live dashboard, and a strategy builder requiring no programming skills. Users can join the VIP Club for exclusive advantages, participate in tournaments, and monetize their strategies in the marketplace. The platform leverages AI to provide data-backed intelligence for optimized trading decisions.

MetaMevs is an advanced AI-powered trading solution designed to maximize profits in the fast-paced world of decentralized finance (DeFi). The platform offers cutting-edge technology and customizable solutions to help traders stay ahead of the curve and capitalize on market opportunities. With features like Sandwich Mevbot, HFT Futures and Spot Bot, FlashLoan Arbitrage Bot, and MetaMev Sniper, MetaMevs provides unmatched performance, security, and reliability for users to optimize their trading strategies.

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.

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.

Lektify is an AI-powered platform designed to revolutionize the way users manage their investment portfolios. By leveraging advanced artificial intelligence algorithms, Lektify helps users discover top-performing stocks and make informed investment decisions. The platform provides valuable insights and recommendations based on extensive data analysis, enabling users to optimize their investment strategies and maximize returns. With Lektify, users can stay ahead of market trends and enhance their portfolio performance with confidence.

Simudyne is an enterprise simulation software powered by AI technology. It allows large financial institutions to simulate various future scenarios efficiently and measure their impact in a safe virtual environment. The software offers solutions for environment, social and governance issues, market execution, financial crime analytics, and risk management. Simudyne's technology is secure, distributable, and Cloudera certified, providing a robust library of code for specialized functions. The platform also utilizes agent-based modeling to bridge the gap between theoretical and real-world scenarios in the financial services sector.

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.

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.

FinRobot is an open-source AI agent platform designed for financial applications using large language models. It transcends the scope of FinGPT, offering a comprehensive solution that integrates a diverse array of AI technologies. The platform's versatility and adaptability cater to the multifaceted needs of the financial industry. FinRobot's ecosystem is organized into four layers, including Financial AI Agents Layer, Financial LLMs Algorithms Layer, LLMOps and DataOps Layers, and Multi-source LLM Foundation Models Layer. The platform's agent workflow involves Perception, Brain, and Action modules to capture, process, and execute financial data and insights. The Smart Scheduler optimizes model diversity and selection for tasks, managed by components like Director Agent, Agent Registration, Agent Adaptor, and Task Manager. The tool provides a structured file organization with subfolders for agents, data sources, and functional modules, along with installation instructions and hands-on tutorials.

This repository contains the Python source code for FINMEM, a Performance-Enhanced Large Language Model Trading Agent with Layered Memory and Character Design. It introduces FinMem, a novel LLM-based agent framework devised for financial decision-making, encompassing three core modules: Profiling, Memory with layered processing, and Decision-making. FinMem's memory module aligns closely with the cognitive structure of human traders, offering robust interpretability and real-time tuning. The framework enables the agent to self-evolve its professional knowledge, react agilely to new investment cues, and continuously refine trading decisions in the volatile financial environment. It presents a cutting-edge LLM agent framework for automated trading, boosting cumulative investment returns.

finagg is a Python package that provides implementations of popular and free financial APIs, tools for aggregating historical data from those APIs into SQL databases, and tools for transforming aggregated data into features useful for analysis and AI/ML. It offers documentation, installation instructions, and basic usage examples for exploring various financial APIs and features. Users can install recommended datasets from 3rd party APIs into a local SQL database, access Bureau of Economic Analysis (BEA) data, Federal Reserve Economic Data (FRED), Securities and Exchange Commission (SEC) filings, and more. The package also allows users to explore raw data features, install refined data features, and perform refined aggregations of raw data. Configuration options for API keys, user agents, and data locations are provided, along with information on dependencies and related projects.

This repository focuses on the application of Large Language Models (LLMs) in the field of finance. It provides insights and knowledge about how LLMs can be utilized in various scenarios within the finance industry, particularly in generating AI agents. The repository aims to explore the potential of LLMs to enhance financial processes and decision-making through the use of advanced natural language processing techniques.

PIXIU is a project designed to support the development, fine-tuning, and evaluation of Large Language Models (LLMs) in the financial domain. It includes components like FinBen, a Financial Language Understanding and Prediction Evaluation Benchmark, FIT, a Financial Instruction Dataset, and FinMA, a Financial Large Language Model. The project provides open resources, multi-task and multi-modal financial data, and diverse financial tasks for training and evaluation. It aims to encourage open research and transparency in the financial NLP field.

The gpt-bitcoin repository is focused on creating an automated trading system for Bitcoin using GPT AI technology. It provides different versions of trading strategies utilizing various data sources such as OHLCV, Moving Averages, RSI, Stochastic Oscillator, MACD, Bollinger Bands, Orderbook Data, news data, fear/greed index, and chart images. Users can set up the system by creating a .env file with necessary API keys and installing required dependencies. The repository also includes instructions for setting up the environment on local machines and AWS EC2 Ubuntu servers. The future plan includes expanding the system to support other cryptocurrency exchanges like Bithumb, Binance, Coinbase, OKX, and Bybit.

Solana AI Trade Bot is an advanced trading tool specifically designed for meme token trading on the Solana blockchain. It leverages AI technology powered by GPT-4.0 to automate trades, identify low-risk/high-potential tokens, and assist in token creation and management. The bot offers cross-platform compatibility and a range of configurable settings for buying, selling, and filtering tokens. Users can benefit from real-time AI support and enhance their trading experience with features like automatic selling, slippage management, and profit/loss calculations. To optimize performance, it is recommended to connect the bot to a private light node for efficient trading execution.

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.

EvalAI is an open-source platform for evaluating and comparing machine learning (ML) and artificial intelligence (AI) algorithms at scale. It provides a central leaderboard and submission interface, making it easier for researchers to reproduce results mentioned in papers and perform reliable & accurate quantitative analysis. EvalAI also offers features such as custom evaluation protocols and phases, remote evaluation, evaluation inside environments, CLI support, portability, and faster evaluation.

Awesome LLM is a curated list of resources related to Large Language Models (LLMs), including models, projects, datasets, benchmarks, materials, papers, posts, GitHub repositories, HuggingFace repositories, and reading materials. It provides detailed information on various LLMs, their parameter sizes, announcement dates, and contributors. The repository covers a wide range of LLM-related topics and serves as a valuable resource for researchers, developers, and enthusiasts interested in the field of natural language processing and artificial intelligence.

**Curated collection of papers and resources on how to unlock the reasoning ability of LLMs and MLLMs.** **Description in less than 400 words, no line breaks and quotation marks.** Large Language Models (LLMs) have revolutionized the NLP landscape, showing improved performance and sample efficiency over smaller models. However, increasing model size alone has not proved sufficient for high performance on challenging reasoning tasks, such as solving arithmetic or commonsense problems. This curated collection of papers and resources presents the latest advancements in unlocking the reasoning abilities of LLMs and Multimodal LLMs (MLLMs). It covers various techniques, benchmarks, and applications, providing a comprehensive overview of the field. **5 jobs suitable for this tool, in lowercase letters.** - content writer - researcher - data analyst - software engineer - product manager **Keywords of the tool, in lowercase letters.** - llm - reasoning - multimodal - chain-of-thought - prompt engineering **5 specific tasks user can use this tool to do, in less than 3 words, Verb + noun form, in daily spoken language.** - write a story - answer a question - translate a language - generate code - summarize a document

Quantus is a toolkit designed for the evaluation of neural network explanations. It offers more than 30 metrics in 6 categories for eXplainable Artificial Intelligence (XAI) evaluation. The toolkit supports different data types (image, time-series, tabular, NLP) and models (PyTorch, TensorFlow). It provides built-in support for explanation methods like captum, tf-explain, and zennit. Quantus is under active development and aims to provide a comprehensive set of quantitative evaluation metrics for XAI methods.

This repository provides a curated list of papers, datasets, and resources related to the detection and mitigation of hallucinations in large language models (LLMs). Hallucinations refer to the generation of factually incorrect or nonsensical text by LLMs, which can be a significant challenge for their use in real-world applications. The resources in this repository aim to help researchers and practitioners better understand and address this issue.

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.

LLMs4TS is a repository focused on the application of cutting-edge AI technologies for time-series analysis. It covers advanced topics such as self-supervised learning, Graph Neural Networks for Time Series, Large Language Models for Time Series, Diffusion models, Mixture-of-Experts architectures, and Mamba models. The resources in this repository span various domains like healthcare, finance, and traffic, offering tutorials, courses, and workshops from prestigious conferences. Whether you're a professional, data scientist, or researcher, the tools and techniques in this repository can enhance your time-series data analysis capabilities.

Taiyi (太一) is a bilingual large language model fine-tuned for diverse biomedical tasks. It aims to facilitate communication between healthcare professionals and patients, provide medical information, and assist in diagnosis, biomedical knowledge discovery, drug development, and personalized healthcare solutions. The model is based on the Qwen-7B-base model and has been fine-tuned using rich bilingual instruction data. It covers tasks such as question answering, biomedical dialogue, medical report generation, biomedical information extraction, machine translation, title generation, text classification, and text semantic similarity. The project also provides standardized data formats, model training details, model inference guidelines, and overall performance metrics across various BioNLP tasks.

Raga LLM Hub is a comprehensive evaluation toolkit for Language and Learning Models (LLMs) with over 100 meticulously designed metrics. It allows developers and organizations to evaluate and compare LLMs effectively, establishing guardrails for LLMs and Retrieval Augmented Generation (RAG) applications. The platform assesses aspects like Relevance & Understanding, Content Quality, Hallucination, Safety & Bias, Context Relevance, Guardrails, and Vulnerability scanning, along with Metric-Based Tests for quantitative analysis. It helps teams identify and fix issues throughout the LLM lifecycle, revolutionizing reliability and trustworthiness.

AiTreasureBox is a versatile AI tool that provides a collection of pre-trained models and algorithms for various machine learning tasks. It simplifies the process of implementing AI solutions by offering ready-to-use components that can be easily integrated into projects. With AiTreasureBox, users can quickly prototype and deploy AI applications without the need for extensive knowledge in machine learning or deep learning. The tool covers a wide range of tasks such as image classification, text generation, sentiment analysis, object detection, and more. It is designed to be user-friendly and accessible to both beginners and experienced developers, making AI development more efficient and accessible to a wider audience.

Especialista em indicadores VWAP, sempre responde em português.

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Expert in health qualitative research and thematic analysis.

A seasoned Market Research Director specializing in qualitative analysis.

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Analyzes tech stocks with in-depth, qualitative and quantitative analysis

对各种量化问题进行拆解和粗略的估算。注意这种估算主要是靠推测，而不是靠准确的数据，因此仅供参考。理想情况下，估算结果和真实值差距可能在1个数量级以内。即使数值不准确，也希望拆解思路对你有所启发。

Stock time-series data analysis

精通数学分析和高等代数，使用中文回答。

Advanced AI for complex computations and data analysis.

OCamlは至高の言語

The essence of Quantitative Investing

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VaultCraft trains users to create automated yield strategies using the VaultCraft VCI & SDK

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Specializes in searching MQL codebase for EAs, indicators, and scripts.

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