45 projects for "python finance" with 1 filter applied:

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  • 1
    Finance

    Finance

    150+ quantitative finance Python programs

    Finance is a repository that compiles structured notes and educational material related to financial analysis, markets, and quantitative finance concepts. The project focuses on explaining key principles used in finance and investment analysis, including topics such as financial statements, valuation models, portfolio theory, and financial markets. The repository is designed as a study reference for students and professionals who want to understand financial systems and the analytical...
    Downloads: 0 This Week
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  • 2
    WYGIWYH

    WYGIWYH

    A simple but powerful self-hosted finance tracker

    WYGIWYH (What You Get Is What You Have) is a self-hosted, principles-first personal finance tracker built for people who prefer a simple, intuitive approach to tracking money without complicated budgets or categories. Based on a philosophy that you should use what you earn each month for that month, it helps you understand where your funds go while keeping savings clearly separated so they aren’t accidentally dipped into for everyday expenses. The app supports multiple currencies,...
    Downloads: 7 This Week
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  • 3
    AI Hedge Fund

    AI Hedge Fund

    An AI Hedge Fund Team

    This repository demonstrates how to build a simplified, automated hedge fund strategy powered by AI/ML. It integrates financial data collection, preprocessing, feature engineering, and predictive modeling to simulate decision-making in trading. The code shows workflows for pulling stock or market data, applying machine learning algorithms to forecast trends, and generating buy/sell/hold signals based on the predictions. Its structure is educational: intended more as a proof-of-concept than a...
    Downloads: 10 This Week
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  • 4
    FinGPT

    FinGPT

    Open-Source Financial Large Language Models

    FinGPT is an open-source, finance-specialized large language model framework that blends the capabilities of general LLMs with real-time financial data feeds, domain-specific knowledge bases, and task-oriented agents to support market analysis, research automation, and decision support. It extends traditional GPT-style models by connecting them to live or historical financial datasets, news APIs, and economic indicators so that outputs are grounded in relevant and recent market conditions...
    Downloads: 8 This Week
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  • 5
    FinGLM

    FinGLM

    Committed to building an open, public welfare

    FinGLM is an open-source financial large language model initiative aimed at advancing artificial intelligence applications within the finance industry. The project focuses on developing domain-specific language models that understand financial terminology, corporate reports, and economic datasets. By combining large language model architectures with financial datasets such as corporate annual reports and structured financial records, FinGLM aims to improve AI performance on tasks that...
    Downloads: 0 This Week
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  • 6
    skfolio

    skfolio

    Python library for portfolio optimization built on top of scikit-learn

    skfolio is a Python library designed for portfolio optimization and financial risk management that integrates closely with the scikit-learn ecosystem. The project provides a unified machine learning-style framework for building, validating, and comparing portfolio allocation strategies using financial data. By following the familiar scikit-learn API design, the library allows quantitative researchers and developers to apply techniques such as model selection, cross-validation, and...
    Downloads: 10 This Week
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  • 7
    Machine Learning and Data Science Apps

    Machine Learning and Data Science Apps

    A curated list of applied machine learning and data science notebooks

    ...Instead of being a single software framework, it acts as a knowledge base containing links to practical projects, notebooks, datasets, and libraries that demonstrate how machine learning can be applied across different sectors. The repository organizes resources by industry categories such as finance, healthcare, agriculture, manufacturing, government, and retail, allowing practitioners to explore domain-specific machine learning use cases. Most examples are written in Python and frequently use Jupyter notebooks to present practical implementations and experiments. The project encourages contributions from data scientists and domain experts who want to share applied analytics projects and techniques that address real business challenges.
    Downloads: 0 This Week
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  • 8
    Public APIs

    Public APIs

    A collective list of free APIs

    public-apis is a collaboratively maintained repository that provides an extensive, categorized list of publicly available APIs for developers. Curated by community contributors and the team at APILayer, it serves as a centralized resource for discovering APIs across a wide range of domains, including data, machine learning, weather, entertainment, and finance. The project aims to make API exploration and integration more accessible by offering a single, organized index of open and...
    Downloads: 0 This Week
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  • 9
    CUDOS Framework

    CUDOS Framework

    Command Line Interface tool for Cloud Intelligence Dashboards

    The AWS Cloud Intelligence Dashboards Framework is a set of open-source tools and templates designed to help organizations deploy and manage advanced data visualization dashboards that offer insights into cost, usage, governance, and operational health across AWS environments. It is part of the AWS Solutions Library and includes CloudFormation templates, CLI commands, and pre-built dashboards that collect, process, and visualize data from AWS billing, cost management, budgets, and usage...
    Downloads: 8 This Week
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  • 10
    MLE-bench

    MLE-bench

    AI multi-agent framework for automating data-driven R&D workflows

    RD-Agent is an open source AI framework designed to automate research and development workflows in data-driven domains. It uses large language models and multiple collaborating agents to simulate the typical cycle of research, experimentation, and improvement that human data scientists follow. It separates the process into two core phases: a research stage that proposes hypotheses and ideas, and a development stage that implements and evaluates them through code execution and experiments. By...
    Downloads: 6 This Week
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  • 11
    Tally

    Tally

    Let agents classify your bank transactions

    Tally is an open-source, AI-assisted tool designed to automate the classification of personal financial transactions, helping users turn raw bank data into meaningful categories without manual tagging. At its core, Tally pairs a local rule engine with large language models so that an AI assistant (like Claude Code, Copilot, or any CLI agent) interprets, suggests, and categorizes expenses, savings, subscriptions, and income events based on your own rules and behavior. It generates...
    Downloads: 0 This Week
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  • 12
    WFGY 3.0

    WFGY 3.0

    A tension reasoning engine over 131 S-class problems

    WFGY is an experimental open-source reasoning framework designed to improve the reliability and interpretability of large language model outputs through structured reasoning layers. The project introduces a conceptual reasoning engine that analyzes complex problems by identifying semantic compression errors and residual assumptions within a system’s reasoning process. Its architecture treats reasoning failures as measurable signals that can be detected and analyzed rather than simply...
    Downloads: 0 This Week
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  • 13
    FinRobot

    FinRobot

    An Open-Source AI Agent Platform for Financial Analysis using LLMs

    FinRobot is an open-source AI framework focused on automating financial data workflows by combining data ingestion, feature engineering, model training, and automated decision-making pipelines tailored for quantitative finance applications. It provides developers and quants with structured modules to fetch market data, process time series, generate technical indicators, and construct features appropriate for machine learning models, while also supporting backtesting and evaluation metrics to...
    Downloads: 0 This Week
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  • 14
    Armadillo

    Armadillo

    fast C++ library for linear algebra & scientific computing

    * Fast C++ library for linear algebra (matrix maths) and scientific computing * Easy to use functions and syntax, deliberately similar to Matlab / Octave * Uses template meta-programming techniques to increase efficiency * Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries * Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. * Downloads:...
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    Downloads: 2,730 This Week
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  • 15
    CostPal

    CostPal

    CostPal is your personal finance manager

    ...With it's smooth intuitive interface (and by using it every day) you can spend minimum time required for tracking your personal expenses (less than 5 minutes a day!). It's purpose is to act as a scratchpad, not a standalone application for managing personal finance - for that you have CostPal. Currently only Dropbox is supported as a cloud storage used for data exchange.
    Downloads: 1 This Week
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  • 16
    fastquant

    fastquant

    Backtest and optimize your ML trading strategies with only 3 lines

    fastquant is a Python library designed to simplify quantitative financial analysis and algorithmic trading strategy development. The project focuses on making backtesting accessible by providing a high-level interface that allows users to test investment strategies with only a few lines of code. It integrates historical market data sources and trading frameworks so that users can quickly build experiments without constructing complex data pipelines.
    Downloads: 0 This Week
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  • 17
    QuantResearch

    QuantResearch

    Quantitative analysis, strategies and backtests

    QuantResearch is a large educational repository dedicated to quantitative finance, algorithmic trading, and financial machine learning research. The project contains numerous notebooks and research materials demonstrating quantitative analysis techniques used in financial markets. These include implementations of factor models, statistical arbitrage strategies, portfolio optimization methods, and reinforcement learning approaches to trading. The repository also explores financial modeling...
    Downloads: 0 This Week
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  • 18
    Odoo ERP CRM System For Local Intranets

    Odoo ERP CRM System For Local Intranets

    Web,Sales,Finance,Inventory,Manufacture,HR,Marketing,Services,Efficacy

    This VM is created for 2 reasons: 1. Very little initial setup work required to make a ERP live, within minutes. 2. This system should keep running for Years, without requiring Updates / Breakages. If you are new to Virtual Machines, then please watch the Video below ( taken from my other project. just replace td with ec wherever mentioned ) After starting this VM, please login to its administration panel with: Website Address: https://ec.local/ ( Accept Any Warnings ) Admin...
    Downloads: 0 This Week
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  • 19
    quantitative

    quantitative

    Quantized transactions python3

    The “quantitative” repository by Jack-Cherish is a tutorial-style codebase for quantitative trading written in Python — essentially a learning resource that guides users through building algorithmic trading strategies step by step. It’s organized as a sequence of lessons (lesson1, lesson2, etc.), making it approachable for learners who want to understand both theory and practice in quantitative finance. The repo is evidently tied to a popular video series (on Bilibili) that reportedly drew substantial attention, suggesting the material is meant to be both educational and hands-on. ...
    Downloads: 0 This Week
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  • 20
    Machine Learning Financial Laboratory

    Machine Learning Financial Laboratory

    MlFinLab helps portfolio managers and traders

    MlFinLab is a comprehensive Python library designed to support the development of machine learning strategies in quantitative finance and algorithmic trading. The project provides a large collection of tools that implement techniques from academic research on financial machine learning. It covers the full lifecycle of developing data-driven trading strategies, including data preprocessing, feature engineering, labeling techniques, model training, and performance evaluation. ...
    Downloads: 1 This Week
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  • 21
    Eiten

    Eiten

    Statistical and Algorithmic Investing Strategies for Everyone

    ...It is part of the broader Tradytics ecosystem, which emphasizes AI-driven financial tools for identifying opportunities in the stock market. The repository serves both as a learning resource and as a practical toolkit for traders and developers interested in quantitative finance. It encourages experimentation with different strategies and models, allowing users to adapt techniques to their own trading goals.
    Downloads: 1 This Week
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  • 22
    surpriver

    surpriver

    Find big moving stocks before they move using machine learning

    surpriver is a machine learning project designed to identify unusual stock market activity that may precede large price movements. The system analyzes historical stock price and volume data to detect anomalies that could indicate potential trading opportunities. By applying machine learning techniques to market indicators, the tool attempts to identify patterns in trading behavior that deviate significantly from normal market activity. These anomalies are interpreted as signals that a stock...
    Downloads: 0 This Week
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  • 23
    Quantitative-Notebooks

    Quantitative-Notebooks

    Educational notebooks on quantitative finance, algorithmic trading

    Quantitative-Notebooks is a curated set of Jupyter notebooks focused on quantitative finance, algorithmic investing, and data-driven portfolio analysis. While each individual notebook is aimed at practical finance workflows, the overall repository helps practitioners and learners use Python, pandas, and numerical libraries to build, test, and evaluate financial strategies using historical market data. The notebooks typically showcase how to perform backtesting, factor analysis, risk assessment, and other quantitative workflows in a reproducible, exploratory format. ...
    Downloads: 0 This Week
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  • 24
    TF Quant Finance

    TF Quant Finance

    High-performance TensorFlow library for quantitative finance

    TF Quant Finance is a high-performance library of quantitative finance components built on TensorFlow, aimed at research and production workloads. It implements pricing engines, risk measures, stochastic models, optimizers, and random number generators that are differentiable and vectorized for accelerators. Users can value options and fixed-income instruments, simulate paths, fit curves, and calibrate models while leveraging TensorFlow’s jit compilation and automatic differentiation. The...
    Downloads: 0 This Week
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  • 25
    AIAlpha

    AIAlpha

    Use unsupervised and supervised learning to predict stocks

    AIAlpha is a machine learning project focused on building predictive models for financial markets and algorithmic trading strategies. The repository explores how artificial intelligence techniques can analyze historical financial data and generate predictions about asset price movements. It provides a research-oriented environment where users can experiment with data processing pipelines, model training workflows, and quantitative trading strategies. The project typically involves collecting...
    Downloads: 0 This Week
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